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1 School of Civil Engineering
Highway Traffic and Safety Analyses Types of Traffic Studies Purdue University School of Civil Engineering West Lafayette

2 What Answers Are Sought?
Current highway and parking use Current traffic characteristics Current traffic and parking quality Current highway safety How to improve current traffic conditions Impact of new highway projects/improvements Impact of a new land development Future traffic conditions (limited change in traffic pattern)

3 Scale of the Studies Single facilities (intersection, road section)
Arterial streets Corridors (several parallel roads) Local areas (part of the network) Entire systems (city, county, state)

4 Traditional Traffic Studies (according to McShane et al.)
Volume studies Speed studies Travel time studies Delay studies Density studies Headway and spacing studies Accident studies (classified by McShane et al. as a special study)

5 Special Traffic Studies and Analyses
Location studies Traffic impact studies and analyses Safety analyses Identification of hazardous locations Identification of hazard sources Identification of countermeasures Corridor studies Parking studies Congestion analyses Pedestrian studies Before-and-after studies

6 Who Are Traffic Engineers’ Clients?
Policy makers Highway administration State County City Citizens groups Land developers Business owners

7 Example Studies Wal-Mart study in Centerville (Utah)

8 Traffic Studies and Analyses offered by HIGGINS ASSOCIATES, CA ( Access & Circulation Studies Accident Analysis Freeway Operations Analysis Speed Studies Traffic Count Programs Traffic Handling for Special Events Traffic Impact Studies Traffic Operations Studies Traffic Safety Studies Traffic Signal Operations & Timing

9 HIGGINS ASSOCIATES, CA (http://www.kbhiggins.com/traffic.html)
Scotts Valley Drive, City of Scotts Valley Performed detailed traffic data collection including video tapes, measurement of delay, residual queues and travel times for a three intersection interchange signal system. Optimized cycle lengths, phase sequences and splits, and implemented in the field with Caltrans staff. Documented optimized traffic operations and noted improvements in delay and queue lengths. The optimization was performed using Synchro 3 and TSPPD (Time Space Platoon Progression Diagram). Morgan Hill On-Call Municipal Traffic Engineering Services Responded to citizen complaints. Performed warrant analyses for requested traffic control devices throughout the City. Provided site plan review. Performed signing, striping and signal design.

10 School of Civil Engineering
Highway Traffic and Safety Analyses Lecture 3: Traffic Impact Analysis (1) Purdue University School of Civil Engineering West Lafayette

11 The Case of Potawatomi Bingo and Casino Parlor Expansion

12 Traffic Impact Analysis (1)
Warrants for analysis Review process Issues addressed by traffic impact studies Extent of study Study area Time horizon and period of analysis Data needed

13 Warrants for Traffic Impact Analysis
Example cases when an impact analysis may be needed: Zoning/rezoning Land subdivision Site plan approval Building permit Amendments to a long-term plan Permit for major driveways

14 Warrants for Traffic Impact Analysis
Criteria may be locally established based on: trip generation, development or area characteristics, or localized conditions. Recommended criterion in lieu of local criteria: 100 or more added vehicle trips in the peak direction (inbound/outbound) during the site’s peak hour traffic

15 Warrants for Traffic Impact Analysis
Example criteria for warrants: Number of peak hour trips Number of daily trips Amount of acreage to rezone Number of dwelling units or square footage in the project Project in a sensitive area

16 Review Process Parties involved
Developer (land owner, business owner) Reviewer (local, state transportation agency) Preparer (consulting company) Early and open discussion between the three parties is important

17 Review Process Objectives Mutual understanding Realistic awareness
Objectiveness of the review Fair assessment of impacts Identification of truly needed improvements

18 Issues to Address in Analysis
Required extent of analysis Needed guidelines and manuals Study area Time horizon and period of analysis Needed data Techniques for data collection and analysis Target level of service Isolating the studied traffic impact from other impacts Needed traffic improvements Phasing improvements Changes needed in the project (development) Documentation

19 Required Analysis Extent
Which components of the site impact studies are needed? How detail should the analysis be? How large should a study area be? How long and how many time horizons are needed? Is field data collection needed? Should any adjacent development be considered? Should planned highway improvements be accounted for? Are safety, sigh distance, queuing and other analyses needed?

20 Needed Guidelines and Manuals
Guidelines for access/traffic analysis Trip generation Manual of traffic engineering studies HCM MUTCD Traffic engineering software manuals Safety analysis guidelines (future HSM)

21 Study Area The Study Area must include the Impact Area
Each impact analysis includes all site access points and major intersections adjacent to the site Additional area may be included based on local or site specific issues (for example, congested locations with additional traffic generated by the project) Excessively large area increases costs of analysis

22 Time Horizon Development Suggested Analysis Horizons
< 500 peak-hour trips, single-phase development Opening year with full build-out and occupancy assumed peak-hour trips, single phase development Five years after opening date >1000 peak-hour trips, single phase development Adopted transportation plan horizon year (if diversion from the plan) >500, multiple-phase development Opening years of each phase Year with complete build-out and occupancy Five years after year of complete build-out and occupancy

23 Period of Analysis Seasonal, weekly, and daily volumes variations
Design volume (20-40th highest hourly volume) Approximation of the design hour Available volume data vs. own counts Average day vs. “design day” Background traffic vs. on-site generated traffic Adjustment factors Worst 15-minutes in the design hour

24 Useful Traffic and Crash Data
Recent and historical daily and hourly volume counts (Figure 3-1) Recent intersection turning movement counts (Figure 3-2) Volume variation adjustment factors Projected volumes from previous studies and regional plans Origin-destination or trip distribution data Accident statistics where safety problems are anticipated (three years)

25 Useful Land Use Data Current land use, densities, and occupancy
Approved development projects and planned completion dates Anticipated development of other parcels Land use master plan Zoning in vicinity Current and future population and employment by traffic analysis zone (for site traffic distribution)

26 Useful Infrastructure Data
Current street characteristics (direction of flows, number of lanes, right of way, access control, traffic control) (Figure 3-3) Roadway functional classification Traffic signal locations, coordination, timing Adopted local and regional plans Transit service and usage Pedestrian and bicycles linkage and usage Parking facilities

27 Figure 3-1 Current Daily Traffic Counts
Back

28 Figure 3-2 Turning Movement Counts
Back

29 Figure 3-3 Infrastructure Data
Back

30 Highway Traffic and Safety Analyses
Lecture 4: Traffic Impact Analysis (2) Purdue University School of Civil Engineering West Lafayette

31 Lecture Outline Traffic in the study area
Methods of traffic forecasting Network modeling Trends method Growth rate method Traffic generation method Pass-by trips Analogy method - own data collection

32 Traffic in the Study Area Future
Analysis Area Study Area Future Background Traffic Analyzed Site Future Generated Traffic

33 Methods of Traffic Forecasting
Large projects Network traffic modeling Small projects – Background traffic Trends method, or Growth factor method Generated traffic ITE trip generation tables, or Analogy method

34 Network Traffic Modeling Large Projects

35 Network Traffic Modeling Large Projects
Transportation planning studies Rather crude representation of networks May be appropriate for large projects Interpolation possible if the planning and study horizons are different (see Figure) Possible discrepancies between the plan assumptions and the land use and street system in the study horizon year Adjustments to bring details may be needed Network modeling for the impact study should be considered (QRS)

36 Trends Method Background Traffic for Small Projects
ADT or Hourly Volume Rate Now Year

37 Growth Rate (Factor) Method Background Traffic for Small Projects
Future Volume = Past Volume · (1 + Growth Rate)N where N = Future Year – Past Year Example: 1,200 veh/h in 2000, 3% growth rate Volume in 2004 = 1,200 · ( ) = 1,350 veh/h

38 ITE Trip Generation Tables Generated Traffic for Small Projects

39 ITE Trip Generation Tables Generated Traffic for Small Projects
General Office Building (710) ITE Trip Generation Tables Generated Traffic for Small Projects

40 ITE Trip Generation Tables
Equations vs. rates When using rates, use average with local adjustments Weekday, weekend, vs. peak hour (see Table) Select the best descriptor (development unit) Involved uncertainty Limitations: suburban, only cars, national averages, single developments, diverted trips, pass-by trips

41 Pass-by Trips No new development 1,000 veh/h
Predicted driveway traffic = 550 trip ends/h (ITE tables) New development Primary traffic generated Pass-by traffic (320 trip ends/h) 1,000 veh/h (160 vehicles stop by) Primary traffic generated = 550 – 320 = 230 trip ends/h

42 Pass-by Trips For shopping centers, weekday, PM peak (ITE, 1991)
ln(p) = ·ln(x) R2=0.34 where p is the percent of the driveway traffic volume which is the pass-by traffic.

43 Pass-by Trips Estimate the primary traffic generated by a shopping center and added to the background traffic during the weekday PM peak. The gross area of the shopping center is 120,000 ft2. The traffic entering and exiting the center is 450 veh/h. Calculations: ln(p) = ·ln(120) = 3.74, p = 42 % Primary traffic = (1 – 42/100)·450 = 260 veh/h

44 Analogy Method – Own Data Collection Generated Traffic for Small Projects
Select generators with similar characteristics Daily machine counts for at least three days Period with peak hour counts during “design days” Manual counts can be used to adjust machine counts Interviews with travelers, O-D counts techniques (primary vs. pass-by trip ends) Interviews with the site owner or manager (development characteristics, occupancy level, etc.) Submit data to the ITE using special forms

45 Typical Peak Hours Land Use Typical Peak Hours Peak Direction
Residential 7-9 am weekdays Outbound 4-6 pm weekdays Inbound Regional Shopping 5-6 pm weekdays Total 12:30-1:30 Saturdays 2:30-3:30 Saturdays Office Industrial Varies with employee shift schedule Recreational Varies with type of activity Back

46 Interpolation to Use Forecasts of Planning Studies
ADT Impact Study Horizon Planning Study Horizon Now Year Back

47 School of Civil Engineering
Highway Traffic and Safety Analyses Lecture 5: Traffic Distribution and Assignment in Impact Analyses Purdue University School of Civil Engineering West Lafayette

48 Lecture Outline Four-step traffic network modeling (large projects)
Traffic forecast task for small and medium projects Trip distribution Analogy method Crude gravity method Traffic assignment to routes Non-car trips (pedestrians, bikes, public transit)

49 Four-Step Traffic Network Modeling (Large Projects)

50 Traffic Forecast Task for Medium and Small Projects
Background traffic (car and non-car) Trends or growth factor methods Traffic already assigned New developments (analyzed one and other) Trip generation tables Car trips only How to distribute, and assign car traffic generated by new developments? What about non-car trips?

51 Traffic Forecast Task for Medium and Small Projects
1 2 3 4 5 Impact Area (Study Area)

52 Traffic Distribution Judgment (most popular) Analogy method
1 2 3 Traffic Distribution Judgment (most popular) Analogy method Crude gravity method

53 Analogy Method Existing similar development
Near the proposed development Data collection techniques License plate technique Driver response survey

54 Market Area System Area Market Area Development Site Impact Area
More than 80% of trips System Area

55 Market Area

56 Market Area Market Area Impact Area 12,000 trip ends/day

57 Gravity Method 1 3 2 where: Tij= number of trip from zone i to zone j,
1 2 3 where: Tij= number of trip from zone i to zone j, Pi = trip production in zone i, Aj = trip attraction in zone j, Fij = inverse function of travel time from i to j, Kij = adjustment factors for flow Tij.

58 Crude Gravity Method where: Tij = trips between zones i and j,
1 2 3 where: Tij = trips between zones i and j, P0 = outbound trips from the new development, A0 = inbound trips to the new development, Sj = relevant socioeconomic characteristic of zone j in the market area.

59 Crude Gravity Method Market Area Impact Area 6,000 population
5,000 work places 6,000 population 1,000 work places 3,000 population no work places Impact Area

60 Crude Gravity Method 2,000 outbound trips/day 0 % 16 % Impact Area
84 % 16 % 0 % 320 1,680 3,000 population no work places 6,000 population 1,000 work places Impact Area 1,000 population no work places 10,000 population 5,000 work places Residential development

61 Crude Gravity Method 2,000 outbound trips/day 15 % 30 % 5 %
50 % 30 % 15 % 5 % 600 300 1,000 100 3,000 population no work places 6,000 population 1,000 work places Impact Area 1,000 population no work places 10,000 population 5,000 work places Office building

62 Trip Distribution (daily)
50% 35%

63 Route Assignment

64 Route Assignment

65 Route Assignment Judgment (most popular) Simplified logit method

66 Trip Assignment Logit Method
Utility of route U = function of route length, travel time, trip cost, etc. Example: U = x travel time in minutes (just an example) Two routes, L1 = 1.5 mi, V1 = 30 mi/h, L2 = 2.0 mi, V2 = 35 mi/h. U1 = -1.50, U2 = -1.71

67 Trip Assignment Logit Method
Logit equation where: Pi = proportion of travelers using route i, Ui = utility of route i. Example: U1 = -1.50, U2 = -1.71, In the all-or-nothing method, all the trips are assigned to the best route.

68 Example Traffic Forecast (format important!)
230 = traffic generated by the development (500) = total traffic Example Traffic Forecast (format important!)

