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CE 451 - Urban Transportation Planning and Modeling Iowa State University Calibration, Adjustment and Validation Sources: Calibration and Adjustment of System Planning Models Note: Date = 1990 (need to adjust for inflation, other changes) Model Validation and Reasonableness Checking Manual NHI course on Travel Demand Forecasting (152054A)
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Objectives: Identify and interpret trends affecting travel demand Explain difference between calibration and validation Identify critical reasonableness checks –socioeconomic –travel survey –network –trip generation –mode split –trip assignment
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Terminology Model Calibration –Estimate parameters –Match observations (OD, AADT) Model Validation –Reasonableness checks –Sensitivity checks Special generators Screen lines, cut lines, cordons Is the model sensitive to policy options?
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Planner responsibilities Actively involve all participants –Modelers –Planners –Decision makers –Public Fairly present all alternatives –Timely –Unbiased Identify (clearly) the decision making process –Who, when, and how –Allows input from all interested groups You must rely on the TDM –Therefore, must be validated –Accurate and easy to understand (documented) www.readysetpresent.com
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Scrutinize these characteristics: Data requirements Logic of structure and conceptual appeal Ease of calibration Effectiveness of the model (accuracy, sensitivity) Flexibility in application Types of available outputs Operational costs Experience and successes to date Public or private domain availability How do you judge a model/recommend improvement? cio.com
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Planners should monitor the following trends: –Demographics –Composition of the labor force –Immigration and emigration –Regional economic development –Modal shares –Vehicle occupancy –Average trip length –Freight transport Are trends consistent with assumptions made in the modeling process? Must be aware of trends to ensure reasonable forecasts Trends Affecting Travel Demand Image sources: scu.edu; usda.gov; illinois.edu; uwex.edu; mwcog.org; fhwa.gov; transportation1.org
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How sensitive is travel to fuel price? http://www.eia.doe.gov/oiaf/aeo/pdf/trend_4.pdf doe.gov
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Tips for building a good model* Build accurate road network Use aerial photos behind Make sure road attributes are correct, esp. traffic Use hourly counts Income and auto ownership don’t fully explain travel age, gender, life cycle and personal interest come into play Use survey data –visualize these data –Survey can be done cheaply –Cooperation will be good if there’s a good reason for it – mayor sends letter, e.g. Employer based surveys get good response (but may be biased) –Some will give home addresses, customer addresses, license plates Use trip chaining (tour based) and activity based trip generation We don’t know much about attractions – ITE sample too small – do your own Drive the network using GPS Get some data and do some statistics to derive your parameters *Howard Slavin, Caliper Corp. 3/13/04 peer review
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Tips for building a good model* Some models are completely made up except traffic counts –See if you really believe the counts Create your OD matrix from ground counts –May be better than trip gen/dist if you “made up” the whole model (no surveys) –TransCAD has a tool for this –If still want to use trip gen/dist, this method can be used to determine K factors –Could also use the row and column totals as the dependent variables in your trip gen model *Howard Slavin, Caliper Corp. 3/13/04 Examine individual links after model run –Where are the trips coming from and going to that use the link? –In TransCAD, what is the process used to determine this (for a particular link)? –In TransCAD, what is the process used to show where traffic from a particular zone is going to? Familiarity with your region is helpful
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Sources of Error Coding Sampling Computation (if done by hand) Specification Data Transfer Data aggregation Improper structure of model, e.g., wrong variables
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Not enough attention on model evaluation and reasonableness checks Checks should be performed after each step – reduces error propagation Errors can also “cancel” Key Concepts
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Reasonable? Methodology? Source? Current? Reasonable? Complete? Level of Detail? Sensitive? Documentation of calibration? Valid for base year? Evaluation and Reasonableness Checks Overview Transportation system (supply) ► Network Data Number and location of households and employment (demand) ► Socioeconomic Data TDF ► Model Specification ► Model validation and calibration Travel survey data Transportation system performance
