1 The Four-step Travel Model GEOG 111 & 211A – Fall 2004 October 14

2 Outline Background Role of Simulation General Process Example of Most Popular Simulation Model Examples of Other Ideas Summary

3 Needs Identify Projects for the Region Use Formal & Accepted Technique(s) to Estimate Project Impacts Simulate the Region for the Next 20 Years Create Scenarios for BEFORE and AFTER a Project or Group of Projects

4 Create a Comprehensive Plan of how we want the area to be in the future Propose projects designed to achieve the goals of the Comprehensive Plan Test Scenarios implementing different projects and forecast their effects Determine what projects should be continued to next stage Present recommendations to decision makers How Do we use Simulation Models?

5 Project Types New Highways (e.g., bypass-ring roads) New Management Activities (e.g., park & ride, signal systems ) New Land Uses (e.g., a new industry, a new residential neighborhood) New Technologies??????? (maybe in management)

6 The Context Urban Transportation Planning System (UTPS) & Urban Transportation Modeling System TEA 21 made it also A Statewide Transportation Planning System Technology should be added (see Pennplan) Associate quantitative estimates with performance measures as in the monitoring part (see PennPlan) Four-step scheme followed today in many MPOs Four-step travel model is limited but popular!

7 Goals and objectives Surveillance Reappraisal Procedural development Service Annual report Continuing elements Policy and technical development Develop immediate action plan PennDOT MPOs TMAs LDDs Local gov’ts Citizen participation Transportation organizations Plan implementation Land use Trip generation Trip distribution Modal split Traffic assign. Calibrate models Population Land use Economic Traffic Revenues Areawide forecast = Part of the Sequential Demand Forecasting Process Develop alternatives Apply models Land use Trip generation Trip distribution Mode choice Traffic assign. Plan testing, evaluation and selection Analysis of future alternative systems Population Land use Economic activity Transportation system Travel volumes Terminal and transfer facilities status & use Financial resources Community values Inventories and data collection DATADATA Typical Process in Long Range Planning

8 The Sequential Forecasting Process & the Urban Transportation Planning System (UTPS) [adapted from Papacostas & Prevedouros, 1993] Transportation system specification Network Assignment Mode Choice Trip Generation Trip Distribution Land use and socioeconomic projections Direct (user) Impacts 4-STEP4-STEP

9 Four step in large MPOs Inventory of facilities Opportunity to think strategically Show the impact of projects on air quality Provide report of emissions inventory Tool for policy assessment PSRC example follows!

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11 Forecast future development (business, roadways, and housing) Model the area’s traffic network Estimate model of the area’s traffic network in the future Make changes to network characteristics in the future model Compare network performance under different scenarios of project development What Other Steps Are Required?

12 UTPS Outline Review the Data Inventory for a Region Review one Procedure to Predict Future Volumes on a Highway Summarize the Method Known as UTPS Questions

13 UTPS 4-step Travel Model Trip Generation Trip Distribution Modal Split Traffic Assignment

14 Data (Inventory) Area of study definition & traffic analysis zones Area of study description (highways, facilities, zoning, rules/regulations) Who are the residents? (age, gender, education, employment, income of residents) Where do people leave? Where do people work, shop, etc? Highway characteristics Other information (plans for rezoning)

15 Travel Model Urban Travel Model (‘60s) –Also known as the Four - Step Process –A methodology to model traffic on a network General planning & programming Land use forecasting (where will residences and stores be?) Four Steps: –Trip GenerationEstimate Person Trips for each TAZ –Trip DistributionDistribute Person Trips from TAZ to TAZ –Mode ChoiceConvert Person Trips to Vehicle Trips –Traffic AssignmentAssign Vehicles to the Network

16 Key Concepts of 4-step TAZ: Traffic Analysis Zone – TAZ= a common sense subdivision of the study area –TAZs are used in trip generation and trip distribution –TAZs may be any shape or size, but US Census Blocks, Block Groups, and Tracts are often used (class: WHY?) BlockBlock GroupTract i.e., a city block

17 8-Zone Study Area with Traffic Analysis Zones (TAZs) 8-Zone Study Area z z = all zones outside study area x = TAZ designations study area boundary TAZ boundaries Legend:

18 Key Concepts of UTPS Centroid –Every TAZ (Gate and Internal) has a centroid, usually placed roughly at the geographic center of the TAZ –All trips to or from a TAZ are assumed to start or end at the centroid Discussion –Why do we use TAZs and centroids to model trips?