69 Non-car Trips Judgment Analogy method Logit method

70 Highway Traffic and Safety Analyses
Lecture 6: Traffic Volume Variability and Studies Purdue University School of Civil Engineering West Lafayette

71 Lecture Outline Definitions Volumes variability Estimation of AADT
Design volume Counting techniques Types of volume studies

72 Definitions Count – number of vehicles/travelers passing a highway spot in a counting period Volume – number of vehicles/travelers passing a highway spot per unit time Capacity – maximum and repeatable volume of vehicles/travelers Demand – volume not influenced by highway capacity

73 Definitions Capacity Demand Traffic Intensity Volume Congestion Time

74 Definitions Volume Traffic Intensity Time

75 AADT vs. ADT AADT = Annual Average Daily Traffic (veh/day)
ADT = Average Daily Traffic (veh/day) represents periods other than a year Weekly ADT, Monthly ADT

76 Seasonal Variability of Monthly ADT
128 % Counts in August on a rural road have given August Monthly ADT = 10,000 veh/h What is Annual ADT? AADT = 10,000∙(1/1.28) =10,000∙0.781 AADT = 7,810 veh/day 0.781 = Seasonal Factor (SF)

77 Weekly Variability of Daily Volumes
0.158 Thursday daily traffic on a suburban arterial = 30,000 veh/day Weekly ADT = ? = 30,000∙(1/0.158/7) = = 30,000∙0.904 = Weekly ADT = 27,100 veh/day 0.904 = Weekly Factor (WF) Weekly ADT ≈ Monthly ADT

78 Seasonal and Weekly Variability of Daily Volumes
Counts in average weekday in March, recreational road, in Minnesota, March Weekday ADT = 20,000 veh/day AADT=? AADT = 20,000∙(1/0.80) = 20,000∙1.25 AADT = 25,000 veh/day 1.25 = WF∙SF

79 Daily Variability of Hourly Traffic
Vehicle counts on a local road on Wednesday between 4-7 PM gave total 2,350 vehicles Wednesday ADT = ? Counting Hour Percent of Daily Traffic Total Wednesday ADT = 2,350∙(1/0.251) = 2,350∙3.98 = 9,360 veh/h 3.98 = Daily Factor (DF)

80 AADT Estimation with Short Counts
AADT = V·DF·WF∙SF where: AADT = Annual Average Daily Traffic, V = count in veh, DF = Daily Factor, WF = Weekly Factor, SF = Seasonal Factor, More than one day of counting (three days) and extended count periods each day are recommended

81 Day-to-day Variability of Daily Profile
95% of volumes

82 Within-Week Variability of Daily Flow Composition

83 AADT Estimation - Exercise
Vehicle counts have been conducted in mid March on Thursday between 3 and 5 PM. Known: Total count V=2,000 veh, Volume between 3 and 4 PM equals 6 % of daily traffic Volume between 4 and 5 PM equals 7 % of daily traffic Thursday daily traffic equals 16 % of weekly traffic March daily traffic equals 98 % of AADT Calculate Daily Factor DF Weekly Factor WF Seasonal Factor SF AADT

84 AADT Estimation - Exercise
DF DF = 1/(Proportion of Daily Traffic) DF = 1/( ) = 7.69 WF WF = 1/(Proportion of Weekly Traffic)/7 WF = 1/0.16/7 = 0.89 SF SF = 1/(Proportion of AADT) SF = 1/0.98 = 1.02 AADT AADT = V·DF·WF∙SF V = 2,000 vehicles AADT = 2,000∙7.69·0.89·1.02 = 13,800 veh/day

85 Design Volume Definition
K 30

86 Design Volume Estimation Using Factor K
DHV = AADT·K·D AADT in the horizon year (veh/day) K = proportion of AADT during the 30th rank hour (other ranks may be used too) D = directional split (busier direction)

87 Design Volume Estimation Using Factor K

88 Alternative Estimation of Design Volume
Estimate AADT1 for the year with available vehicle counts, AADT1=V∙DF1∙WF1∙SF1 Predict AADT2 for the future year using a growth factor AADT2=AADT1∙GF Select month, day of week, and hour in the future year when the volume is likely to be close to the design volume Convert the predicted AADT2 to the hourly volume for the hour selected in step 3, DHV=AADT2/DF2/WF2/SF2 or DHV = V ∙ (DF1/DF2) ∙ (WF1/WF2) ∙ (SF1/SF2) ∙ GF

89 Short-Term Volume Variability
Traffic performance is checked for the worst 15 minutes of the design hour

90 Peak Hour Factor Estimation of PHF
PHF = Hourly Count/(4·Highest 15-min Count) Use of PHF Peak Volume Rate = DHV/PHF

91 Types of Volume Studies
Intersection counts (duration depends on the purpose, 15-minute intervals or shorter, turning volumes) Pedestrian counts (duration depends on the purpose, 5-minute intervals or longer) Cordon counts (one weekday + travelers’ survey) Screen line counts (hourly counts for a weekday) Area wide counts Control counts (hourly counts with permanent stations) Coverage counts (hourly counts for one or two days)

92 Counting Techniques Manual counting Machine counting
For one day or less Turning volumes, pedestrians, test counts Pencil and paper Electronic manual recorders Machine counting For longer counting periods: one day or longer Permanent stations (inductive loops, WIM) Portable stations (pneumatic, inductive, magnetic, video, etc.)

93 Origin-Destination Studies
External (on the road) Cordon studies Roadside interviews Postcard studies License plate studies Tag-on vehicle method Lights-on studies Transit passenger questionnaire

94 Origin-Destination Studies
Internal (off the road) Dwelling unit interviews Vehicle owner mail questionnaires Interview at traffic generators (workplace, etc) Truck and taxi surveys

95 Lecture 7: Parking Studies
Highway Traffic and Safety Analyses Lecture 7: Parking Studies Purdue University School of Civil Engineering West Lafayette

96 Lecture Outline Definitions Demand vs. Supply Parking Inventory
Accumulation Studies License Plate Checks

97 Definitions Parking volume (veh/day) Parking accumulation (veh)
Number of vehicles parking in a study area during a specific length of time (typically a day). Vehicles leaving the parking area and returning are counted twice. Parking accumulation (veh) Number of vehicles parking at a specific time Parking accumulation curve A curve showing variation of parking accumulation over time

98 Definitions Parking load (veh-hour) Parking duration (hour)
The area under the parking accumulation curve Parking duration (hour) Average parking time Parking turnover (veh/space) Number of vehicles per parking space during the analyzed period

99 Accumulation Curve Accumulation (veh) Time (hrs)

100 Demand vs. Supply Maximum Demand No. of Legal Spots Accumulation (veh)
Time (hrs) Accumulation (veh) No. of Legal Spots True Demand

101 Demand vs. Supply Hidden Demand Accumulation (veh) Illegal Parking
Time (hrs) Accumulation (veh) Hidden Demand Illegal Parking

102 Parking Inventory Number of parking spaces
Time limits and hours of operation Type of ownership Rates and method of fee collection Parking regulations at curb spaces (loading zones, passenger zones, handicapped zones, taxi zones, bus zones) Lot or garage Degree of permanency

103 Parking Inventory Numbering System
Curb Face Number 1 2 4 3 Block Number 6 7 5 6 7 5 Off-Street Facility Number

104 Parking Inventory Summary Sheet
6 5 1 2 4 3 7 Block Number Curb Face Number Off-Street Facility Number Parking Inventory Summary Sheet Block Facility Inventory Data Parking Spaces Non-public Spaces Data 3 Data 4 Data 5 ….. 5 1 7 2 12 3 6 4

105 Area and Time of Parking Accumulation Studies
Study area – parking area for the studied development On days when maximum parking is expected Counting period should include time of intense parking 6 AM to 8 PM for employment and commercial sites (several times) 1 AM to 5 AM should be covered in residential areas (once)

106 Techniques of Parking Demand Studies
Cordon-based without vehicles identification Cordon-based with vehicles identification Route-based without vehicles identification Route-based with vehicles identification

107 Cordon-Based Parking Study without Vehicles Identification
Estimating the initial accumulation by counting along routes Continuous counting of vehicles entering and exiting the study area Estimating the final accumulation by counting along routes

108 Cordon-Based Parking Study with Vehicles Identification
Estimating the initial accumulation by counting along routes Manual recording of license numbers when low flows Videotaping of license numbers with post-processing when large flows Estimating the final accumulation by counting along routes

109 Route-Based Accumulation Studies without Vehicles Identification
Counting along a pre-specified route that covers the study area Careful routes design for large areas (multiple field checkers) Counting vehicles or empty spaces (what easier) Counting interval: one or two hours 5-hour shifts Common starting point helps supervising

110 Route-Based Accumulation Studies with Vehicles Identification
Hand-held computers, tape recorders, or paper worksheets Counting interval: 1/3 of the average parking duration and not longer than 1-2 hours 1 ½ minutes per one parking space needed 5-hour shifts Careful routes design for large areas (multiple field checkers) Common starting point helps supervising

111 Exercise 1 Parking vehicles were counted every two hours
Draw a parking accumulation curve, calculate the parking load based on the parking counts.

112 License Plate Checks Calculations
Turnover = Parking Volume/Parking Spaces Parking Load = Av. Accumulation x No. of Intervals x Av. Interval Average Parking Duration = Parking Load/Parking Volume

113 Exercise 2 The license plates were noted every two hours.
Determine the parking volume and calculate the parking turnover and the average parking duration.

114 Results Obtainable from Various Parking Study Techniques
Cordon without Identification Cordon with Identification Routes without Identification Routes with Identification Accumulation Yes Volume No Turnover Average Duration Variability of Duration Space use Illegal parking Yes/No Enforcement

115 Lecture 8: Speed, Travel Time, and Delay Studies
Highway Traffic and Safety Analyses Lecture 8: Speed, Travel Time, and Delay Studies Purdue University School of Civil Engineering West Lafayette

116 Outline Speed Travel time Delay Definitions Study applications
Measurement techniques Measurement issues Data analysis Travel time Applications Delay

117 SPEED

118 Definitions Spot speed – a speed of a vehicle at a spot (instantaneous speed) Space-mean speed – an average instantaneous speed of vehicles that occupy a highway segment Time-mean speed – an average instantaneous speed of vehicles passing a spot during a period

119 Definitions Free-flow speed – vehicle speed when other vehicles do not impede Running speed – vehicle speed not influenced by intersections and other spot obstructions Travel speed – average speed along a highway segment

120 Applications Traffic operations and control
speed limits, advisory speeds, critical speeds, no-passing zones, signs location, signals design Advanced Traveler Information Systems Houston San Diego Highway design Highway safety Speed trends Indiana (p.37 and following) Effectiveness of controls and programs

121 Measurement Techniques
Manual Vehicle detectors Radar

122 Bias in Radar Measurements
Vehicle Radar beam True Speeds (mph) Angle  (o) Measured Speeds (mph)

123 Sample Size Determination
Test measurements Estimation of required size based on the test results N = (S·K/E)2 where: N = minimum number of required speed observations, S = speed standard deviation estimated from test sample, E = permitted error in mean speed estimate, for example, E = 5 mi/h, K = depends on desired confidence level and size of test sample, Test sample larger than 30 → K = 1.96 for 95% confidence (standardized normal distribution), Test sample 30 or smaller → K = varies with the test sample size and confidence level (Student-t distribution). Additional measurements if required

124 Sample Size -Example Initial measurements gave speeds: 45, 41, 32, 50, 49, 35 (mph). How many more speeds are required if the permitted error is 3 mph at the level of confidence 95%? Mean = ( )/6 = 42.0 mph S2 = [( )2+( )2+…]/(6-1) = 54.4, standard deviation S = 7.4 mph K = 2.57 for sample size with dof = 6-1 = 5 and the 95% confidence interval N = (S·K/E)2 N = (7.4x2.57/3)2 = 40.2 Additional =35 speed observations are required Using normal distribution would give = 18 additional speeds

125 Frequency distribution table for set of speed data
Data Analysis Frequency distribution table for set of speed data

126 Data Analysis

127 TRAVEL TIME

128 Definitions Travel time – time taken to travel a highway segment
Running time – travel time along a highway segment without spot obstructions (intersections) Free-flow travel time – travel time along a highway segment without impedance from other vehicles Desired travel time – travel time along a highway segment without spot obstructions nor impedance from other vehicles

129 Study Applications Identify problem locations
Input to traffic assignment models Input to economic analysis Congestion management Component of delay studies Travel time contour maps (accessibility vs. mobility)

130 Travel Time Contour Maps

131 Measurement Techniques
Probe vehicle Manual technique Automatic technique License plate method

132 Travel Time Measurements
1st Street 2nd Street 3rd Street Travel Time Travel Distance Vehicle Trajectory Running Speed Running Time

133 DELAY

134 Definitions Delay - unwanted extra travel time
Delay = Travel Time – Desired Travel Time Operational delay - delay caused by impedance from other vehicles Operational delay = Travel Time – Free-Flow Travel Time Control delay - delay caused by traffic control Control Delay = Travel Time – Running Time

135 Study Applications Identification of problem locations
Evaluation of improvements Input to planning and economic analyses Trend analysis

136 Measurement Techniques
Based on travel time measurements Based on queue measurements (control delays)

137 Delay Measurement Based on Travel Times
1st Street 2nd Street 3rd Street Control Delay Travel Time Vehicle Trajectory Running Time Travel Distance

138 Delay Measurement Based on Queues
Total counts = = 371 vehicles Volume = 530 veh/15 min Average stopped delay = 371 x 15 / 530 = 10.5 sec Additional adjustments are required to incorporate the deceleration/acceleration component

139 School of Civil Engineering
Highway Traffic and Safety Analyses Lecture 9: Highway Capacity Manual 2000 (original presentation by R. Dowling revised and expanded by A. Tarko) Purdue University School of Civil Engineering West Lafayette

140 Lecture Objectives To highlight the content of the Year 2000 edition of the Highway Capacity Manual. To help identify suitable procedures in the Manual things and properly apply to traffic operations problems. This seminar has two objectives: 1. To highlight the content and major changes of the Year 2000 edition of the Highway Capacity Manual, and 2. At the end of the seminar attendees will know: Where to find material in the HCM, How to apply the HCM to traffic operations problems, The major changes in methodology between the 1994, 1997, and 2000 HCM

141 Purpose of the HCM “To provide transportation practitioners and researchers with a consistent system of techniques for the evaluation of the quality of service on highway and street facilities.” “HCM does not set policies regarding a desirable or appropriate quality of service…” Part I states the purpose of the Highway Capacity Manual (see slide for details).

