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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
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Transportation Operations Group Outline Introduction – Mesoscopic – Microscopic Multi-Resolution Modeling – Concept – Conversion Process – Modeling Issues Case Study Applications
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Transportation Operations Group Outline Introduction – Mesoscopic – Microscopic Multi-Resolution Modeling – Concept – Conversion Process – Modeling Issues Case Study Applications
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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
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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
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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
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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
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Transportation Operations Group Outline Introduction – Mesoscopic – Microscopic Multi-Resolution Modeling – Concept – Conversion Process – Modeling Issues Case Study Applications
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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
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Transportation Operations Group Concept Mesoscopic Model Sub-area Cut Model Conversion Process Integration Tool Microscopic Model
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Transportation Operations Group Concept DynusTVISSIMVISUM Sub- Area
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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
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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
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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
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Transportation Operations Group DTA Model Preparation 24 - one hour matrices
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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
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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
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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
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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)
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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
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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
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Transportation Operations Group Modeling Issues Density (veh/mi) Speed (mph)
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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
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Transportation Operations Group Outline Introduction – Mesoscopic – Microscopic Multi-Resolution Modeling – Concept – Conversion Process – Modeling Issues Case Study Applications
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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?
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Transportation Operations Group Case Study Which type of model do I use? Macroscopic Mesoscopic Microscopic
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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
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Transportation Operations Group Model Development 106 Origin/Destination links - 1895 Routes created
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Transportation Operations Group Model Development GPS unit was used to input freeway grading information
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Transportation Operations Group Model Development Field data collection-freeway speed profile (PM peak hour)
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Transportation Operations Group Model Development Data provided by TxDOT Automatic Traffic Recorder Stations
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Transportation Operations Group Model Development
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Transportation Operations Group Case Study SpeedAccel/Decel
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Transportation Operations Group Case Study SpeedAccel/Decel
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Transportation Operations Group Case Study Speed – Left vs. Right Lane
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Transportation Operations Group Outline Introduction – Mesoscopic – Microscopic Multi-Resolution Modeling – Concept – Conversion Process – Modeling Issues Case Study Applications
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Transportation Operations Group Applications Managed lanes – Truck restricted lanes – HOV lanes – HOT lanes – Time-dependent variable pricing
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Transportation Operations Group Applications Geometric design alternatives – Freeway direct connect » Various design configurations – Ramp reconfiguration » Braided ramps » “X” ramps
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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
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Transportation Operations Group Questions ?
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