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

Transportation Operations Group Outline  Introduction – Mesoscopic – Microscopic  Multi-Resolution Modeling – Concept – Conversion Process – Modeling Issues  Case Study  Applications

Transportation Operations Group Outline  Introduction – Mesoscopic – Microscopic  Multi-Resolution Modeling – Concept – Conversion Process – Modeling Issues  Case Study  Applications

Transportation Operations Group 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

Transportation Operations Group 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

Transportation Operations Group 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

Transportation Operations Group 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

Transportation Operations Group Outline  Introduction – Mesoscopic – Microscopic  Multi-Resolution Modeling – Concept – Conversion Process – Modeling Issues  Case Study  Applications

Transportation Operations Group 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

Transportation Operations Group Concept Mesoscopic Model Sub-area Cut Model Conversion Process Integration Tool Microscopic Model

Transportation Operations Group Concept DynusTVISSIMVISUM Sub- Area

Transportation Operations Group Multi-Resolution Modeling Framework Regional Travel Demand Model Initial Network Conversion (DynusT) Calibration Speed Profile OD Traffic Model Sub-Area CutDVC VISSIM Calibration Network Modification Field Data Rerun DTA Detailed Analysis No Yes

Transportation Operations Group 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

Transportation Operations Group DTA Model Preparation H-WW-HH-PP-HTHRUEXLONHBEXLO Multiply each matrix by hourly factor Summation of matrices gives you directional 1-hour matrix

Transportation Operations Group DTA Model Preparation 24 - one hour matrices

Transportation Operations Group 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

Transportation Operations Group Calibration  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 Network Traffic Flow Model Intersection Controls Estimated Time- Dependent OD Matrices Traffic Assignment/ Simulation Linear Optimization Model Optimized Affected, Time-Dependent OD Pairs Results Update Demand Assignment Results

Transportation Operations Group 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

Transportation Operations Group 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)

Transportation Operations Group 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

Transportation Operations Group 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

Transportation Operations Group Modeling Issues Density (veh/mi) Speed (mph)

Transportation Operations Group Modeling Issues When Feedback is Necessary Rerun DTA Regional Travel Demand Model Initial Network Conversion (DynusT) Calibration Speed Profile OD Traffic Model Sub-Area CutDVC VISSIM Calibration Network Modification Field Data Detailed Analysis No Yes

Transportation Operations Group Outline  Introduction – Mesoscopic – Microscopic  Multi-Resolution Modeling – Concept – Conversion Process – Modeling Issues  Case Study  Applications

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

Transportation Operations Group Case Study Which type of model do I use? Macroscopic Mesoscopic Microscopic

Transportation Operations Group 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

Transportation Operations Group Model Development 106 Origin/Destination links Routes created

Transportation Operations Group Model Development GPS unit was used to input freeway grading information

Transportation Operations Group Model Development Field data collection-freeway speed profile (PM peak hour)

Transportation Operations Group Model Development Data provided by TxDOT Automatic Traffic Recorder Stations

Transportation Operations Group Model Development

Transportation Operations Group Case Study SpeedAccel/Decel

Transportation Operations Group Case Study SpeedAccel/Decel

Transportation Operations Group Case Study Speed – Left vs. Right Lane

Transportation Operations Group Outline  Introduction – Mesoscopic – Microscopic  Multi-Resolution Modeling – Concept – Conversion Process – Modeling Issues  Case Study  Applications

Transportation Operations Group Applications  Managed lanes – Truck restricted lanes – HOV lanes – HOT lanes – Time-dependent variable pricing

Transportation Operations Group Applications  Geometric design alternatives – Freeway direct connect » Various design configurations – Ramp reconfiguration » Braided ramps » “X” ramps

Transportation Operations Group 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

Transportation Operations Group Questions ?