142 HCM 2000 Formats Book CD-ROM Five parts, 35 chapters
Audio-visual tutorials CD-ROM presentation The HCM 2000 will come in two formats, a printed book and a CD-ROM. The CD-ROM will contain an electronic copy of the printed book plus a hyperlinked version of the manual with audio-visual aids. No capacity analysis software will be issued with the HCM 2000, as is currently the case. Users will have to obtain capacity analysis software from other sources.

143 HCM 2000 Table of Contents Part I - Overview Part II - Concepts
Part III - Methodologies Part IV - Corridor and Areawide Analyses Part V - Simulation and Other Models The chapters of the HCM are grouped into 5 parts as shown in the slide. Part III will be the most recognizable because that is where updated versions of the majority of the current HCM chapters will reside. The other 4 parts are entirely new.

144 Part II. Concepts Describes factors affecting LOS.
Identifies required input. Suggests default values for input. Provides service volume tables Part II chapters describe the factors affecting level of service, identify the input required to compute level of service, and provide suggested default values that can be used to fill in gaps in the available data. These chapters also provide service volume tables that can be used to quickly look up the number of lanes required to provide a target level of service for a given demand volume.

145 HCM Components This slide illustrates one of the Part II tables identifying required input data and suggesting default values for the computation of signalized intersection level of service.

146 This slide illustrates one of the Part II tables identifying required input data and suggesting default values for the computation of signalized intersection level of service.

147 HCM Components and Structure
Chapter 9 is Your Gateway to the HCM Exhibit 9-1 lists facility types and components. The same exhibit gives Part II and Part III chapter references for each facility type. Chapter 9 Provides Guidance on: Use of defaults. Use of or development of service volume tables. Precision and accuracy of results. People wishing to apply the HCM 2000 to a particular problem should start with Chapter 9 in Part I. This chapter provides a road map to the other chapters of the manual. Exhibit 9-1 (shown on following slide) shows the facility types covered in the manual and provides the chapters related to each facility type. Chapter 9 also provides guidance on the use of defaults, the development of custom service volume tables, and the precision and accuracy of results.

148 Chapter 9 Structure of HCM
This is the left hand side of Exhibit This slide shows the chapters related to the analysis of Urban Streets and Freeways. Chapter 9 Structure of HCM

149 Chapter 9 Structure of HCM
This right hand side of Exhibit 9-1 shows the chapters related to the analysis of highways, transit, pedestrian, and bicycle facilities. Chapter 9 Structure of HCM

150 Part III. Methodologies
Provides Methodologies to Compute: Level of Service, Delay, Queues Contents Freeway Facilities (4 chapters) Urban Streets (3 chapters) Highways (2 chapters) Pedestrian & Bikeways (1 chapter) Transit (1 chapter) Part III chapters provide the analytical methodologies to be used to compute level of service, delay, and queues. There are 11 chapters in this part, 4 for freeways,3 for urban streets, 2 for rural highways, 1 each for pedestrians and bikeways, and 1 for transit.

151 Intersection Control This slide illustrates a diagram provided in Chapter 10 to aid planners in estimating the likely intersection control that would be in place at a future intersection. This figure was prepared prior to the recent FHWA report on roundabouts, and consequently does not reflect the recommendations contained in that report.

152 Required Data for Signals
This slide illustrates one of the Part II tables identifying required input data and suggesting default values for the computation of signalized intersection level of service.

153 Level of Service Criteria
This slide illustrates an example service volume table for urban streets. The user enters the table with the demand volume and class of the facility to determine the required number of through lanes. Note that level of service “A” and “B” are impossible to achieve under the default assumptions of signal timing and signal spacing that were used to construct this table. The user would need to construct their own service volume tables for other assumptions of signal timing and spacing.

154 Level of Service Criteria
This slide illustrates an example service volume table for urban streets. The user enters the table with the demand volume and class of the facility to determine the required number of through lanes. Note that level of service “A” and “B” are impossible to achieve under the default assumptions of signal timing and signal spacing that were used to construct this table. The user would need to construct their own service volume tables for other assumptions of signal timing and spacing.

155 Transit LOS Criteria

156 Part IV. Corridor/Areawide
Purpose: How to adapt HCM to planning models Multi-Modal Corridor Analysis Computation of intensity, duration, extent of congestion (for performance measures) Areawide Analysis Capacity analysis for planning models Speed-flow and node delay equations for models A new Part IV has been added to the Highway Capacity Manual that provides guidance on how to extend and adapt the Part III procedures to the analysis of corridors and large areas. The corridor analysis chapter gives guidance on multimodal analyses of corridors. Procedures are provided for computing the maximum intensity, duration, and physical extent of congestion. The area-wide analysis chapter provides guidance to planners wishing to adapt the HCM capacity equations for use in planning models. Special HCM based speed-flow and intersection (node) delay equations are provided for use in planning models

157 Part V. Simulation Purpose Contents
Guidance on the use of simulation for conditions beyond the bounds of Part III. Contents Chapter 31. Simulation and Other Models Introduction to simulation techniques Part V contains entirely new material on the use of simulation for conditions that fall outside the range of applicability of the traditional capacity analysis procedures described in Part III of the HCM An introduction to simulation techniques is provided.

158 Using the HCM 2000 Determine Facility Type
See Exhibit 9-1, Chapter 5 Definitions Exhibit 29-2 provides summary. Review Concepts, Inputs, Defaults Review relevant Part II chapter. Conduct Analysis Apply relevant Part III chapter. Interpretation of Results See Chapter 9 discussion on precision. See end of Part III Chapter for sensitivity discussion This slide review the four basic steps involved in applying the HCM 2000 to a capacity and level of service analysis problem. Step 1. Use Exhibit 9-1 and the definitions provided in Chapter 5 to determine the facility type. Exhibit 29-2 summarizes much of this information. Step 2. Review the relevant concepts, inputs, and defaults in the appropriate Part II chapter. Step 3. Conduct the analysis using the procedures described in Part III. Step 4. See the end of each Part III chapter and Chapter 9 for guidance on the interpretation of the results. This concludes Session 1, Overview.

159 CD ROM Tutorials 4. Delay 3:35 9. Control Delay at Signalized
Intersections 5:50 20. Bicycle Events and Hindrance 3:05 21. Bicycle LOS by Facility Types 4:10 32. Transit Quality of Service 5:05

160 Highway Capacity Software
No official TRB approved software FHWA sponsored software (2) Windows (Catalina), EZ-HCS written in JAVA Other developers McTrans, Strong Concepts, Dowling, KLD, etc. There never has been, and there is no official Transportation Research Board software for analyzing capacity. The Federal Highway Administration co-sponsoring the private development of two new software products by Catalina Engineering and Iteris for the analysis of capacity. These will be private sector commercial products upon their completion. Other private developers are also developing or updating their software for the HCM 2000. The CD-ROM is supposed to have links that allow users to identity the analysis software that they wish to call from the electronic version of the manual.

161 School of Civil Engineering
Highway Traffic and Safety Analyses Lecture 10: Traffic Control Basics Purdue University School of Civil Engineering West Lafayette

162 Lecture Outline What control, why, where,
and when use to improve traffic Signs Signals Reading Assignment Example outreach Crosswalks, speed limits, stop signs This seminar has two objectives: 1. To highlight the content and major changes of the Year 2000 edition of the Highway Capacity Manual, and 2. At the end of the seminar attendees will know: Where to find material in the HCM, How to apply the HCM to traffic operations problems, The major changes in methodology between the 1994, 1997, and 2000 HCM

163 How Make Control Effective
A traffic control device should: Fulfill a need, Command attention, Convey a clear, simple meaning, Command respect from road users, and Give adequate time for a proper response.

164 SIGNS

165 Location of Signs

166 Location of Signs

167 Location of Signs

168 Use of Warning Signs

169 Where Use Two-Way Stop Signs
A. Intersection of a less important road with a main road where application of the normal right-of-way rule would not be expected to provide reasonably safe operation. B. Street entering a through highway or street. C. Unsignalized intersection on a signalized arterial. D. High speeds, restricted view, or crash records indicate a need for control by the STOP sign.

170 Which Road Should Have Stop Signs?
The street carrying the lowest volume of traffic If volumes are similar, then The direction that conflicts the most with established pedestrian crossing activity The direction that has obscured vision, dips, or bumps on the approaches The direction that has the longest distance of uninterrupted flow approaching the intersection The direction that has the best sight distance to conflicting traffic measured from the stopped vehicle

171 Where Use All-Way Stop Signs
A. As an interim measure before installation of the traffic control signal. B. Five or more right- and left-turn collisions as well as right-angle collisions reported in a 12-month period.

172 Where Use All-Way Stop Signs
C. Minimum volumes: 1. The vehicular volume entering the intersection from the major street approaches (total of both approaches) averages at least 300 vehicles per hour for any 8 hours of an average day, and 2. The combined vehicular, pedestrian, and bicycle volume entering the intersection from the minor street approaches (total of both approaches) averages at least 200 units per hour for the same 8 hours, with an average delay to minor-street vehicular traffic of at least 30 seconds per vehicle during the highest hour, but 3. If the 85th-percentile approach speed of the major-street traffic exceeds 65 km/h (40 mph), the minimum vehicular volume warrants are 70 percent of the above values.

173 Where Use All-Way Stop Signs
Supplementary considerations A. The need to control left-turn conflicts. B. The need to control vehicle/pedestrian conflicts near locations that generate high pedestrian volumes. C. Locations where a road user, after stopping, cannot see conflicting traffic and is not able to safely negotiate the intersection unless conflicting cross traffic is also required to stop (insufficient sight distances from stopped vehicles). D. An intersection of two residential neighborhood collector (through) streets of similar design and operating characteristics where multi-way stop control would improve traffic operational characteristics of the intersection.

174 Where Use Yield Signs A. When the ability to see all potentially conflicting traffic is sufficient to allow a road user traveling at the posted speed, the 85th-percentile speed, or the statutory speed to pass through the intersection or to stop in a safe manner. B. If controlling a merge-type movement on the entering roadway where acceleration geometry and/or sight distance is not adequate for merging traffic operation. C. At the second crossroad of a divided highway, where the median width is 9 m (30 ft) or greater. A STOP sign may be installed at the entrance to the first roadway of a divided highway and a YIELD sign may be installed at the entrance to the second roadway. D. At an intersection where a special problem exists and where engineering judgment indicates the problem to be susceptible to correction by the use of the YIELD sign.

175 Where Use Speed Limit After an engineering study has been made in accordance with established traffic engineering practices, the Speed Limit sign shall display the limit established by law, ordinance, regulation, or as adopted by the authorized agency. The speed limits shown shall be in multiples of 10 km/h (5 mph).

176 Other Considerations for Speed Limits
A. Road characteristics, shoulder condition, grade, alignment, and sight distance. B. The running speed. C. Roadside development and environment. D. Parking practices and pedestrian activity. E. Reported crash experience for at least a 12-month period.

177 Where Use Overhead Signs?
A. Traffic volume at or near capacity B. Complex interchange design C. Three or more lanes in each direction D. Restricted sight distance E. Closely-spaced interchanges F. Multi-lane exits G. Large percentage of trucks H. Street lighting background I. High-speed traffic J. Consistency of sign message location through a series of interchanges K. Insufficient space for ground-mounted signs L. Junction of two freeways M. Left exit ramps

178 SIGNALS

179 Advantages of Traffic Signals
A. They provide for the orderly movement of traffic. B. They can increase the capacity of the intersection. C. They reduce the frequency and severity of certain types of crashes, especially right-angle collisions. D. They are coordinated to provide for continuous or nearly continuous movement of traffic. E. They are used to interrupt heavy traffic at intervals to permit other traffic, vehicular or pedestrian, to cross.

180 Disadvantages of Unjustified or Poorly Designed Traffic Signals
A. Excessive delay. B. Excessive disobedience of the signal indications. C. Increased use of less adequate routes as road users attempt to avoid the traffic control signals. D. Significant increases in the frequency of collisions (especially rear-end collisions).