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Model Calibration Model Validation Model Application Feedback Loop CALIBRATION and VALIDATION are sometimes confused. Model development is sometimes called calibration or estimation as we are estimating parameters and constants for the particular model structure. estimating is a statistical process … want high correlation coefficients and significant parameter values can "import" a model - or borrow structure and parameters from a "similar" area VALIDATION is checking if the model is accurately estimating traffic volumes by calculated measures (like RMSE)
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“Transportation Conformity Guidelines” (Air Quality) require model validated < 10 years ago Model Validation Validation of new model –Model applied to complete model chain –Base year model compared to observed travel –Judgment as to model suitability, return to calibration if not Validation of a previously calibrated model –Compare to a new base year, with new … SE data Special gen. Network Counts
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- Systemwide - compare traffic counts across … - Screenlines -(long lines, check major flows) check trip interchange (distribution) between large sections or quadrants -need a survey; local knowledge of commute patterns helps - Cordon lines (surround a major generator, e.g. university, CBD...) - Cutlines (shorter, verify corridor flows, fine tuning) if "importing" should validate all borrowed parameters and constants Validation suggestions
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IT IS VERY IMPORTANT TO HAVE A GOOD COUNT PROGRAM DESIGNED TO SUPPORT VALIDATION! iowadotmaps.com
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The Calibration and Adjustment manual is not intended to replace good OD data, and is intended more for small urban areas. (and has some old data in it! – more recent data area available in the Barton-Ashman publication). To "calibrate" the model, need an OD database from a survey. This is time consuming and expensive. Few, if any cities have developed OD databases since 1980, but many have updated old ones since then using a small survey (e.g. 1%)
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Calibration and Adjustment Steps: 1) verify network and socioeconomic data 2) run the model 3) develop region-wide values (e.g. trips/person, vmt/person) 4) compare region wide values with “Appendix A” values 5) develop screenlines and cutlines 6) compare model results with ground counts for crossings 7) determine problems (system level, local, combination) 8) modify one or more equations, parameters or variables according to chapters on: - networks - trip generation - auto occupancy - trip distribution - traffic assignment
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Other chapters focus on: - transit - external stations - system vs. local changes - expected vs. required accuracy - conclusions - trouble shooting
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Network Data Reasonableness Checks Check Trees for 2-3 major attractions* Check coded facility types – how used (BPR?)? Verify speed and capacity look-up table (what LOS used for capacity?)* –Speed adjust (can lower the freeway speed if it is being overloaded – tweak?) Significant transportation projects – narrative included? Still viable? Consistency with MTP Plot (facility types, # lanes, speeds, area types) to detect coding errors* * Items we can check in labs
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Details 2. Network Errors 2.1 Centroid Connectors - represent local streets - check access (all 4 sides?) - not connected to intersections - make sure they are not blocked by a physical barrier (river, etc.)
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Des Moines Model Capacity Look-up Table
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Des Moines Model Capacity Look-up Table (cont.)
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2.3 Intersection Penalties (check them!) - most congestion here - more important in sub-area modeling - turn penalties - account for congestion - speed volume function - can include delay on approach links - can do it manually for small networks -check for circuity (correct with small turn penalties!)
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-See TransCAD Manual B “Chapter 10: Traffic Assignment with Volume Dependent Turning Delays”
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2.4 Intrazonal times increasing intrazonal trips (in distribution) decreases interzonal trips (useful if too many trips are being loaded on the network) number of trips is a function of travel time (gravity model) -can adjust travel time on intrazonals -can adjust friction factor curve to produce more shorter trips (which intrazonals usually are) -can change definition of zones (size, land use) Air quality analysis implications???
