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Travel Modeling 101

Travel Modeling 101. Opening the Black Box. The Four Steps. Transportation Networks. Transportation Supply. Traffic Analysis Zone and Data. Transportation Demand. How many trips?. Trip Generation. Where will they go?. Trip Distribution. What mode?. Mode Choice. Feedback. What route?.

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Travel Modeling 101

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Presentation Transcript

  1. Travel Modeling 101

  2. Opening the Black Box

  3. The Four Steps Transportation Networks Transportation Supply Traffic Analysis Zone and Data Transportation Demand How many trips? Trip Generation Where will they go? Trip Distribution What mode? Mode Choice Feedback What route? Trip Assignment Roadway / Transit Results Reports

  4. Model Inputs and Outputs Inputs Outputs Trips by Mode Transportation Networks Traffic Volumes Socioeconomic Data Congested Speeds External Data Transit Volumes Special Generators Bike / Ped Volumes Model Parameters Summary Information

  5. Model Inputs and Outputs Inputs • Roadway Networks • Contains roadway characteristics • Speed Limit • Number of Lanes • Roadway Type (Freeway, arterial, etc.) • Area Type (CBD, Urban, Suburban, Rural) Transportation Networks Socioeconomic Data External Data Special Generators Model Parameters

  6. Model Inputs and Outputs Inputs • Transit networks • Route locations • Service frequency • Park and rides • Non-motorized networks • Bike/Ped facilities • Based on the roadway network (sidewalk availability) • Also includes off-street paths Transportation Networks Socioeconomic Data External Data Special Generators Model Parameters

  7. Model Inputs and Outputs Inputs • Identifies demand for travel • Household data • Required: • Total Housholds • Optional: • Average household size • Median household income • Employment data • By Type • Retail • Service • Basic/Industrial • Optional: • Education • Health Care • Leisure/Recreation Transportation Networks Socioeconomic Data External Data Special Generators Model Parameters

  8. Model Inputs and Outputs Inputs • Identify travel to/from the region • Identify travel through the region • Based on data from MDT Transportation Networks Socioeconomic Data External Data Special Generators Model Parameters

  9. Model Inputs and Outputs Inputs • Unique locations • Not well represented by employment data • University of Montanna • Generate trips based on faculty, staff, and enrollment • Allocate trip-ends based on address data Transportation Networks Socioeconomic Data External Data Special Generators Model Parameters

  10. Model Inputs and Outputs Inputs • Represent the way people behave • How many trips are made? • How far will people travel? • What impacts decisions about travel mode? • How does congestion impact travel? • Source Data Required • Mostly borrowed from other areas • Local data wherever possible • Calibrated & validated to counts Transportation Networks Socioeconomic Data External Data Special Generators Model Parameters

  11. Model Inputs and Outputs Outputs • Information about each trip • Start/end • Time of day • Mode of travel • Purpose of trip • Trip time and distance Trips by Mode Traffic Volumes Congested Speeds Transit Volumes Bike / Ped Volumes Summary Information

  12. Model Inputs and Outputs Outputs • By Time of Day • Daily • AM & PM Peak Hour (less accuracy) • Turn Movements • Can be estimated with assistance of base-year counts • Congested speed based on volume Trips by Mode Traffic Volumes Congested Speeds Transit Volumes Bike / Ped Volumes Summary Information

  13. Model Inputs and Outputs Outputs • Transit • By Time of Day • Peak and Off-Peak • Daily sum • By route or route group • Route-level data is less accurate • Bike / Pedestrian • Short trip demand is the best tool for bike and pedestrian planning Trips by Mode Traffic Volumes Congested Speeds Transit Volumes Bike / Ped Volumes Summary Information

  14. Model Inputs and Outputs Outputs • Performance Report • Detailed summary of model results • Useful for planners and engineers • Planning Tools • Maps and charts • Results presented for easy understanding • VMT, VHT, Delay • Level of Service • Trip Lengths • Trip Patterns Trips by Mode Traffic Volumes Congested Speeds Transit Volumes Bike / Ped Volumes Summary Information

  15. Model Inputs and Outputs • The model is not a “Crystal Ball” • The model is a tool that can aid in the decision making process • Evaluate results with a bit of skepticism • The model is a way oforganizing your assumptions