181 Alternatives to Traffic Signals
A. Installing signs along the major street to warn road users approaching the intersection. B. Relocating the stop line(s) and making other changes to improve the sight distance at the intersection. C. Installing measures designed to reduce speeds on the approaches. D. Installing a flashing beacon at the intersection to supplement STOP sign control. E. Installing flashing beacons on warning signs in advance of a STOP sign controlled intersection on major- and/or minor-street approaches. F. Adding one or more lanes on a minor-street approach to reduce the number of vehicles per lane on the approach.

182 Alternatives to Traffic Signals
G. Revising the intersection geometry to channelize vehicular movements and reduce the time required for a vehicle to complete a movement, which could also assist pedestrians. H. Installing roadway lighting if a disproportionate number of crashes occur at night. I. Restricting one or more turning movements, perhaps on a time-of-day basis, if alternate routes are available. J. If the warrant is satisfied, installing multi-way STOP sign control. K. Installing a roundabout.

183 Justifying Traffic Signals
An engineering study of traffic conditions, pedestrian characteristics, and physical characteristics of the location shall be performed to determine whether installation of a traffic control signal is justified at a particular location.

184 Justifying Traffic Signals MUTCD 4C-3 thru 4C-14
Warrant 1, Eight-Hour Vehicular Volume. Warrant 2, Four-Hour Vehicular Volume. Warrant 3, Peak Hour. Warrant 4, Pedestrian Volume. Warrant 5, School Crossing. Warrant 6, Coordinated Signal System. Warrant 7, Crash Experience. Warrant 8, Roadway Network.

185 Traffic Study Prior Signals Installation
A. The number of vehicles entering the intersection in each hour from each approach during 12 hours of an average day. It is desirable that the hours selected contain the greatest percentage of the 24-hour traffic volume. B. Vehicular volumes for each traffic movement from each approach, classified by vehicle type (heavy trucks, passenger cars and light trucks, public-transit vehicles, and, in some locations, bicycles), during each 15-minute period of the 2 hours in the morning and 2 hours in the afternoon during which total traffic entering the intersection is greatest. C. Pedestrian volume counts on each crosswalk during the same periods as the vehicular counts in Paragraph B above and during hours of highest pedestrian volume. Where young, elderly, and/or persons with physical or visual disabilities need special consideration, the pedestrians and their crossing times may be classified by general observation.

186 Traffic Study Prior Signals Installation
D. Information about nearby facilities and activity centers that serve the young, elderly, and/or persons with disabilities, including requests from persons with disabilities for accessible crossing improvements at the location under study. These persons may not be adequately reflected in the pedestrian volume count if the absence of a signal restrains their mobility. E. The posted or statutory speed limit or the 85th-percentile speed on the uncontrolled approaches to the location. F. A condition diagram showing details of the physical layout, including such features as intersection geometry, channelization, grades, sight-distance restrictions, transit stops and routes, parking conditions, pavement markings, roadway lighting, driveways, nearby railroad crossings, distance to nearest traffic control signals, utility poles and fixtures, and adjacent land use. G. A collision diagram showing crash experience by type, location, direction of movement, severity, weather, time of day, date, and day of week for at least 1 year.

187 Additional Data Recommended
A. Vehicle-hours of stopped time delay determined separately for each approach during the peak hour. B. The number and distribution of acceptable gaps in vehicular traffic on the major street for entrance from the minor street. C. Pedestrian delay time for at least two 30-minute peak pedestrian delay periods of an average weekday or like periods of a Saturday or Sunday. D. Queue length on stop-controlled approaches.

188 Preemptive Signals Examples:
A. The prompt displaying of green signal indications at signalized locations ahead of fire vehicles, police cars, ambulances, and other official emergency vehicles. B. A special sequence of signal phases and timing to provide additional clearance time for vehicles to clear the tracks prior to the arrival of a train. C. A special sequence of signal phases to display a red indication to prohibit turning movements towards the tracks during the approach or passage of a train or transit vehicle.

189 Priority Signals Examples:
A. The displaying of early or extended green signal indications at an intersection to assist public transit vehicles in remaining on schedule. B. Special phasing to assist public transit vehicles in entering the travel stream ahead of the platoon of traffic.

190 Signals Coordination Traffic control signals within 800 m (0.5 mi) of one another along a major route or in a network of intersecting major routes should be coordinated, preferably with interconnected controller units. Signal coordination need not be maintained across boundaries between signal systems that operate on different cycle lengths.

191 Highway Traffic and Safety Analyses
Lecture 11: Traffic Signals Design and Timing Purdue University School of Civil Engineering West Lafayette

192 Management of Traffic Signals
Major Decisions Need for new signals Signals design and setting Field evaluation Signals improvement Removal of signals

193 Traffic Signals Studies
Decision Study New signal? Traffic signal warrants study Design and setting Traffic signals design and optimization Field evaluation Delay and queuing studies Signals improvement Individual intersections and corridor studies Remove signals? Alternative control studies

194 Signals Design and Settings
Signals Needed Non-coordinated Coordinated Full-actuated Semi-actuated Pre-timed Signal phases Signal phases Signal phases Coordinated phase Coordinated phase Change periods Change periods Change periods Control settings Signals timing Detectors type and location

195 Signals Coordinated or Isolated? Actuated or Pre-timed?
Coordination when 0.5 mile or less between signals Isolated signals when 1 mile or more to the closest signals Cost-effectiveness of coordination should be studied Pre-timed and semi-actuated signals in coordination Full-actuated at isolated intersections

196 Signal Phases - Left Turns Treatment
Two-lane left turn considered when 300 vehicles per hour or more. Dual Left – most efficient traffic actuated-operation. Various phases and combinations of phases appear only on demand.   Lead-Lag (With Overlap)- pre-timed or traffic-actuated. In coordination when the traffic in the opposing directions arrives at different times during a cycle. Opposite/Opposing (Split Phase) – used when the left turns are equal or stronger than the through traffic.   Three Phase Operation - the simplest and the least expensive, pre-timed or traffic-actuated. Inefficient when strong traffic disproportion between the opposing approaches.

197 Signal Phases

198 Signal Phases

199 Signal Phases

200 Change Periods Y

201 Change Periods - Yellow

202 Change Periods – All Red

203 Pre-timed Signals Timing
Cycle Green split Offsets (coordination)

204 Settings for Actuated Signals
Minimum green times Maximum green times Gap interval Unit (vehicle) extension Force offs Offsets Cycle length Time-of-day settings

205 Signal Detectors Vehicle Detectors
1. Inductive loop detectors detect standing vehicles as well as moving ones. The detection area is roughly that enclosed by the loop. 2. Video detectors have similar capabilities as the inductive loop detectors. They require video cameras installed at the intersection. The longitudinal location (setback) of detectors relative to the stop line depends on the speed of traffic and the type of detector operation desired.   Bicycle Detectors Bicycle detectors may be required at traffic-actuated signal installations. Type D loop configuration is effective for detecting bicycles and small motorcycles and shall be installed at the bicycle loop detector locations.

206 Signal Detectors see Northwestern-Stadium

207 Signal Detectors

208 Typical Installation

209 Minimum Green for Pedestrians

210 Highway Traffic and Safety Analyses
Lecture 12: Traffic Signals Design (2) Purdue University School of Civil Engineering West Lafayette

211 Design Process Phases (Ring Structure) Timing Detectors Coordination
Minimum Green Times Video and Inductive Loop Detectors Signal Cycle Change Periods Phase Splits (Force-off Points) Pulse and Presence Detectors Pedestrian Signals Offsets Maximum Green Times Stop-bar and Advance Detectors Time-of-day (TOD) Plans Vehicle Extension Times Vehicle and Bike Detectors Density Functions

212 Ring Structure Navigation

213 Ring Structure Navigation

214 Minimum Green Times Absolute minimums = 5 s for left turns
10 s main street through movements 7 s side street through movements Adjustments for unusual traffic volumes are recommended Navigation

215 Change Periods tr= 1.0 s a = 10 ft/s2 W = intersection width (ft)
L = vehicle length (ft) V = speed (m/h) Navigation

216 Pedestrian Signals Minimum walk time = 7 s
Pedestrians change period = W/Vp Vp = 4 ft/s in typical situation Walk time + Pedestrian change period must not be longer than the Vehicle maximum green + Vehicle change period Navigation

217 Maximum Green Times Free Operation
Maximum green time = 1.5 x Green time obtained for X = 0.95 Guidance when optimal splits are not known: Main street maximum green = 75 seconds Side street maximum green = 60 seconds Left-turn maximum green = 50 seconds Maximum green must not be excessively long to avoid discomfort among drivers Navigation

218 Maximum Green Times Coordination
Maximum green time = 1.3 x Green time obtained from optimization software (Synchro, Transyt, or Passer) Guidance when optimal splits are not known (coordination): Main street maximum green = 50 seconds Side street maximum green = 40 seconds Left-turn maximum green = 35 seconds Maximum green + Change period must not be longer than the time between the corresponding force-off points Navigation

219 Vehicle Extension Times Stop-bar Detectors
Vehicle extension (s) = 3 – (L+D)/(1.47·V) L = vehicle length (ft) D = detection zone length (ft) V = speed (m/h) Navigation

220 Vehicle Extension Times Advance Detectors
Vehicle extension (s) = DS/(1.47·V) DS = detection setback (ft) V = speed (m/h) Navigation

221 Density Functions Minimum Green Extension for Advance Detectors
Maximum initial green = from table below Second/actuation = Maximum initial green/No. of actuations Navigation

222 Density Functions Variable Gap
Minimum gap = 3 seconds Maximum gap = Min (Vehicle extension, 5 seconds) Time before reduction = 33 % of maximum green Time to reduction = 80 % of maximum green Gap Vehicle extension or 5 s 3 s Time before reduction Green elapsed Time to reduction Navigation

223 Video and Inductive Loop Detectors
1. Inductive loop detectors detect standing vehicles as well as moving ones. The detection area is roughly that enclosed by the loop. 2. Video detectors have similar capabilities as the inductive loop detectors. They require video cameras installed at the intersection. The longitudinal location (setback) of detectors relative to the stop line depends on the speed of traffic and the type of detector operation desired.   Navigation

224 Pulse and Presence Detectors
Navigation

225 Stop-bar and Advance Detectors
Navigation

226 Vehicle and Bike Detectors
Navigation

227 Signal Cycle Cycle Cycle Cycle Cycle
Obtained from optimization software or calculated for the busiest intersection (X = 0.95) Navigation

228 Phase Splits (Force-off Points)
Navigation Phase Splits (Force-off Points) Force-off points (F.O.) are obtained from optimization software or from calculations of the average green times for semi-actuated controllers.

229 Offsets Navigation System zero
Offsets are obtained from optimization software or from a time-space diagram.

230 Time-of-day Plans Coordination plans (cycle, splits, and offsets) for different time periods Table of plan-to-plan switch times Free mode possible if justified (night?) Navigation

231 Highway Traffic and Safety Analyses
Lecture 13: Traffic Signals Design (3) Purdue University School of Civil Engineering West Lafayette

232 Design Process Phases (Ring Structure) Timing Detectors Coordination
Minimum Green Times Video and Inductive Loop Detectors Signal Cycle Change Periods Phase Splits (Force-off Points) Pulse and Presence Detectors Pedestrian Signals Offsets Maximum Green Times Stop-bar and Advance Detectors Time-of-day (TOD) Plans Vehicle Extension Times Vehicle and Bike Detectors Density Functions

233 Ring Structure Navigation

234 Ring Structure Navigation

235 Minimum Green Times Absolute minimums = 5 s for left turns
10 s main street through movements 7 s side street through movements Adjustments for unusual traffic volumes are recommended Navigation

236 Change Periods tr= 1.0 s a = 10 ft/s2 W = intersection width (ft)
L = vehicle length (ft) V = speed (m/h) Navigation

237 Pedestrian Signals Minimum walk time = 7 s
Pedestrians change period = W/Vp Vp = 4 ft/s in typical situation Walk time + Pedestrian change period must not be longer than the Vehicle maximum green + Vehicle change period Navigation

238 Maximum Green Times Free Operation
Maximum green time = 1.5 x Green time obtained for X = 0.95 Guidance when optimal splits are not known: Main street maximum green = 75 seconds Side street maximum green = 60 seconds Left-turn maximum green = 50 seconds Maximum green must not be excessively long to avoid discomfort among drivers Navigation

239 Maximum Green Times Coordination
Maximum green time = 1.3 x Green time obtained from optimization software (Synchro, Transyt, or Passer) Guidance when optimal splits are not known (coordination): Main street maximum green = 50 seconds Side street maximum green = 40 seconds Left-turn maximum green = 35 seconds Maximum green + Change period must not be longer than the time between the corresponding force-off points Navigation

240 Vehicle Extension Times Stop-bar Detectors
Vehicle extension (s) = 3 – (L+D)/(1.47·V) L = vehicle length (ft) D = detection zone length (ft) V = speed (m/h) Navigation

241 Vehicle Extension Times Advance Detectors
Vehicle extension (s) = DS/(1.47·V) DS = detection setback (ft) V = speed (m/h) Navigation

242 Density Functions Minimum Green Extension for Advance Detectors
Maximum initial green = from table below Second/actuation = Maximum initial green/No. of actuations Navigation

243 Density Functions Variable Gap
Minimum gap = 3 seconds Maximum gap = Min (Vehicle extension, 5 seconds) Time before reduction = 33 % of maximum green Time to reduction = 80 % of maximum green Gap Vehicle extension or 5 s 3 s Time before reduction Green elapsed Time to reduction Navigation

244 Video and Inductive Loop Detectors
1. Inductive loop detectors detect standing vehicles as well as moving ones. The detection area is roughly that enclosed by the loop. 2. Video detectors have similar capabilities as the inductive loop detectors. They require video cameras installed at the intersection. The longitudinal location (setback) of detectors relative to the stop line depends on the speed of traffic and the type of detector operation desired.   Navigation

245 Pulse and Presence Detectors
Navigation

246 Stop-bar and Advance Detectors
Navigation

247 Vehicle and Bike Detectors
Navigation

248 Signal Cycle Cycle Cycle Cycle Cycle
Obtained from optimization software or calculated for the busiest intersection (X = 0.95) Navigation

249 Phase Splits (Force-off Points)
Navigation 2 3 4 8 7 6 5 1 Force-off points (F.O.) are obtained from optimization software or from calculations of the average green times for semi-actuated controllers.

