1 / 40

Toward a Consistent and Robust Integrated Multi-Resolution Modeling Approach for Traffic Analysis

Toward a Consistent and Robust Integrated Multi-Resolution Modeling Approach for Traffic Analysis. Jeff Shelton, TTI Yi-Chang Chiu, Univ. of Arizona TRB – Transportation Planning Conference Houston, TX. May 17-21, 2009. Outline. Introduction Mesoscopic Microscopic

ollie
Download Presentation

Toward a Consistent and Robust Integrated Multi-Resolution Modeling Approach for Traffic Analysis

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Toward a Consistent and Robust Integrated Multi-Resolution Modeling Approach for Traffic Analysis Jeff Shelton, TTI Yi-Chang Chiu, Univ. of Arizona TRB – Transportation Planning Conference Houston, TX May 17-21, 2009

  2. Outline • Introduction • Mesoscopic • Microscopic • Multi-Resolution Modeling • Concept • Conversion Process • Modeling Issues • Case Study • Applications

  3. Outline • Introduction • Mesoscopic • Microscopic • Multi-Resolution Modeling • Concept • Conversion Process • Modeling Issues • Case Study • Applications

  4. Introduction • Integrating mesoscopic dynamic traffic assignment (DTA) and microscopic traffic simulation and assignment models can be advantageous for region-wide operational planning projects • DTA – region-wide estimation of traffic redistribution • Microscopic – local operational analysis • The integration synergizes the strengths of both models. • Challenges remain in model translation and interface • Modeling issues to be addressed • Consistency • Situation in which feedback is needed

  5. Simulation-Based Dynamic Traffic Assignment (SBDTA) • Address issues that may fall beyond the reach of both: • Microscopic models: (dynamic but small-scale) typically used by traffic engineers for project traffic studies • Macroscopic models: (large-scale but static) typically used by transportation planners for long-range planning • SBDTA – dynamic and large-scale • The scenarios of interest may result in shifts of network or corridor-wide traffic flow patterns. • Significant change to roadway configuration • Certain corridor management strategies

  6. Mesoscopic Dynamic Traffic Assignment • DynusT v2.0 • Free version available for DYNASMART-P users • Dynamic simulation and assignment tool for regional operational planning analysis • Equilibrium-based Dynamic Traffic Assignment • Assigned paths are based on experienced (actual) travel time • Applications • Assess impacts of ITS technologies • Work zone planning and traffic management • Evaluate HOV/HOT lanes • Congestion pricing • Special event/emergency evacuation

  7. Microscopic • VISSIM 5.1 • A driver-behavior-based simulation tool capable of performing multiple applications including • Analyzing complex intersections • Border crossings inspection booths • Managed lanes • University campus settings • Fined-grained analysis • Vehicle interactions • Individual lane analysis • Simulate multiple modes of transportation simultaneously 3-D graphics

  8. Outline • Introduction • Mesoscopic • Microscopic • Multi-Resolution Modeling • Concept • Conversion Process • Modeling Issues • Case Study • Applications

  9. Concept • What is multi-resolution modeling? • Integrating mesoscopic and microscopic models for the purpose of achieving a specific goal • Analyze network at both the system-wide and localized levels • Why is multi-resolution modeling so important? • Mesoscopic & microscopic models are not mutually exclusive • They are complimentary to one another and can accomplish optimal modeling capabilities. • Retain the best characteristics of both • Realistic representation of regional traffic • Detailed interactions

  10. Mesoscopic Model Sub-area Cut Concept Model Conversion Process Microscopic Model Integration Tool

  11. Concept DynusT Sub-Area VISUM VISSIM

  12. Multi-Resolution Modeling Framework Field Data Regional Travel Demand Model Initial Network Conversion (DynusT) • Calibration • Speed Profile • OD • Traffic Model Sub-Area Cut DVC VISSIM Calibration Yes Rerun DTA Detailed Analysis Network Modification No

  13. DTA Model Preparation • Convert the GIS layer of the Travel Demand Model to Mesoscopic format. • Disaggregate 24-hour matrix based upon car & truck • Home to work • Work to home • Home to private • Private to home • Thru • External Local • Non-home based external local • Multiply each matrix by corresponding hourly factor

  14. DTA Model Preparation Multiply each matrix by hourly factor H-W W-H H-P P-H THRU EXLO NHBEXLO Summation of matrices gives you directional 1-hour matrix