  16. Summary: Model Run Data Needs • Roadway Improvement • Complete Project Description • Project Extents • New Configuration details • lanes, speed limit, bike/ped facilities, facility type • Land Use / Development Scenario • Number of Units • Households, employment (or square footage) • Access Details • Where will the development take access to the roadway system • Traffic Studies • ITE-based traffic studies are helpful in evaluating a project

  17. Missoula MPO Travel Demand Model Enhancement Example Model Output

  18. Model Inputs and Outputs • The model can estimate level of service to help identify problem areas.

  19. Household And Employment Growth Today

  20. Household And Employment Growth Future

  21. Travel Patterns Today

  22. Travel Patterns Future

  23. 2010 Roadway Level of Service • PM Peak Hour Conditions • Uncongested • Congesting • Congested • Thicker lines indicate highervolume DRAFT

  24. Traffic Difference • Example: Madison Street Bridge Closure • Traffic decrease • Traffic Increase DRAFT

  25. Select Link/ZoneAnalysis • Track vehicles that use a link • Example: traffic using the Madison Street bridge • Track trips to and from a particular zone DRAFT

  26. Transit Activity Map • Home-end stop activity • Non-home stop activity • Transfers • Transit Ridership • Directional from home to work/school DRAFT Note: UM routes are shown at a smaller scale

  27. Short Trips • Gauge potential bicycle facility demand • 3-6 mile trips • 1-3 mile trips • 0-1 mile trips(different scale) DRAFT DRAFT

  28. Traffic Difference • Example: Madison Street Bridge Closure • Traffic decrease • Traffic Increase Diverted Volumes shown in thousands DRAFT

  29. Bringing the Model Up to Date Model Steps

  30. Trip Generation How Many Trips? • Keep track of more trip purposes • Better locate trips • Use population & income details • Track university trips • Include all trips • Walk, • Bike, • Transit, • Auto, • …

  31. Trip Distribution The Gravity concept can be used to model travel! Where Will They Go? • Match trips from home to • Work, Shopping, Appointments, School, Recreation, etc… • Match trips between • Work , shop, appointment, etc. • Calibrate a gravity modelbased on local data

  32. Mode Choice Can I get a ride? Is it close enough to bike? How much $ is parking? How about the bus? What Mode? • This will be a new model component! • Choose between: • Drive, • Carpool, • Walk, • Bicycle, • Transit

  33. Mode Choice What Route? • Find the best route from A to B • Avoid congestion • Especially in the peaktravel times • Use Equilibrium (capacity constrained) assignment

  34. Testing the Model Model Validation

  35. Matching Counts • How does the model work for today • Statistics • R-Squared • % RMSE • Volume / Count Ratio • Etc… • Screenlines • Corridor Review • Highest Errors

  36. Testing Sensitivity • Dynamic Validation • Observe how the model reacts changes • Test big and small changes • Test the base and forecast year • Do results make sense?

  37. Don’t Do Missoula MPO Travel Demand Model Enhancement Travel Model & ’S ’S

  38. Testing Demand Changes Don’t Do • Evaluate base, interim, and forecast year datasets • Consider testing large development proposals(e.g., over 200 households or employees) • Use the model’s trip distribution to compare to traffic study assumptions • Cross-check development model runs with ITE-based traffic studies • Use the model to test very small developments • Test unreasonable changes to the jobs/housing balance

  39. Testing Roadway Changes Don’t Do • D • Test large and medium-scale capacity changes • Test different roadway alternatives • Test a comprehensive roadway plan • consider forecast conditions • Test scenarios that do not impact system capacity • Try to model very small capacity or speed changes

  40. Non-motorized Results Don’t Do • Focus on potential non-motorized demand • E.g., 1, 3, and 6 mile trip bandwidths • Identify good places for infrastructure improvements • Consider non-motorized model results to be a rough estimate • The model is only one tool to aid in analysis • Expect detailed numbers • YES: “There is a high demand for a new bike lane in this corridor” • NO: “This new bike lane will result in X new bike trips”

  41. Transit Results Don’t Do • Evaluate major system adjustments • Test large route changes • Focus on a system-wide results • Test fine tuning of route alignments • Expect detailed forecasts by transit route or transit stop • This information is available, but must be interpreted carefully by a transit professional

  42. Thank You!

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