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3.1 Trip generation - socioeconomic data can be a source of error - initial step is to check system trip totals, compare w/ Table 4 and A1 and A2 (next pages) - if there is a problem, check the system number of dwelling units - still a problem?, check production/attraction rates
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Trip Generation Calibration Reasonableness checks – compare to other cities, check future trends Population503,345 Households201,116 Average Household Size2.50 Basic employment76,795 (33%) Retail employment50,465 (24%) Service employment101,697 (43%) Military employment42,800 Population per employee1.81 Person trips per person4.26 Person trips per household10.65 HBW attractions per employee1.44 HBW productions per household 1.74 HB shopping attractions per retail employee 5.99 Colorado Springs 1996 Travel Demand Model Calibration
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Table A2
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From Minimum Travel Demand Model Calibration and Validation Guidelines for the State of TNMinimum Travel Demand Model Calibration and Validation Guidelines for the State of TN More recent data …
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3.2 Income - be sure you are using “real” dollars
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3.3 P and A rates Problems: old, borrowed, small survey may work OK at the system level, but not for sub-areas check system-wide values (see tables, next pages) –raise or lower trip generation rates –Person trip or vehicle trip rates used? we usually have person trip by purpose, but can apply occupancy factor and check against vehicle rates (ITE) later, screen line counts can be adjusted by varying trip generation rates (post assignment) check cutlines and cordon counts -coordinate all of the above
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home Non-
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Trip Generation Calibration Typical Values Person trips per household: 8.5 to 10.5 HBW person trips per household: 1.7 to 2.3 HBO person trips per household: 3.5 to 4.8 NHB person trips per household: 1.7 to 2.9 HBW trips: 18% to 27% of all trips HBO trips: 47% to 54% of all trips NHB trips: 22% to 31% of all trips More recent data …
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Trip Generation Reasonableness Checks Examine trip production and attraction models – Form? – sensitivity? –IMPORTANT: keep parameters reasonable (e.g. don't use negative coefficients in regression models just because they provide the best fit.) If you think you need to use unintuitive parameters, check the whole process... Check models for … –External-through and external-local trips –Truck trips To calibrate trip generation and trip distribution, sometimes we may use... –default values from past surveys –very limited new surveys –census journey to work data (CTPP)
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Scale survey for participation (relative participation) Note: each income class is a purpose! TRIP PURPOSES Scaling Factor HBW low income0.795 HBW low-middle income0.823 HBW middle income0.861 HBW upper middle income0.908 HBW high income0.936 HB elementary school0.733 HB high school1.991 HB university0.895 HB shopping0.698 HB social-recreation0.945 HB other0.875 NHB work-related0.858 NHB other0.820 Truck0.985 Internal-external0.591 Examine trip purposes used … Use more trip purposes? Colorado Springs 1996 Travel Demand Model Calibration
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Travel Survey Data Reasonableness Checks Determine source of travel survey data –Types of survey conducted –Year of survey Scale survey for participation If no survey (borrowed) –Check source of trip rates, lengths, TLFD –Is area similar Geographic area? pop/HH/empl. characteristics? Urban density and trans system? Compare to similar regions and to same region in earlier times: –Person trip rates by trip purpose –Mean trip lengths by trip purpose HBW longest? HBO shortest? –TLFDs by trip purpose
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Socioeconomic Data: Check Reasonableness Review source for estimates and forecasts Visualize (plot) trends … –Population and household size –Household income –automotive availability –distribution of employment by type (basic, retail, service) –employees per household and per capita … rate of increase is decreasing Check future household and employment changes by zone
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3.4 Special generators -e.g. universities, airports, malls,... -Use ITE or survey
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3.5 trip balancing factors 4.0 Auto occupancy initially, Ps and As should balance to should be 0.9 to 1.1; if not, check your PA rates and socioeconomic data NHB is usually out of balance Automobile occupancy –by trip purpose? –Basis? –Constant? see table 6 and A9 (next pages … are these still good?)
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5.0 Trip Distribution 5.1 Mean Trip Length - recall: shape of curve affects trip length distribution -See below for effect of changing friction factors
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-varying trip length has a big impact on assigned volumes -portions of a friction factor table can be adjusted (more flexible than adjusting equations)
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5.2 Estimate Trip Length -compare average trip lengths (in minutes) by purpose to: HBWt = 0.98 x p.19 HBSRt = 2.18 x p.12 HBSht = 8.1 NHBt = 0.63 x p.20 where p is population SR = social/recreation Sh = shopping
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From Minimum Travel Demand Model Calibration and Validation Guidelines for the State of TNMinimum Travel Demand Model Calibration and Validation Guidelines for the State of TN
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Source: Virginia Travel Demand Modeling Policies and Procedures ManualVirginia Travel Demand Modeling Policies and Procedures Manual
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Source: Virginia Travel Demand Modeling Policies and Procedures ManualVirginia Travel Demand Modeling Policies and Procedures Manual
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Source: Virginia Travel Demand Modeling Policies and Procedures ManualVirginia Travel Demand Modeling Policies and Procedures Manual
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5.3 Employment Distribution Problems (large cities, mostly) problem: match low income households with low income jobs solution #1: disaggregate trip purposes by income quartile solution #2: use k-factors (trial and error) … yuk Jobs/Housing Imbalance!