250 Offsets Navigation System zero
Offsets are obtained from optimization software or from a time-space diagram.

251 Time-of-day Plans Coordination plans (cycle, splits, and offsets) for different time periods Table of plan-to-plan switch times Free mode possible if justified (night?) Navigation

252 Lecture 14: HCS and SYNCHRO (1)
Highway Traffic and Safety Analyses Lecture 14: HCS and SYNCHRO (1) Purdue University School of Civil Engineering West Lafayette

253 HCS Example

254 SYNCHRO Capabilities Optimizes isolated signals and coordinated signalized networks of streets Pre-timed, semi-actuated, and full-actuated controllers Export of the input data to SIMTRAFFIC, CORSIM, TRANSYT, and HCS Convenient user interface

255 SYNCHRO Open the two ring.sy6 file SYNCHRO
Add two more links with one intersection Delete the added node Show the link parameters Show the link window Show the volume window Show the control window Import a background image with scaling

256 SYNCHRO Editing Streets and Nodes
Drawing links Curved links, bend nodes Link parameters Signalized nodes Setting geometry parameters Adding traffic data Setting control at AWSC Running simulation in SimTraffic

257 Control Input and Results
Highway Traffic and Safety Analyses Lecture 15: SYNCHRO - Control Input and Results Purdue University School of Civil Engineering West Lafayette

258 Control Types in SYNCHRO
STOP and YIELD in SYNCHRO v.5 Single-lane roundabouts Isolated and coordinated signals Pre-timed, semi-actuated, and full-actuated controllers

259 Dual Ring Control Open dual ring2.sy6, go to timing window
Dual ring controller

260 Timing Window - Control Input
Lanes and movement assignment Phase assignment to movements Detector assignment to phases Timing parameters for a movement Sequence of phases Recall mode

261 Timing Window - Coordination
Reference phase Master intersection Lock timings Offset (input or output)

262 Timing Window – Results for Movements
Effective Green g/C ratio v/c ratio Delay Delay type to calculate (network options) LOS Queue Queuing penalty Stops Fuel used Dilemma vehicles

263 Percentile Delay and Queue
Percentile delay/queue 10th, 30th, 50th, 70th, 90th percentiles (Poisson) deterministic queuing diagram time # veh arrivals departures Queue Delay

264 Queuing Penalty Rough estimate of the number of vehicles blocked by the downstream queue time # veh arrivals departures Max queue that can fit between intersections Blocking time

265 Phasing Window Additional items Vehicle extension Minimum gap
Time before reduce Time to reduce Pedestrian data Green time percentile

266 Green Time Percentiles
sk Phase is skipped mn Phase shows for minimum time gp Phase gaps-out hd Phase held for other ring to cross barrier mx Phase maxes out mr Phase has max-recall cd Coordinated phase

267 Optimization in SYNCHRO
Network optimization – manual option Offset optimization for selected cycle Graphical visualization of the coordination (space-time diagram) Graphical visualization of coordination, delays, and v/c Report

268 SimTraffic Exporting the data to SimTraffic
Changing the simulation options and running the simulation Visualization of the MOEs for movements Reports

269 Highway Traffic and Safety Analyses
Lecture 16: Road Safety Concepts Purdue University School of Civil Engineering West Lafayette

270 Road Safety and Its Measurement
What is road safety? Road safety crosses multiple areas Stakeholders of highway safety Present issues Safety Management System Objective, perceived, and nominal safety Measures of safety

271 Road Safety When is a road considered safe?
Basic facts about road safety

272 Hadden’s Matrix Road safety crosses multiple areas
Travelers Vehicle Road + Environment Pre-Crash Crash Post-Crash Attitudes Driver Skills Alcohol/Drug Use Vision Education Safety Belts Use Air Bags Side Impact Protection Traveler’s Age Traveler’s Health First Aid Training Safety Equipment Vehicle Design Vehicle Size Vehicle Weight Automatic Seatbelts Fuel System Integrity Road Design Weather Conditions Road Operation Road Maintenance Lighting Delineation Roadside Hazards Fixed Objects EMS Response Hospitals Availability of Med. Services Matrix developed by William Hadden, Insurance Institute for Highway Safety

273 Stakeholders of Road Safety
Legislature (funding, safety law and regulations) Government (overseeing) Road administration (road safety management) Bureau of motor vehicles (safety through proper licensing) Police (crash data, enforcement) Public research agencies (knowledge enhancement) Auto industry (observance of safety regulations, competition) Highway industry (safe road construction) Freight industry (safe trucks operation) Railroad industry (safe railway construction and operation) Insurance industry (reduce crash costs) Emergency medical services (reduce crash consequences) Private consultants (research, analysis, service) Citizens coalitions (lobbying for safety improvements)

274 Organizations Involved in Road Safety
United States Department of Transportation American Association of State Highway and Transportation Officials (AASHTO) National Association of Governors Highway Safety Representatives (NAGSHR) National Transportation Safety Board (NTSB) Mothers Against Drunk Driving (MADD) Insurance Institute for Highway Safety (IIHS) American Automobile Association (AAA) Traffic Safety Foundation American Association of Motor Vehicle Administrators (AAMVA) American Association of Retired Persons (AARP) National Safety Council (NSC) Bicycle Federation of America American Trucking Association (ATA) Transportation Research Board (TRB) American Road and Transportation Builders Association (ARTBA) Roadway Safety Federation (RSF) American Traffic Safety Services Association (ATSSA)

275 Safety Emphases Special Users - pedestrians and bicyclists
Drivers - curbing aggressive driving, reducing impaired driving, keeping drivers alert, increasing driver safety awareness, seat belt usage, aging drivers Special Users - pedestrians and bicyclists Vehicles - motorcycle and commercial truck safety, vehicle safety enhancements (antilock brake systems) Highways - vehicle-train crashes, highway intersection design and operation, head-on and across-median crashes, and work zones Emergency Medical Services - increase survivability of crash victims Management - gathering and analyzing crash data

276 Safety Emphases Highways Management Reducing Vehicle-Train Crashes
Keeping Vehicles on the Roadway Minimizing the Consequences of Leaving the Road Improving the Design and Operation of Highway Intersections Reducing Head-on and Across-median Crashes Designing Safer Work Zones Management Improving Information and Decision Support Systems Creating More Effective Processes and Safety Management Systems

277 Safety Management System
1991 ISTEA required SMS from state DOTs 1997 TEA-21 - Transportation Equity Act for the 21st Century doesn’t require SMS SMS developed by some states anyway Florida North Carolina

278 Safety Management System Cycle
Safety-related Decision Making Safety Projects Implementation Safety Data Acquisition and Management

279 Safety Management System Decision-making Process
Identify highway hazard Determine causes Determine countermeasures Develop safety projects Select projects for implementation Evaluate projects effectiveness

280 Objective, perceived, and nominal safety
Objective safety – measured with crashes Perceived safety – felt by motorists Nominal safety – measured with compliance to design and operational safety standards

281 Measures of Safety Expected crash frequencies (crash/year)
Expected crash rates (crash/unit exposure) Example unit exposures (used by Fatality Analysis Reporting System) 100,000,000 vehicle-miles traveled (VMT) 100,000 registered vehicles 100,000 licensed drivers

282 Measures of Safety http://www.nhtsa.dot.gov/people/ncsa

283 Measures of Safety http://www.nhtsa.dot.gov/people/ncsa

284 Highway Traffic and Safety Analyses
Lecture 17: Measurement of Road Safety Purdue University School of Civil Engineering West Lafayette

285 Measurement of Road Safety
Traffic records system Crashes underreporting Crash counts vs. crash rates Statistical properties of crash counts Confidence interval of crash frequency estimate Pyramid of traffic events

286 Traffic Records System http://www.dottrcc.gov/
Crash File with data on the time, environment, and circumstances of a crash; identification of the vehicles, drivers, cyclists, occupants, and pedestrians involved; and documentation of crash consequences (fatalities, injuries, property damage and violations charged) with the data tied to a location reference system. Report form (show). Commercial Motor Vehicle Crash File which uses uniform data definitions and collects information on the vehicle configuration, cargo body type, hazardous materials, information to identify the motor carrier, as well as information on the crash (States are encouraged to use available information systems to cross-reference commercial vehicle citations for violations of Federal and State commercial vehicle safety regulations). Roadway File with information about roadway location, identification, and classification as well as a description of a road's total physical characteristics, which are tied to a location reference system. This file should also contain data for normalizing purposes, such as miles of roadway and annual average daily traffic (AADT).

287 Traffic Records System
Emergency Medical Services (EMS) file with emergency care and victim outcome information about ambulance responses to crashes, e.g., emergency care unit, care given, injury data, and times of EMS notification and arrival; information on emergency facility and hospital care, including Trauma Registry data; and medical outcome data relative to crash victims receiving rehabilitation and for those who died as the result of the crash. Citation/Conviction File which identifies the type of citation and the time, date, and location of the violation; the violator, vehicle and the enforcement agency; and adjudication action and results, including court of jurisdiction (an Enforcement/Citation File could be maintained separate from a Judicial/Conviction File) and fines assessed and collected.

288 Traffic Records System
Driver File or driver history record of licensed drivers in the State, with data on personal identification and driver license number, type of license, license status (suspended or revoked), driver restrictions, driver convictions for traffic violations, crash history, driver control or improvement actions, and safety education data. Vehicle File with information on identification, ownership and taxation, and vehicle inspection (where applicable).

289 Traffic Records System
! Provisions for file linkage through common data elements between the files or through other consistent means; performance level data as part of the traffic records system; demographic data to normalize or adjust for exposure when analyzing the various data in the files; and provisions for the use of cost data relative to amounts spent on countermeasure programs and the costs of fatalities, injuries and property damage.

290 Alternative data source
Underreporting of Crashes Hauer and Hakkert, Extent and some Implications of Incomplete Accidents Reporting, Transportation Research Record 1185 Year of Publication Country or state Alternative data source Sample Size % Reported 1966 California Employee records for DOH vehicles 438 cases Fatal 100%, Injury 93%, PDO 38%, All 49% 1969 Mississippi Phone interviews 500 All crashes 42% 1971 USA Self reports All crashes 35% 1981 7624 Injury crashes 79% PDO 54% 1984 Several countries Death certificates large Netherlands 106% New Zealand 97% Norway 80% West Germany 104% USA 96% 1985 Ohio Hospitals vs. BMV 882 cases Injuries 55% Young (<16 yrs) 28% West Germany Hospitals, insurance 2744 cases Fatalities 95% Serious injury 78% Slight injury 62% Major PDO 42%

291 Crash-based Measures of Safety
Annual crash counts: c1, c2…cn Estimate of crash frequency (expected annual count): Expected crash rate: a / Exposure Exposure: annual volume, annual VMT, etc.