19 Key Concepts of UTPS Gate TAZs –TAZs placed outside the Study Area where major roads cross the boundaries of the study area –Used to model External Trips (i.e., trips with an origin or destination) Note: Do we care when OD is outside the study area? –Gate TAZs represent all areas outside of the study area (Study Area) Gate TAZ Network

20 Network & Links Numbered Example: Computer schematic representation

Network and Nodes Numbered

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23 Gate TAZ Centroid

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26 Land Use/Economic Analysis Considers general trends Allocates population to geographic subdivisions Assigns land uses Each TAZ contains “observed” numbers for today’s analysis and predicted numbers for forecasting

27 OUTPUT = a map with TAZ’s and their characteristics – households, businesses, employers

28 Trip Generation Process Collect Data, usually by Surveys and Census –Sociodemographic Data and Travel Behavior Data Create a Trip Generation Model (e.g., regression) Estimate the number of Productions and Attractions for each TAZ, by Trip Purpose Balance Productions and Attractions for each Trip Purpose –Total number of Productions and Attractions must be equal for each Trip Purpose –We will discuss balancing later

29 Trip Generation Models Regression Models –Explanatory Variables are used to predict trip generation rates, usually by Multiple Regression Trip Rate Analysis –Average trip generation rates are associated with different trip generators or land uses Cross - Classification / Category Analysis –Average trip generation rates are associated with different trip generators or land uses as a function of generator or land use attributes Models may be TAZ, Household, or Person - Based

30 ITE Trip Generation Manual Trip Rate Analysis Model –Univariate regression for trip generation –Primarily for Businesses –Explanatory variables are usually number of employees or square footage –Models developed using data from national averages and numerous studies from around the US

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32 Possible geographic detail in trip generation with GIS & business data

33 Typical output from trip generation OUTPUT

34 Trip Distribution Convert Production and Attraction Tables into Origin - Destination (O - D) Matrices Destinations Sum Origins Sum T 11 T 12 T 13 T 14 T 15 T 16 O 1 T 21 T 22 T 23 T 24 T 25 T 26 O 2 T 31 T 32 T 33 T 34 T 35 T 36 O 3 T 41 T 42 T 43 T 44 T 45 T 46 O 4 T 51 T 52 T 53 T 54 T 55 T 56 O 5 T 61 T 62 T 63 T 64 T 65 T 66 O 6 D 1 D 2 D 3 D 4 D 5 D 6 TAZP A Sum

35 Trip Distribution, Methodology General Equation: –Tij = Ti P(Tj) Tij = calculated trips from zone i to zone j Ti = total trips originating at zone i P(Tj) = probability measure that trips will be attracted to zone j Constraints: Singly Constrained –Sumi Tij = Dj OR Sumj Tij = Oi Doubly Constrained –Sumi Tij = Dj AND Sumj Tij = Oi

36 Trip Distribution Models Example Gravity Model Tij is: Tij = trips from zone i to zone j = Ti = total trips originating at zone i Aj = attraction factor at j Ax = attraction factor at any zone x Cij = travel friction from i to j expressed as a generalized cost function Cix = travel friction from i to any zone x expressed as a generalized cost function a = friction exponent or restraining influence Sum (A x / C ix ) a T i A j / C ij a

37 Gravity Model Process Create Shortest Path Matrix –How: Minimize Link Cost among Centroids Estimate Friction Factor Parameters –How: Function of Trip Length Characteristics by Trip Purpose Calculate Friction Factor Matrix Convert Productions and Attractions to Origins and Destinations Calculate Origin - Destination Matrix Enforce Constraints on O - D Matrix