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5.4 Special Treatment, other trip purposes - schools (ignore if small %?) - trucks (calibrate with externals?) -Taxi normally, distortions are insignificant
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Trip Distribution Reasonableness Checks Examine … Mean trip length (increasing or decreasing?) TLFDs Treatment of friction factors (same?) Treatment of terminal times (logic?) Treatment of K factors Comparison with JTW trip length Comparison with JTW sector interchange volumes or percentages.
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Calibrate friction factors 1 st iteration Calibrating Friction Factors
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Travel Times Ranges from Skims Observed Trip Expanded from Surveys Input Friction Factors Gravity Model Trips Adjustment Factor Observed Gravity Model New Friction Factors Friction Adjustment Factor x Friction Factor 2.57,10030.08,2000.8725.98 5.014,9502.5016,3000.922.29 7.517,8501.8019,2500.931.67 10.016,0001.5019,1000.841.26 12.515,5001.2017,1000.911.09 15.015,9001.0012,3001.291.29 17.516,4000.9518,0000.910.87 20.015,1500.9014,3001.060.95 22.513,5000.8511,9001.130.96 25.011,0000.809,2501.190.95 27.59,5000.758,1001.170.88 30.09,1000.706,1001.491.04 32.55,7000.654,9001.160.76 ……………… Calibrating a Gravity Model Adjusting Friction Factors
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2 nd iteration
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Commute Length in Minutes PercentJourney-to-WorkFlowsPercent < 15 27.87Central-CentralCounty31.49 15-2941.63Central-SuburbanCounty7.48 30-3917.04 Suburban-Central County 15.13 40-597.70 Within Suburban County 32.98 >603.00 To Other Suburban County 10.81 Mean 21.44 Work out of area 2.11 Trip Distribution Calibration and Validation Check modeled vs. household survey TLFD and mean trip lengths Get HBW area-to-area flows from JTW HBW 1990 JTW TLFD and Area-to-Area Flows for Kansas City
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Using cell phone and/or GPS location to determine travel patterns is nothing new. But leave it to Google to make it really easy - maybe too easy. http://googleblog.blogspot.com/2009/08/bright-side-of-sitting-in-traffic.html Adam Shell Office of Systems Planning Iowa Department of Transportation Link OD data are destroyed! (privacy) POA: price of anarchy (30%?) Nash equilibrium vs. system optimality OD validation
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6.0 Traffic assignment 6.1 All or nothing - adjusting link speeds will change assigned volumes - initial speeds should be set to LOS C speeds (0.87 x free flow speeds)
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6.2 capacity restraint - volume = f(time) - final volume is average of all iterations or later iterations can be weighted more heavily - adjust free flow time or c (capacity) to change volumes IF… THEN… Link Speed Travel Assigned CapacityTimeVolume
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6.2.1 definition of capacity design: LOS C (0.87c) ultimate: LOS E (1.00c) parameters differ depending on definition of capacity … if defined as LOS C, 0.15(v/c) 4 if defined as LOS E, 0.80(v/c) 4 (see HCM)
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6.3.2 free speeds in systems with good progression should be coded at about 1.1 times the speed limit time - more than 10 iterations may be needed for small areas 6.3 equilibrium - multiple paths may be selected
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7.0 Transit Ridership - for small/medium cities, may not have to build a transit network - If not using a transit network, can use the following method (if trip generation includes transit trips): 1. increase auto occupancy by transit percentage (e.g. if auto occupancy is 1.05, then change to 1.05 x 1.38 = 1.45) if transit percentage is 38% 2. decrease trip production or attraction rates (one of them only, then balance) … if you use productions, can vary mode split by income class 3. modify productions or attractions by zone - get data from transit company - adjust socioeconomic data or make direct P/A adjustments
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Mode Split Reasonableness Checks Mode split model? Form? Variables included in the utility functions? Coefficients logical? Value of time assumptions Parking cost assumptions How do mode shares change over time? Mode share comparisons with other cities http://www.bts.gov/publicati ons/journal_of_transportation _and_statistics/volume_08_n umber_02/html/paper_05/fig ure_05_03.html
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Experienced planning consultant required … –Form of LOGIT model –Variables included in utility functions –Calibration of coefficients for utility function variables –Testing for IIA properties –Analysis of household survey data –Analysis of on-board transit survey data Calibration tasks we can do: Compare highway and transit trips Total By purpose Compare Ridership by route CBD cordon line survey (if bus service is downtown only) Mode Split Calibration and Validation