292 Crash Counts vs. Crash Rates
BEFORE Crash Rate AFTER Crashes Crashes BEFORE VMT before Crashes AFTER VMT after VMT

293 Statistical Properties of Crash Counts
Poisson variability of annual counts

294 Gamma distribution 0.05 90 % confidence interval 0.05 al au

295 Confidence Interval of Frequency Estimate Gamma-based Estimation

296 Confidence Interval of Frequency Estimate Gamma-based Estimation
c = 10 crashes, n = 3 years, 90% confidence level Expected crash frequency a = c/n=10/3 = 3.33 crashes/year Lower limit of the expected crash frequency al = GAMMAINV(0.05, 10, 1/3) = al = GAMMAINV (0.05, 10, 0.33) = 1.81 crashes/year Upper limit of the expected crash frequency au = GAMMAINV (0.95, 10, 1/3) = au = GAMMAINV (0.95, 10, 0.33) = 5.24 crashes/year

297 Confidence Interval of Frequency Estimate Nicholson, The Estimation of Accident Rates and Countermeasure Effectiveness, Traffic Engineering and Control, October 1987, pp a=3.3n = 1

298 Confidence Interval of Frequency Estimate Nicholson, The Estimation of Accident Rates and Countermeasure Effectiveness, Traffic Engineering and Control, October 1987, pp a=3.3n = 3

299 Confidence Interval of Frequency Estimate Nicholson, The Estimation of Accident Rates and Countermeasure Effectiveness, Traffic Engineering and Control, October 1987, pp a=3.3n = 5

300 Confidence Interval of Frequency Estimate Nicholson, The Estimation of Accident Rates and Countermeasure Effectiveness, Traffic Engineering and Control, October 1987, pp a=3.3n = 10

301 Normal Poisson Mean = 1.8 Mean = 27.0

302 Confidence Interval of Frequency Estimate Normal Approximation

303 Confidence Interval of Frequency Estimate Normal Approximation
Normal distribution c = total crash count during n years al = lower bound of the confidence interval for the mean au= upper bound of the confidence interval for the mean 100k % = confidence level

304 Confidence Interval of Frequency Estimate Normal Approximation Example
c = 10 crashes, n = 3 years, 90% confidence level, k = 0.90 Expected crash frequency a = c/n=10/3 = 3.33 crashes/year Lower limit of the expected crash frequency al = NORMINV(0.05, 10/3, 101/2/3) = al = MORMINV(0.05, 3.33, 1.05) = 1.60 crashes/year Upper limit of the expected crash frequency au = NORMINV(0.95, 10/3, 101/2/3) = au = MORMINV(0.95, 3.33, 1.05) = 5.07 crashes/year

305 Confidence Interval of Frequency Estimate Comparison
c = 10 crashes, n = 3 years, 90% confidence level Case Lower Limit Upper Limit Gamma 1.81 5.24 Normal 1.60 5.07

306 Confidence Interval of Crash Rate
Estimate the confidence interval of crash frequency Convert the interval limits to crash rates Assumption: negligible error of exposure estimates

307 Pyramid of Traffic Events
A traffic conflict takes place when one or more drivers have to performed an evasive maneuver (rapid swerving or braking) to avoid collision with another vehicle. PDO Relevance to Safety Severity

308 Indiana Police Crash Report Form
Full form Back

309 Highway Traffic and Safety Analyses
Lecture 18: Safety Performance Functions Purdue University School of Civil Engineering West Lafayette

310 Outline Crash counts variability across sites
Safety performance functions -- regression models Example safety performance functions Use of safety performance functions

311 Variability of Counts across Locations
What site-to-site distribution of crash counts would you expect for IDENTICAL locations? What can you say about site-to-site variability of counts at VARIOUS locations?

312 Variability of Counts across Locations
Poisson variability of counts at individual sites (from year to year) Gamma variability of expected crash counts across locations (assumption) Gamma distribution of means Poisson distribution of counts around means = Negative Binomial distribution of counts Negative Binomial variability of counts across locations

313 Negative Binomial Safety Model
(1) C|A is the Poisson-distributed crash count with average A, (2) A = a·G(1,α), a = f(x), typically, exp(∑xβ’). where: C = NB-distributed crash count, A = Gamma-distributed crash frequency (with mean a and over-dispersion parameter α), x = model variables, β’ = model parameters, G(1, α) = Gamma variables with mean equal to 1. var C|A = A, var A = ·a2, var C = E[var(C|A)]+var[E(C|A)] = E(A)+var(A)=a+·a2 A confidence interval for the mean is based on Gamma distribution

314 Negative Binomial Safety Model
Frequently used models Highway sections Intersections

315 Rural Intersections Bonneson and McCoy (1993)

316 Rural Intersections Crash Models for Rural Intersections: Four-Lane by Two-Lane Stop-Controlled and Two-Lane by Two-Lane Signalized, PUBLICATION NO. FHWA-RD OCTOBER a = exp(0 + 1 log AADT 2 log AADT2 + b1 X1 +… + bn Xn) , b

317 Rural Intersections PUBLICATION NO. FHWA-RD-99-128 OCTOBER 1999
90 percent confidence interval for the mean Fi=15,000, a = exp(-0.442) ∙ (4∙(15∙15) ) = 13.7 crashes/year Gamma parameters: α’=1/0.294 = 3.40, β = 0.294∙13.7 = 4.03 al = GAMMAINV(0.05, 3.40, 4.03) = 4.1 au = GAMMAINV(0.95, 3.40, 4.03) = Graph

318 Safety in Work Zones (Kanipakapatnam, Tarko, 2000)
Total Number of Crashes Inside Work Zone Variable Coefficient Standard error t-ratio p-value Log k 1.3514 0.0000 ADT 1.1588 0.2207 5.2501 Time 0.5126 0.2425 2.1138 0.0345 Length 0.7601 0.1573 4.8331 Cost Rate 0.1615 0.0558 2.8969 0.0038 Work Type 2.3080 0.3128 7.3776 0.5593 0.1437 3.8926 0.0001

319 Rural Two-lane Roads (Eranky, Tarko, 1999)

320 Urban Arterial Streets (JTRP research for Indiana SMS, Brown and Tarko, 1999)
Total crashes = x Segment length x Years x AADT x EXP ( x Access density – x Shoulder x PS – x TWLTL – x Median ),  = 1.15 where: Length = segment length expressed in kilometers AADT = average annual daily traffic in 1000s vehicles/day Access density = number of access points per kilometer PS = proportion of access points that are signalized Shoulder = 1 if shoulder is present, 0 otherwise TWLTL = 1 if two-way left-turn lane is present, 0 otherwise Median = 1 if median exists with no openings between signals, 0 otherwise.

321 Urban Arterial Streets Transferability Of Models That Estimate Crashes As A Function Of Access Management, Miller, Hoel, Kim, and Drummond, TRB meeting Application to Virginia arterial streets

322 Urban Arterial Streets Application to Virginia arterial streets

323 Urban Arterial Streets Application to Virginia arterial streets

324 Use of Safety Performance Functions
Analysis of the presence Estimate present safety Identify “abnormal” locations Prediction of the future Predict future safety Predict the effects of improvements

325 Highway Traffic and Safety Analyses
Lecture 19: Combining Information about Crash Frequency Purdue University School of Civil Engineering West Lafayette

326 Sources of Information about Crash Frequency
Safety performance function (SPF) a,  Crash counts c, n

327 Information Equivalence Hauer and Persaud, 1984

328 Combining Information from Two Crash Counts

329 Combining Information from SPF and Crash Count

330 Confidence Interval for the Crash Frequency
Mean estimate: a0 = 3.12, 0 = 0.130 c0 = 1/0.130 = 7.69, n0 = 1/(3.12·0.130) = 2.47 In Excel, Gamma distribution has parameters: ’ = 1/ = c and  = a· = 1/n ’ = and  = 1/2.47 = 0.405 90 % confidence interval (k = 0.90) Lower limit is GammaInv(0.5-k/2, ’, ) GammaInv(0.05, 7.69, 0.405) = 1.52 Upper limit is GammaInv(0.5+k/2, ’, ) GammaInv(0.95, 7.69, 0.405) = 5.16

331 90 % confidence interval

332 Effect of Combining Information
Source c n a al au au-al First 3.12 0.130 Second 12 5 Combined

333 Effect of Combining Information
Source c n a al au au-al First 2.47 7.69 3.12 0.130 5.16 1.52 3.64 Second 12 5 Combined

334 Effect of Combining Information
Source c n a al au au-al First 2.47 7.69 3.12 0.130 5.16 1.52 3.64 Second 12 5 0.083 2.40 2.26 3.64 1.38 Combined

335 Effect of Combining Information
Source c n a al au au-al First 7.69 2.47 3.12 0.130 1.52 5.16 3.64 Second 12 5 2.40 0.083 1.38 3.64 2.26 Combined 19.69 7.47 2.64 0.051 1.74 3.68 1.94

336 Crash Count (a=2.40, =0.083) Combined Sources (a=2.64, =0.051) Safety Performance Function (a=3.12, =0.130)

337 Effect of Combining Information
Source c n a al au au-al First 7.69 2.47 3.12 0.130 1.52 5.16 3.64 Second 12 5 2.40 0.083 1.38 2.26 Combined 19.69 7.47 2.64 0.051 1.74 3.68 1.94 Perfect knowledge 2.80

338 Predicting the Number of Crashes
How likely are 7 crashes next year if the mean crash count is 5 ( = 0)? The answer is Poisson(x, a, 0), Poisson(7, 5.0, 0) = 0.104 How likely are 7 or less crashes next year if the mean crash count is 5 ( = 0)? The answer is Poisson(x, a, 1), Poisson(7, 5.0, 1) = 0.867

339 Poisson (a=5.0, =0.0)

340 Predicting the Number of Crashes
How likely are 7 crashes next year if the mean crash count is 5 ( = 0.5)? In Excel, Negative Binomial distribution has parameters: r = 1/ = c and p = 1/(1+·a) = n/(n+1) r = 1/0.5 = 2.0, p = 1/(1+50.5) = 0.286 The answer is NegBinomDist(x, r, p), NegBinomDist(7, 2, 0.286) = 0.062

341 Poisson (a=5.0, =0.0) Negative Binomial (a=5.0, =0.5)

342 School of Civil Engineering
Highway Traffic and Safety Analyses Lecture 20: Identifying Hazardous Locations Purdue University School of Civil Engineering West Lafayette

343 Reading Assignment Chapter 4, pages 9-26, in “Guidelines for Highway Safety Improvements in Indiana,” access via HAT – prototype software distributed in class

344 Safety Management System Decision-making Process
Identify highway hazard Determine causes Determine countermeasures Develop safety projects Select projects for implementation Evaluate projects effectiveness

345 Identifying Hazardous Locations
Identification task Criteria for selection of locations Statistical quality control Policy-based criterion Exposure-based criterion Rank list Other methods Safety index Safety priority index

346 Identification Task OBJECTIVE
Select sites that can have safety considerably improved with cost-effective remedial actions ISSUES Many candidate locations (sites) Limited information about the sites CONSEQUENCES OF INCORRECT SELECTION Selecting safe locations causes costs wasted on detail analysis of these locations Not selecting hazardous location eliminates this location from further consideration

347 Selection Criteria Excessive crash frequency
For example, a > am Promotes the most cost-effective mitigation of hazard (system perspective) Excessive risk faced by users For example, r > rm, where r = a/E Promotes fairness of the highway system by reducing the differences in risk experienced by users (user perspective)

348 Statistical Quality Control Policy-based am
If am is assumed by policy, how large crash count c in n years has to be to indicate that the unknown crash frequency is higher than am (hazard is statistically evident)? Hazard is statistically evident at the significance level p if : Pr(C≥c |mean = n·am) = p ≤ p*. The lowest such c is control limit Lp* L0.10 L0.05 L0.01

349 System Perspective – Example 1 Policy-based am
Maximum frequency am = 5 crashes per year p* = 0.10 Number of crashes during one year c = 8 Does the location deserve attention? p = Pr(C≥8|mean=5) = 1- Poisson(8-1,5,1) p = > p* The location does not deserve attention

350 System Perspective – Example 1 Policy-based am
p = Pr(C≥8)|mean=5) = 0.133 p > p*

351 System Perspective – Example 2 Policy-based am
Maximum frequency am = 5 crashes per year p* = 0.10 Number of crashes during the last three year c = 21 Does the location deserve attention? p = Pr(C≥21|mean=3·5) =1- Poisson(21-1,15,1) = 0.083 p < p* The location deserves attention

352 User Perspective – Example Policy-based rm
The maximum crash rate for two-lane rural segments is rm = 1 crash/million VMT A road segment has AADT = 10,000 veh/day and is L=2.3 miles long Observed number of crashes c during the last three years (n=3) is 35 The required significance level is p*= 0.05 Does this segment require attention?

353 User Perspective – Example Policy-based rm
am = rm·E = (rm)·(AADT·L·365·n/b) am = (1.0)·(10,000·2.3·365·3/1,000,000) = 25.2 p =1-Poisson(35-1, 25.2, 1) = 0.037 p < p* The segment requires attention

354 Statistical Quality Control Exposure-based am Estimate
A safety performance function that includes only exposure variables estimates the crash frequency an conditioned on the exposure The location deserves attention if the crash frequency is higher than the expected one Past research indicates that this criterion balances the user and system perspectives

355 Statistical Quality Control Exposure-based am Estimate
A signalized intersection with known volumes and with 46 crashes last year is analyzed at the p*=0.05 significance level a = 25.4 crashes/year from a safety performance function with over-dispersion  = 0.2 p = Pr(C≥c) = 1 - x=0..c-1 NegBinomDist(x, 1/, 1/(1+·a)) Useful equivalence x=0..c NegBinomDist(x, s, f) = BetaDist(f, s, c+1) p = 1- BetaDist(1/(1+·a), 1/, c) p = 1- BetaDist(1/(1+0.2·25.4), 1/0.2, 46) = 0.062 p > p* The site does not require attention

356 Index of Crash Frequency Introduction

357 Index of Crash Frequency (Policy-based am = 5, n = 1)
IF = Index of Crash Frequency IF = (c – n·am)/sigma Var = var c + var (n·am) = 8 IF = (8-5)/81/2= 1.06

358 Index of Crash Frequency (Exposure-based estimated am = 5, α = 0
Index of Crash Frequency (Exposure-based estimated am = 5, α = 0.2, n = 1) IF = (c – n·am)/sigma Var = c+α·(n·am)2 = 8+0.2·(1·5)2 = 13 IF = (8-5)/131/2 = 0.83

359 Index of Crash Cost IC where wi is the cost of crash of severity i.
Remark: wi can be any equivalency factor for any crash category i. The name of the calculated index should reflect its meaning. RoadHAT

360 Rank List Roads sorted by evidence of safety problems (crash counts, calculated p, certain safety index) An agency selects top candidates according to available safety resources

361 Other Methods Safety Index
Equivalent Property Damage Only crashes (EPDO) EPDO = PDO + wI·INJURY + wF·FATAL where wI is the weight for an injury crash, and wF is the weight for a fatal crash Weights may reflect the differences between the average costs of crashes

362 Other Methods Safety Priority Index System (Oregon DOT)
Crash counts recorded for urban segments of 0.05 mi, and for rural segments of 0.10 mi. n = number of years, c = total crash count.