38 Shortest Path Matrix Matrix of Minimum Generalized Cost from any Zone i to any Zone j –Distance, Time, Monetary Cost, Waiting Time, Transfer Time, etc.. may be used in Generalized Cost –Time or Distance Often Used –Matrix Not Necessarily Symmetric (Effect of One - Way Streets) TAZ ID TAZ ID C 11 C 12 C 13 C 14 C 15 C 16 C 21 C 22 C 23 C 24 C 25 C 26 C 31 C 32 C 33 C 34 C 35 C 36 C 41 C 42 C 43 C 44 C 45 C 46 C 51 C 52 C 53 C 54 C 55 C 56 C 61 C 62 C 63 C 64 C 65 C 66

39 O - D Matrix Calculation Calculate Initial Matrix By Gravity Equation, by Trip Purpose –Each Cell has a Different Friction, Found in the Corresponding Cell of the Friction Factor Matrix Enforce Constraints in Iterative Process –Sum of Trips in Row i Must Equal Origins of TAZ i –Sum of Trips in Column j Must Equal Destinations of TAZ j –Iterate Until No Adjustments Required

40 O - D Matrix Example: Destinations Sum Origins Sum T 11 T 12 T 13 T 14 T 15 T 16 O 1 T 21 T 22 T 23 T 24 T 25 T 26 O 2 T 31 T 32 T 33 T 34 T 35 T 36 O 3 T 41 T 42 T 43 T 44 T 45 T 46 O 4 T 51 T 52 T 53 T 54 T 55 T 56 O 5 T 61 T 62 T 63 T 64 T 65 T 66 O 6 D 1 D 2 D 3 D 4 D 5 D 6

41 Final O - D Matrix Combine (Add) O - D Matrices for Various Trip Purposes Scale Matrix for Peak Hour –Scale by Percent of Daily Trips Made in the Peak Hour –0.1 Often Used Scale Matrix for Vehicle Trips –Scale by Inverse of Ridership Ratio to Convert Person Trips to Vehicle Trips –0.95 to 1 Often Used Note: Other Mode Split Process / Models using Discrete Choice may be More Accurate

42 OUTPUT = the trip interchange matrix and the shortest path trees

43 Modal Split Use a model to convert trips into vehicle trips Usually public transportation versus private car Nomographs, Regression methods, Microeconomic Regression methods Stated Preference (conjoint measurement) techniques for hypothetical options Traveler objective and subjective constraints in selecting a mode

44 OUTPUT = a trip interchange matrix for each mode: car, public transportation, could also be pedestrian but not usual

45 Traffic Assignment Fourth Step in UTPS Modeling Inputs: –Peak Hour, Passenger Vehicle Origin - Destination (O - D) Matrix –Network Travel Time, Capacity, Direction Outputs: –Peak Hour Volumes, Estimated Travel Times, and Volume to Capacity Ratios

46 Roadway Performance Functions Traffic Flow and Travel Time Traffic Flow Linear RelationshipNon-Linear Relationship Route Travel Time Capacity Free-Flow Travel Time

47 Assignment Methods All or Nothing –All traffic from zone i to zone j uses the (initially) minimal travel time path –Roadway performance not used System Equilibrium –Assignment is performed such that total system travel time is minimized (UPS, Fed-EX).

48 Assignment Methods User Equilibrium –Travel time from zone i to zone j cannot be decreased by using an alternate route –Roadway performance used Stochastic User Equilibrium –Same as User Equilibrium but accounts for user variability

49 Dynamic Assignment Methods Assign Traffic by Time of Day –Estimate origins & destinations by time of day –Apply an equilibrium method –Sometimes incorporate departure time choice –Sometimes incorporate system performance characteristics See also page 288 of Meyer & Miller, 2001 textbook

50 OUTPUT = traffic volumes (cars per hour) on each road, travel times on each link, congestion levels

51 Planning 4-step Procedure Summary Land Use and Economics Trip Generation Trip Distribution Modal Split Traffic Assignment Main Input=Sociodemographics of study area Main Output=Traffic volumes and level of service on roads Secondary input-output (many depends on application and software)

52 Output from traffic assignment

53 Output from traffic assignment

54 Questions?Questions?