Toward a Consistent and Robust Integrated MultiResolution Modeling

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 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 § Dynus. T v 2. 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 Conversion Process Integration Tool Microscopic Model Transportation Operations Group

Concept Dynus. T Sub. Area VISUM VISSIM Transportation Operations Group

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

DTA Model Preparation 24 - one hour matrices Transportation Operations Group

Calibration § Traffic flow model – Traffic simulation in Dynus. T 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 – 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 Estimated Time. Dependent OD Matrices Traffic Assignment/ Simulation Assignment Results Linear Optimization Model Update Demand § Time-Dependent OD Traffic Network Traffic Flow Model Intersection Controls Results Optimized Affected, Time-Dependent OD Pairs 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 § Dynus. T-VISSIM Converter – Developed by researchers from TTI and UA – Converts roadway network to VISUM network – Retains network geometry – Converts all timedependent 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 “finegrained” 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 40 35 30 Speed (mph) 25 Observed 20 Calibrated 15 10 5 0 0 20 40 60 80 100 120 140 160 Density (veh/mi) Transportation Operations Group

Modeling Issues Field Data Regional Travel Demand Model Initial Network Conversion (Dynus. T) Calibration • Speed Profile • OD • Traffic Model Sub-Area Cut Yes Detailed Analysis No DVC VISSIM Calibration Rerun DTA Network Modification When Feedback is Necessary 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 How does the ordinance affect the freeway and surrounding arterials? Transportation Operations Group

Case Study Which type of model do I use? 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 – Dynus. T 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 - 1895 Transportation Routes created 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 Tx. DOT Automatic Traffic. Transportation Recorder. Operations Stations Group

Model Development Transportation Operations Group

Case Study Speed Accel/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 ? Transportation Operations Group