363 Highway Traffic and Safety Analyses
Lecture 21: Identifying Safety Deficiencies and Countermeasures Purdue University School of Civil Engineering West Lafayette

364 Reading Assignment GUIDELINES FOR ROADWAY SAFETY IMPROVEMENTS, October 2006, link. Chapter 5: SAFETY REVIEW OF HIGH CRASH LOCATIONS, Pages 27-46

365 Identifying Safety Deficiencies and Countermeasures
Safety audits Analysis of hazardous locations Collision and condition diagrams On-site observation Crash reduction factors ? Motorist feedback ?

366 Road Safety Audits What is Road Safety Audit?
Formal examination of an existing or future road or traffic project by an independent team of trained specialists to identify road safety deficiencies. Summary of the ITE report on RSA

367 Stages of safety audits = Stages of a road project
Road Safety Audits Stages of safety audits = Stages of a road project Feasibility Study -- scope of a project, route choice, selection of design standard, impact on the existing road network, route continuity, provision of interchanges or intersections, access control, number of lanes, route terminals, stage development, and more. Preliminary Design -- horizontal and vertical alignment, sightlines, intersection layouts, land and shoulder width, pavement side slope and superelevation, overtaking lanes, provision for parked and stationary vehicles, provision for cyclists and pedestrians, effects of departures from standards and guidelines, safety during construction.

368 Road Safety Audits Detailed Design -- line markings, signing, delineation, lighting, intersection details, clearances to roadside objects, provision for road user groups with special requirements (for instance, pedestrians, cyclists, people with disabilities, trucks and buses), temporary traffic management and control during construction, drainage, poles and other roadside objects, landscaping, slopes and guard fencing. Pre-opening -- the audit team would walk or drive through a project to check on the quality of completed safety features. They would inspect many of the same items as were considered during the design process, and they would try to be at the project during different conditions--day and night, wet and dry, etc. In-service -- identifies weaknesses in the functioning of safety features while the road is open to motorists.

369 Example Road Safety Audit Form
N/A Yes No Comments STAGE 2: DRAFT DESIGN 2.2 DESIGN ISSUES (GENERAL) 1 Geometry of Horizontal and Vertical Alignment 1A Does the horizontal and vertical design combination of the road provide a suitable alignment for drivers? 1B Do the combinations of horizontal and vertical design elements conform to design practice? (i.e. there shouldn’t be undesirable combinations of horizontal and vertical design) 1C Is the design free of cues that would cause a driver to misread the road characteristics? (e.g. visual illusions, confusing delineation of lines of trees, poles, etc.) 1D Does the alignment selected ensure speed consistency? 1E Are overtaking / climbing criteria met? 2 Typical Cross Sections 2A Are the lane widths, shoulders, medians and other cross section features in accordance with standard design and adequate for the function of the road? 2B Is the width of traffic lanes and roadway suitable in relation to: - alignment? - traffic? - vehicle dimensions? - speed environment? - combinations of speed and traffic volume?

370 Road Safety Audits Process
The audit team should include specialists of highway safety engineering. The findings and audit advice should be documented and formally reported. The reasons for rejecting any element of advice should be explained. Provisions for arbitration should be made. Independence of audit must be maintained, and there should be an awareness of possible litigation if there are subsequent failures.

371 Road Safety Audit RSA tends to improve nominal safety
RSA improves objective safety only if the design and traffic control standards are correct and experts are right Highway administration accepts RSA if RSA is believed to reduce the risk of litigation

372 Analysis of Hazardous Locations
Prepare a collision diagram Identify predominant crash patterns Visit the site Prepare a condition diagram Look for safety deficiencies Propose countermeasures Sight distance, volume, speed, and other studies may be needed

373 Collision Diagram A collision diagram includes:
Drawing of intersection Identification of diagram Identification of streets and crash information: Direction of travel Date of accident Time Road conditions Weather conditions Any unusual conditions (flood, storm, intoxication, etc.)

374 Collision Diagram

375 Collision Diagram http://www. dot. state. mn

376 Example Collision Diagram www. city. niagarafalls. on
Example Collision Diagram

377 On-site Observations Seeing the road from drivers’ perspective can be revealing Watching traffic can be revealing (traffic conflicts, traffic violations, erratic behavior) A manual of road safety audits can be useful

378 On-site Observation Visit during conditions with the high crash frequency (rush hour, night, winter?) Make a condition diagram Drive the road Walk the road Watch the traffic Videotape from the drivers’ position (in motion) Videotape from the raised elevation (stationary camera) Make still pictures of the road for documentation Make report, drawings, audio recording Look for design and traffic control deficiencies

379 Condition Diagram A condition diagram should include: Curbs
Roadway limits Property lines Sidewalks Driveways View obstructions on corners Physical obstructions on roadway Ditches Bridges Traffic signals Signs Pavement marking Streetlights Grades Road surface Type of adjacent property Irregularities (potholes, dips, etc.)

380 Condition Diagram

381 On-Site Observation Report

382 Location Analysis Form

383 Crash Reduction Factors ?
Crash reduction factors give the expected percent reduction of crashes after a specific improvement Do not use crash reduction factors to get an idea of safety improvements Most of the crash reduction factors have been derived after a particular road deficiency has been corrected They may overstate the safety effect if a road or control change is not needed

384 Travelers’ Feedback ? People’s complaints represent subjective safety
They impact decisions about safety projects (political pressure) They may include valuable information about road safety deficiencies The link between subjective safety and objective safety is not fully understood Caution should be exercised

385 Highway Traffic and Safety Analyses
Lecture 22: Traffic Conflicts Technique Purdue University School of Civil Engineering West Lafayette

386 Outline Concept On-site observations Analyses

387 Concept – Traffic Conflict
Traffic conflict occurs when one or two drivers have to rapidly slow down or swerve to avoid collision with another vehicle.

388 Concept – Time to Collision
Time when the collision point is occupied by another vehicle Hypothetical collision happens Time to collision (TTC) is the time measured between the moment of the evasive action beginning and the hypothetical moment of collision if the evasive action was not taken. Trajectory of the vehicle Distance Hypothetical trajectory of the vehicle Time to collision (TTC) Beginning of the evasive maneuver Time

389 Concept Time to Collision
TTC Score TTC (s) Risk of collision 1 Low 2 Moderate 3 High

390 Concept – Time to Collision
Time-to-collision zones correspond to the TTC ranges: , ,

391 Concept –Secondary Conflict

392 Concept –Secondary Conflict

393 Concept –Secondary Conflict

394 Concept – Traffic Conflict Types

395 Concept – Traffic Conflict Types

396 On-site Observations - Field Form

397 On-site Observation - Observers
TWSC intersection requires 2 for 16 hours (two days)

398 On-site Observation - Observers
Signalized intersection requires 4 observers for 8 hours or 2 observers for 16 hours

399 On-site Observations - Training
Day One: Fundamentals of Traffic Conflicts Technique Day Two: First and Second Field Observations and Debriefing Day Three: Third and Fourth Field Observations and Debriefing Compressed program does not include the third day

400 Analysis Distribution by type Spatial distribution Conflict frequency
Conflict severity Temporal distribution Conflict causes and interpretation

401 Analysis

402 Analysis – Spatial Distribution

403 Analysis - Average Hourly Conflicts

404 Analysis - Average Hourly Conflicts per Thousand Entering Vehicles
AHC/TEV = AHC·1,000/Average Hourly Volume

405 Summary of Conflict Characteristics

406 Reading Assignment

407 References G.D. Hamilton Associates Consulting Ltd., Traffic Conflict Procedures, Manual, Second Edition, Insurance Corporation of British Columbia, November 1996

408 School of Civil Engineering
Highway Traffic and Safety Analyses Lecture 23: Selecting Safety Projects Purdue University School of Civil Engineering West Lafayette

409 Safety Management System Decision-making Process
Identify highway hazard Determine the causes Determine countermeasures Develop safety projects Select projects for implementation Implement the selected projects Evaluate projects’ effectiveness (before-and-after studies) Next year Updating CRFs

410 Safety Projects A safety project includes a set of improvements for a certain location. The improvements should be justified with the site investigation. A safety project should be specific sufficiently to evaluate its cost with reasonable accuracy. A safety project should have predicted number of crashes saved in each considered category.

411 Selection Tasks Task 1 From potential projects for a single location, select the most cost-effective one. The selected project has to be feasible (benefits exceed costs). Task 2 From projects identified for multiple locations in Task 1, select a subset of projects that promise the highest total safety improvement and the total cost fits the budget.

412 Benefit-to-Cost Ratio
Benefit = Cost of the saved crashes during the period of analysis Cost = Installation/construction and maintenance costs during the period of analysis, salvage value (negative or positive) Period of analysis = project lifetime, sequence of project lifetimes Present worth or equivalent annual amount methods

413 Time Frame for Economic Evaluation
Present year (PY) Implemen-tation year (PI)

414 Cost Components (GT)

415 Present Benefit Present year (PY) Implementation year (IY) Y3 Y4 Y2

416 Present Benefit

417 Present Cost

418 Equivalent Uniform Annual Benefit
Equivalent Uniform Annual Cost

419 Economic Effectiveness
Benefit-to-Cost Ratio Net Annual Benefit Present Worth Net Benefit

420 Project Lifetime Examples from Hazard Elimination Safety – Program Criteria, Minnesota Department of Transportation, Feb. 1994 Improvement Lifetime (Years) Construct turning lanes at intersections 10 Improve sight distance at intersection Install traffic signs 6 Install pavement marking 2 Widen traveled way 20 Install median barrier 15 Construct pedestrian overpass/underpass 30 Improve RR crossing surface Relocate highway to eliminate RR crossing

421 Crash Frequency Safety Performance Function and Counts
 = 0.2, over-dispersion factor; a = 6.2, crash frequency estimate; Crash counts c = 16, crash count; n = 2, number of years; Final estimate of crash frequency:

422 Crash Reduction Factors Example Indiana Values
COUNTERMEASURE All Fatal or Injury PDO Install Inside Shoulders [AA] b a) Rural Multi-Lane 4 feet shoulders 6 feet shoulders b) Urban Multi-Lane 70 84 56 71  Widen Lane a)Rural Two-Lane [AA] b Add 1 Foot to Both Lanes Add 2 Feet to Both Lanes    16 29 20 37 12 22 b)Urban Two-Lane [AA] b 30 24 Widen Median [AA]b Rural Multi-Lane Widening 4 Feet Widening 10 Feet Widening 20 Feet 19 42 66 10 23 41 21 44 68 Widen Median at Intersections [AA]b   Widening 4 Feet  5  6 14 26 Crash Reduction Factors Example Indiana Values

423 Crash Costs Oregon Department of Transportation – injury and fatal crashes (1995) Location Urban Rural Freeway 62,500 121,400 State highway 60,000 122,800 County/Local 60,800 105,500 City 54,400 N/A

424 Crash Costs Minnesota Department of Transportation (1994)
PDO = $2,000; INJ = 26,500; F = $500,000 Wisconsin Department of Transportation (1997) PDO = $7,000; INJ = 35,000; F = $70,000 Michigan Department of Transportation (1997) PDO = $1,600; INJ = 10,800; F = $240,000

425 Crash Costs Maryland Department of Transportation, state roads (1996)
Crash severity Urban Rural All roads Fatal 3,572,000 3,704,000 3,635,780 Injury 114,700 115,800 115,003 Property Damage Only 23,800 19,650 22,675 All crashes 91,579 124,483 100,634

426 Procedure Define potential projects for each hazardous location
Estimate the B/C and NAB for each project Eliminate projects with B/C  1 Select projects with the highest B/C or NAB for each hazardous location Find such subset J of projects that Max jJ NABj s.t. jJ CCj ≤ Budget Constrained knapsack problem

427 School of Civil Engineering
Highway Traffic and Safety Analyses Lecture 24: Before-and-after Studies Purdue University School of Civil Engineering West Lafayette

428 Outline Evaluation task Crude method Negative binomial test
Regression-to-mean effect Demonstration Mitigation Adjustment for change in exposure Example

429 Evaluation Task Is the crash frequency after the road improvement lower than the crash frequency that would be during the same “after” period if the road improvement were not introduced? Safety before improvement aB Safety after improvement aA Safety during after period but without road improvement a0A

430 Crude Method Assumption:
Safety does not change if the improvement is not introduced. a0A = aB Example: Let cB=10 crashes for nB = 3 years before improvement and cA= 5 crashes for nA = 2 years after improvement. a0A = aB = cB/nB = 3.3, aA = cA/nA = 5/2 = 2.5 The improvement is effective because (a0A - aA) = 3.3 – 2.5 = 0.8 > 0

431 Uncertainty The crude method does not consider uncertainty
Values a0A and aA are only estimates of the true crash frequencies A statistical test is needed to help decide whether the observed difference in crash counts is significant

432 nAa0A = 10.0 0A = 0.2 cA= 2 nAa0A = 5.0 0A = 0.5 cA= 0 0.045
Concept of a Test P0= 0.05 cA= 2 nAa0A = 5.0 0A = 0.5 cA= 0

433 Negative Binomial Test
Consider two hypothesis, H0: aA = a0A and H1: aA < a0A. Select significance level P0. Assume hypothesis H0 true (no safety effect) Assuming H0 calculate likelihood P that C  cA If P  P0 then state that there is no basis to claim that H0 is true, and conclude that aA < a0A.