  15. DTA Model Preparation 24 - one hour matrices

  16. Calibration • Traffic flow model • Traffic simulation in DynusT is based upon the Anisotropic Mesoscopic Simulation (AMS) model • Moves vehicles based upon speed-density (v-k) relationship • v-k relationship is derived from Greenshields equation

  17. Calibration Traffic Network Traffic Flow Model Intersection Controls Estimated Time-Dependent OD Matrices • Time-Dependent OD • Minimize the deviation between simulated and actual screen line counts & speed profile • Iterative process • Program solves linearized quadratic minimization problem • Results in updated OD matrices Traffic Assignment/ Simulation Assignment Results Update Demand Linear Optimization Model Results Optimized Affected, Time-Dependent OD Pairs

  18. Conversion Process • Sub-area cut • Remove unneeded sections of network • Renumbering of new zones, nodes and links • Retains paths and flows that travel through the sub-area

  19. Conversion Process • DynusT-VISSIM Converter • Developed by researchers from TTI and UA • Converts roadway network to VISUM network • Retains network geometry • Converts all time-dependent paths and flows • Creates separate transportation systems (car, truck)

  20. Conversion Process • Microscopic model • Calibrate VISSIM model to reflect realistic roadway conditions • Perform detailed “fine-grained” analyses • Speed profile for individual lanes • Lane-changing behaviors • Vehicle interactions at merge areas • Create 3-D graphics for presentations

  21. Modeling Issues • Consistency • Network • Lane configuration • Geometric design • Paths and flow • Verify same origin/destination paths • Verify number of vehicles generated • Speed profile • Perform field data collection to determine speed and vehicle counts • Obtain v-k curve from simulation output • Calibrate models with field data

  22. Modeling Issues Speed (mph) Density (veh/mi)

  23. Modeling Issues Field Data Regional Travel Demand Model Initial Network Conversion (DynusT) • Calibration • Speed Profile • OD • Traffic Model Sub-Area Cut DVC VISSIM Calibration Yes Rerun DTA Detailed Analysis Network Modification No When Feedback is Necessary

  24. Outline • Introduction • Mesoscopic • Microscopic • Multi-Resolution Modeling • Concept • Conversion Process • Modeling Issues • Case Study • Applications

  25. Case Study Model entire 22-mile corridor Freeway grade affects truck acceleration City Council proposes ordinance to restrict trucks from using left lane on I-10 corridor Analyze during peak hour traffic Use separate truck demand How does the ordinance affect the freeway and surrounding arterials?

  26. Case Study Which type of model do I use? Microscopic Macroscopic Mesoscopic

  27. Case Study • Truck restricted lanes • A case study to analyze the effectiveness of restricting trucks from left-most fast lane on freeway • 22-mile corridor of I-10 in El Paso, TX • Analyze a.m. peak, p.m. peak, & mid-day • Determine benefits • Speed on left-most lane • Acceleration/Deceleration patterns • Vehicle interactions at merge areas • DynusT estimates region-wide truck trajectories (route and flows) • VISSIM models detailed IH-10 truck lane operations given truck trajectories

  28. Model Development 106 Origin/Destination links - 1895 Routes created

  29. Model Development GPS unit was used to input freeway grading information

  30. Model Development Field data collection-freeway speed profile (PM peak hour)

  31. Model Development Data provided by TxDOT Automatic Traffic Recorder Stations

  32. Model Development

  33. Case Study Speed Accel/Decel

  34. Case Study Speed Accel/Decel

  35. Case Study Speed – Left vs. Right Lane

  36. Outline • Introduction • Mesoscopic • Microscopic • Multi-Resolution Modeling • Concept • Conversion Process • Modeling Issues • Case Study • Applications

  37. Applications • Managed lanes • Truck restricted lanes • HOV lanes • HOT lanes • Time-dependent variable pricing

  38. Applications • Geometric design alternatives • Freeway direct connect • Various design configurations • Ramp reconfiguration • Braided ramps • “X” ramps

  39. Applications • Traffic impact studies • New retail shopping centers • Driveways • Pedestrian crossings • University campus planning • Integrating various modes of transportation (e.g. student, faculty, staff, pedestrians, transit) • New parking facilities • Campus core closure • Traffic calming

  40. Questions ?

More Related