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8. External stations - externals have no socioeconomic data - Ps and As are prepared by matching ground counts - I/E treated with the gravity model -E/E - compare with Table 11 below
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9.System vs. local checks check1. system wide (screenlines) 2. major movements (cutlines) 3. links if all screenlines are high or low, vary - auto occupancy - trip generation rates - trip lengths - intrazonal times - all zones - socioeconomic data - all zones if corridor volumes are high or low, vary (for zones affecting corridor…) - auto occupancy - trip generation rates - intrazonal travel times - land use - centroid connectors - intersection penalties if links are high/low, vary - speed - intersection penalty - centroid locations - special generators - local network configuration
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10. Expected/Required accuracy We are concerned about errors that would require a design change (e.g. number of lanes) Note that ground counts also contain error Perfectly calibrated models produce link estimates with 1/3 above the standard error in ground counts and 2/3 below the standard error. Need ground counts for 65% of freeways and arterials, and a good sample from other facilities From Minimum Travel Demand Model Calibration and Validation Guidelines for the State of TNMinimum Travel Demand Model Calibration and Validation Guidelines for the State of TN
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10. Expected/Required accuracy (cont.) The correlation coefficient should be greater than.88 VMT estimate (region-wide) should be within 5% (take care to compare same roads in systems) VMT/person should be 17-24 for large areas, 10-16 for smaller areas (see also Table A7, next page) VMT/household should be 40-60 for large areas, 30-40 for smaller areas
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From CTRE Employment Data Project:
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From Minimum Travel Demand Model Calibration and Validation Guidelines for the State of TNMinimum Travel Demand Model Calibration and Validation Guidelines for the State of TN
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Source: Virginia Travel Demand Modeling Policies and Procedures ManualVirginia Travel Demand Modeling Policies and Procedures Manual
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From Minimum Travel Demand Model Calibration and Validation Guidelines for the State of TNMinimum Travel Demand Model Calibration and Validation Guidelines for the State of TN
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From Minimum Travel Demand Model Calibration and Validation Guidelines for the State of TNMinimum Travel Demand Model Calibration and Validation Guidelines for the State of TN
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Source: Virginia Travel Demand Modeling Policies and Procedures ManualVirginia Travel Demand Modeling Policies and Procedures Manual
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From Minimum Travel Demand Model Calibration and Validation Guidelines for the State of TNMinimum Travel Demand Model Calibration and Validation Guidelines for the State of TN
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All-or-nothing assignment study effect of increasing capacity Compare to Equilibrium assignment Check volume delay equation (BPR parameters) Compare screen line volumes Cut line volumes Time-of-day assignments? Source of factors Peak spreading used for future? If not, conversion factors source? (peak hour to 24-hour) Local VMT (% assigned to intrazonals and centroid connectors All or Nothing Equil ibrium Trip Assignment Reasonableness Checks
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Assignment calibration performed last Trip Assignment Calibration and Validation Overall VMT or VHT check 40 to 60 miles per day per HH in large metro areas 30 to 40 miles per day per HH in medium metro +/- 10% OK on screen lines Sign is important
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Compute by … - volume group - facility type - transit assignments - time of day
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12. TROUBLE SHOOTING
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Other Factors Impacting Forecasted Travel Demand Can be implied in travel surveys (but not explicit) –Telecommuting –Flexible work hours –HB business How to account for … –Aging population –Internet shopping –Roadway congestion (will it affect generation in the future) –New modes
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Issues for modeling Transferability of parameters –More research is needed Forensic analysis –How well did the models work? Confidence and Credibility –How to improve “Official” versions vs. what-if models –Integrity of the model Need more transparency, documentation, appropriateness of techniques
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