434 Negative Binomial Test Example
cB = 10, nB = 3, cA = 5, nA = 2 Significance level P0 = 0.10. aB=cB/nB=10/3=3.33, B = 1/cB = 1/10 = 0.1 a0A = aB = 3.33, 0A = B = 0.1 6. P = 0.40 > P0  The safety increase is insignificant

435 Regression-to-mean Hauer and Lovell, TRR 1068, 1987
Number of intersections Crashes per intersection in 1976 Average crashes per intersection in 1977 562 0.53 287 1 0.94 155 2 1.37 74 3 1.72 33 4 2.61 13 5 3.00 11 6 2.64 7 2.25 8 1.00 9 3.50 Total crashes = 120 Total crashes = 46 Crashes “saved” = 120 – 46 = 74

436 Regression-to-mean Bias Mitigation Use of Safety Performance Function
a1 = before crash frequency estimated with the safety performance function (crashes/year),  = overdispersion factor, cB = crash count before improvement, nB = number of before years, aB = before crash frequency updated with the before crash count, B = over-dispersion parameter updated with the before crash count.

437 Adjustment for Changed Exposure to Risk
Before crash frequency a1 calculated with a crash performance function based on before annual exposure EB After crash frequency a2 calculated with a crash performance function based on after annual exposure EA Before annual frequency aB updated with crash counts Adjustments: a0A = aB· (a2/a1) which simplifies in most cases to (EA/EB)β, 0A = B

438 Example A rural two-lane segment 2.3-mile long has been modernized by upgrading the curves. Check the safety effect of this road improvement. Tables 1 provides safety and exposure data for the subject segment. Crash frequency for non-modernized segments can be predicted using the following equation: a = ·AADT·L,  = 0.15.

439 Example Table 1 Data for the subject segment
Year Crashes AADT 1993 8 10,100 1994 15 10,300 1995 13 10,500 1996 12 11,100 1997 7 11,300 1998 Year of modernization 1999 12,000 2000 6 12,300 2001 10 12,400

440 Example Counts and number of years
cB = = 55 crashes, nB = 5 years cA = = 24 crashes, nA = 3 years Average annual AADT AADTB = 10,660 veh/day, AADTA = 12,233 veh/day

441 Example Before annual crash frequency adjusted for regression-to-mean effect a1 = ·10,660·2.3 = 4.9 crashes/year aB = (1/+cB)/(1/(·aB)+nB) = (1/ )/(1/(0.15·4.9) + 5) = 9.7 crashes/year B = 1/(1/ +cB) = 1/(1/ ) = 0.016

442 Example Adjustments for change in exposure
EA/EB = (12,233·365·2.3)/(10,660·365·2.3) = 1.15 a0A = (EA/EB)1.0·aB = 1.15·9.7 = 11.2 0A = B = 0.016 Predicting counts for the after period Pr(C≤24) = BetaDist(0.650, 62.5, 25) = 0.095 6. The improvement is barely significant at the level of 0.10.

443 Highway Traffic and Safety Analyses
Lecture 25: Estimating and Updating Crash Reduction Factors Purdue University School of Civil Engineering West Lafayette

444 Outline Estimation of crash reduction factors for a single site
Control site Multiple sites Estimation accuracy Significance test Updating crash reduction factors

445 Reference Crash Frequency a0A
This is the expected annual number of crashes a0A for the after period assuming no road improvement The best estimate of the expected annual number of crashes before improvement (before crash frequency) Adjust the obtained crash frequency for the change in the annual exposure (EA/EB)β

446 Estimation of the Crash Reduction Factor for a Single Location

447 Crash Reduction Factor for a Single Location - Example

448 Estimation of the Crash Reduction Factor with Control Location

449 Estimation of the Crash Reduction Factor with Control Location

450 Multiple Locations The procedure of estimating the crash reduction factors is as follows Calculate aA, var aA, a0A, and var a0A for each treated location i and untreated (control) location k. Calculate total values for treated sites Calculate total values of untreated (control) group. Repeat remaining steps leading to θ, var θ, θ’ and var θ’ as for a single location but using the total values Calculated adjusted F, its variance and standard deviation.

451 Significance Test

452 Updating Crash Reduction Factors
“Old” crash reduction factor F1 with the estimation variance var F1 (normal distribution) “New” crash reduction factor F2 with the estimation variance var F2 (normal distribution) The old and new estimates are independent

453 Updating Crash Reduction Factors

454 Updating Crash Reduction Factors

455 Highway Traffic and Safety Analyses
Lecture 26: Human Behavior and Road Safety Purdue University School of Civil Engineering West Lafayette

456 Human Behavior 85-95 percent of crashes are attributed by experts to faulty human behavior

457 Human Behavior Theories Behavioral issues Countermeasures
Perceived vs. accepted risks Theory of rational choice Homeostasis theory Behavioral issues Aggressive driving Runs on red Speeding Road rage Countermeasures

458 Theories

459 Perceived vs. Accepted Risks
Perceived risk Traffic and road situation Driver traits Driver experience (knowledge) Driver state Accepted risk Driver state and traits Travel purpose and time constraints Perceived gain from taking a risk

460 Perceived and Accepted Risks versus Objective Risk
Road Traffic Driver Objective Risk

461 Perceived and Accepted Risks versus Objective Risk
Road Driver Behavior Traffic Driver Objective Risk

462 Perceived and Accepted Risks versus Objective Risk
Perceived Risk Road Driver Behavior Accepted Risk Traffic Driver Objective Risk

463 Perceived and Accepted Risks versus Objective Risk
Sweden changed to driving on the right. It resulted in 17% less road deaths in the first year (Guardian, 26 January 1996). Accepted risk  , perceived risk  => Risk-taking behavior  After introducing free-market economy in Poland in late 1980s, the crash rates increased by 30 percent. Accepted risk , perceived risk  => Risk-taking behavior 

464 Theory of Rational Choice
Drivers consider Alternative behaviors (slow down, accelerate, change lane, etc.) costs associated with each behavior (likelihood of crash and its outcome) benefits associated with each behavior (time gain, personal satisfaction) Drivers select the alternative with the highest net benefit

465 Risk Homeostasis Drivers have their own target risk
They reduce (compensate) risk with more cautious behavior if Perceived Risk > Target Risk They change behavior towards more dangerous if Perceived Risk < Target Risk

466 Risk Homeostasis Examples of risk-taking behavior The first indicator
Risky leisure activities (mountain climbing, rodeo riding, gambling, etc.) The first indicator In 1968, Congress mandated seat belts and several other safety equipment 20-percent reduction in fatalities were predicted as a result of improving millions of cars Safety researches found no difference in fatalities

467 Risk Homeostasis Seat belts Speed limit
Volunteers drove go-karts with and without seat belts The average speed of people wearing seat belts was higher than those who did not Speed limit In 1987, the federal government allowed for raising speed limit from 55 to 65 miles/hour Fatalities in states with the 65 speed limit where lower than in the other states by three percent WATCH: Do Safer Cars = Dangerous Drivers?

468 Behavioral Issues

469 Aggressive Driving What behavior is aggressive
Aggressive Driving What behavior is aggressive? – survey of Canadian drivers Percent of Respondents Behavior 1999 2000 Tailgating 93 Passing on the shoulder 88 87 Making rude gestures 86 Pulling into someone else's parking space 80 82 Changing lanes without signaling 75 73 Flashing high beams at car in front 74 72 Drive through yellow lights turning red 69 Merge at last second with traffic on highway 66 Speeding (20km/h or more over speed limit) 65

470 Aggressive Driving Red Signal Running
In 1998, there were 89,000 red light running crashes that resulted in 80,000 injuries and 986 deaths. 56 percent of Americans admit to running red lights.

471 Aggressive Driving Red Signal Running
Indiana drivers’ survey (2000/2001) 56 % see red signal running several times a week 55 % think that drivers are in hurry 27 % think that drivers do not pay attention 68 % think that less than 10% violators are ticketed by the police 59 % believe in enforcement 78 % would support photo-enforcement

472 Aggressive Driving Red Signal Running
West Lafayette research (2001/2002) No enforcement: 20 % of drivers arriving at the beginning of red signal runs it Residual effect of police enforcement: 5 % of drivers arriving at the beginning of red signal runs it The residual effect does not last long Violation rate significantly lower if students aren’t in the flow (vacation)

473 Aggressive Driving Speeding

474 Aggressive Driving Speeding

475 Cultural norms of disrespect = Road Rage
More congestion + Cultural norms of disrespect = Road Rage

476 Road Rage Verbal Quiet Epic yelling, honking, rude gestures, insulting
rushing, competing, resisting Epic cutting in, blocking, chasing, fighting, shooting

477 Countermeasures

478 Countermeasures Perceived vs. Accepted Risks
Increase the risk perception Educate about human limitations Provide road hazard facts to public Educate about drug impacts Display warning signs Law and enforcement (additional risk) Decrease the risk acceptance Gratification of safe driving (premium by employer) Any other ideas?

479 Countermeasures Aggressive Driving – AAA Survey of Agencies http://www

480 Countermeasures Red Signal Running http://safety. fhwa. dot
Photo-enforcement 1997, Oxnard, California, population 151,000 Nine camera sites, $104 fine and one point on the driver's license. A 30-day warning period during which red light cameras photographed violators, but no tickets were issued. The red light violation rate reduced 42 percent. Increase of red signal compliance on unequipped intersections as well

481 Countermeasures Speeding –Survey of Drivers http://www. nhtsa. dot
More police assigned to traffic (85%) More frequent ticketing (82%) Double or triple fines (81%) Revoking licenses more often (81%) Increased insurance costs (80%) Road design changes (78%)

482 Countermeasures Road Rage webpages.marshall.edu/~harrison2
Database of Unsafe Driving – license plate numbers of drivers who were acting upon road rage Quality Driving Circles – groups of drivers who meet discuss their difficult driving experience Education - educational materials, public service announcements, self-tests, self-help and self-education through the Internet

483 Countermeasures Road Rage http://www. aaafts
Legislation directed at controlling road rage in 17 states Enforcement: unmarked cars, plain-clothes police officers, helicopters, airplanes, video cameras, air patrols in contact with grounded policemen (TRIAD – Targeting Reckless, Intimidating, and Aggressive Driving in Ohio)

484 Countermeasures Improve the Road www.nous.org.uk/reform.html
"Don't attempt to reform man. An adequately organized environment will permit humanity's original, innate capabilities to become successful. Politics and conventionalized education have sought erroneously to mould or reform humanity.“ Utopia or Oblivion, Buckminster Fuller, 1969. "increasing safety and decreasing accidents by engineering improvements of motor vehicles while also providing overpasses and banked turns for the vehicles to drive on, instead of trying to reform the vehicle-drivers' behaviors" . Critical Path, Buckminster Fuller, 1981.

485 Highway Traffic and Safety Analyses
Lecture 27: Internet-Supported Evaluation of Highway Safety Purdue University School of Civil Engineering West Lafayette

486 Presentation Outline Research Goals Website Design Data Collection
Survey Tool Evaluation Evaluation of Safety Information Conclusions

487 Research Goals Develop a prototype website to obtain motorist feedback about hazardous locations Investigate the relationship between driver perception and highway safety

488 Website Design

489 Website Design

490 Data Collection

491 Data Collection 146 responses Almost all were complete (non-blank)
95 intersections

492 Evaluation of Survey Tool
User feedback Common complaints Map outdated More options desired

493 Motorist Concerns

494 Sources of Motorist Concern

495 Top Reported Locations

496 Can Motorists Point Out Hazard?
Evidence

497 Effectiveness of Detecting Hazard

498 Evaluation of Safety Information
Gender and Age Effects No significant difference between male and female respondents Efficiency Rate tends to increase as respondent age increases

499 Conclusions Much safety information to be gained through the survey
Locations indicated by motorists tend to be more hazardous than those not indicated Gender and age of respondents have no significant effects Considering only responses that include first-hand information is justified Motorist feedback is a good supplement to crash data Tarko, A. and B. DeSalle, Perception-base road hazard identification with Internet support, Applied Health Economics and Health Policy, Open Mind Journals, Vol.2, No.4, 2003, pp


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