Transcript Slide 1
DynusT (Dynamic Urban Systems in Transportation) Recent Projects IH corridor improvement (North Carolina, 2003-present) IH tolling and congestion pricing (ELP, TX2003-present) IH work zone planning (ELP, TX-2004) Evacuation operational Planning (HOU, TX, 2007, Baltimore, MD, 2005, Knoxville, TN, 2003) Downtown improvement (ELP, TX, 2004) ICM AMS modeling (Bay Area, CA, 2006present) On-going Efforts Military deployment transportation improvement in Guam (PB, FHWA) Interstate highway corridor improvement (TTI, TxDOT, ELP MPO) Value pricing (ORNL, FHWA; SRF, Mn/DOT, TTI, TxDOT) Evacuation operational planning (UA, ADOT; LSU, LDOT; Noblis, FHWA; Univ. of Toronto) Integrated Corridor Management modeling (CS, FHWA) Bay area regional modeling (CS, MTC) Florida turnpike system traffic and evacuation analysis (FDOT Turnpike) What DynusT Represents? Regional Operational Planning Capability Regional - area larger than corridor Operational - traffic flow dynamics sensitive to signals, road configurations Planning - short-term impact and long-term equilibrium Enabled by Mesoscopic Traffic Simulation Dynamic Traffic Assignment (DTA) Micro-meso-micro integration What is Mesoscopic Traffic Simulation? Not as detailed as microscopic models, but is as capable of high-fidelity traffic simulation of an entire region What is Dynamic Traffic Assignment? A method to predict/estimate how trip-makers may shift to other routes or departure time in response to: Congestion Pricing Controls Incidents Improvements Understand how individual travel decisions impact an entire region, by Time of day Origin-Destination (OD) zones Transportation modes How Trip-makers Adapt to Congestion Macro-Meso-Micro Integration Macro Meso Micro Proposed toll lanes Analyze Ingress/Egress points for weaving Estimate toll lane usage and revenue Macro-Meso-Micro Integration Macro Travel Demand Models (TDM) Micro e.g. VISSIM Visualizing the Model’s Results - An Example Applying toll on 495 ramp may improve traffic on both 495W and 95S I-95S AM commuting traffic impacted by spillback from 495W A “What-if” Pricing Scheme Variable toll on I-95 S to I-495 W ramp Toll increases with congestion level Morning peak period (5AM - 11AM) Value of Time: $10/hour Pricing LOV 89% HOV 11% Distance based tolls: $0.25 /mile $2 for through traffic Peak-period tolls: 7AM - 9AM Dimensions of impacts Departure time Route Both Peak Spreading Due to Value Pricing Change of departure time due to pricing Base Case 12000 Peak Spreading 10000 8000 6000 4000 2000 Tim e 10:30 10:00 9:30 9:00 8:30 8:00 7:30 7:00 6:30 6:00 5:30 0 5:00 # of Vehicles Generated A Regional View (DynusT Animation) A Closer View (VISSIM animation) Addressing Diversion Tolling may cause diversion on alternative routes and/or other transportation modes Turnkey solution package needed to improve the capacity to which the traffic may be diverted Signal optimization, information provision, transit operation, peak spreading A Low-Hanging Fruit Strategy – Optimize Signal Other Freeway Operations Scenarios/Strategies Dynamic message signs Information strategies Congestion warning Mandatory detour Speed advisory Pre-trip information In-vehicle information Incident Work zone Managed lanes Truck only Truck restriction Resource Considerations Initial TDM import and conversion 100+ Data collection and model calibration 300+ hrs Scenario analysis and reporting 400+ hrs hrs Total man-hours 800+ Budget 1,000 - 1,500 hours; including learning How to Get Started Capacity building Training workshop – agency and consultants Establish baseline and future datasets Allow 12-18 months with sufficient budget Will be a valuable asset for many future applications Save $$$ for agency in the long-run Lesson learned from Minneapolis collapse Plan ahead and get the model built We are ready to act when needs arise