SHRP2 Project C05: Final Report to TCC Understanding the Contribution of Operations, Technology, and Design to Meeting Highway Capacity Needs Wayne Kittelson.

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Presentation transcript:

SHRP2 Project C05: Final Report to TCC Understanding the Contribution of Operations, Technology, and Design to Meeting Highway Capacity Needs Wayne Kittelson & Brandon Nevers TCC Meeting at The Beckman Center April 26, 2010

Presentation Overview Project Scope, Objectives, and Timeline Key Findings Key Products Response to TCC Feedback of Spring 2009 Schedule for Completion

Project Scope and Objectives Quantify capacity benefits of improvements at the network level Provide information and tools to analyze operational improvements as an alternative to traditional construction Develop guidelines for “sustainable service rates” to be used in planning networks

Project Timeline

FreewayArterialBoth HOV LanesSignal RetimingNarrow Lanes Ramp MeteringSignal CoordinationReversible Lanes Ramp ClosuresAdaptive SignalsVariable Lanes Congestion PricingQueue ManagementTruck Only Lanes Pricing by DistanceRaised MediansTruck Restrictions HOT LanesAccess PointsPre-Trip Information Weaving SectionRight/Left Turn Channelization In-Vehicle Info Frontage RoadAlt LT TreatmentsVMS/DMS Interchange Modifications Non-Lane Widening Strategies to Improve Capacity

Insights on Strategy Effectiveness Effectiveness needs to be tested in network context –Requires the use of a travel demand/DTA model –Cannot be done with static look-up tables Impacts most pronounced at the link and corridor levels, and often difficult to see at the network level –Demand-side issues are best viewed from an O-D perspective –Supply-side issues are best viewed at the link and corridor level Pre-trip information can reduce buffer time –En-route information may create instabilities

Key Products Traffic Model Enhancements Diagnostic Tools Strategy Evaluation Results Spreadsheet-Based Model Final Report Guidebook

Traffic Model Enhancements: Stochastic Capacity for Freeway Bottlenecks

Traffic Model Enhancements: Stochastic Capacity for Arterials

Traffic Model Enhancements: Day-to-Day Traveler Learning Traveler’s route choice is based on experiences remembered from the past two weeks Limits applied to number of travelers who will adjust their trip each day Expected to be important in the evaluation of non- recurring congestion

Traffic Model Enhancements: Improved Bottleneck Representation Merges Short Turn Pockets

Diagnostic Tools: Active Bottleneck Identification

Diagnostic Tools: Movement-Specific Intersection Delay Display

Diagnostic Tools: Stochastic Link Performance and Breakdown Probability Visual representation currently being developed Breakdown probabilities estimated from recorded simulated experience

Overview of Strategy Testing Plan Testing plan developed for 25 strategies –Location within the DFW network –Geometric, volume, and operational inputs –Selection of performance evaluation MOE’s Test Protocol –I: Baseline stabilization –II: Strategy stabilization –III: 20-day results comparison period IIIIII

Strategy Evaluation Results: Equivalent Capacity Gain Concept

Baseline # of Lanes 1.9 miles 0.9 miles 5.7 miles Lane-Mile Addition +7.6 (+22%) 8.5 miles miles 0.9 miles 5.7 miles +8.5 (+24%) (+46%) 8.5 miles 6 ABC 17 Capacity Addition Scenarios (Southbound Freeway Corridor)

20-Day Average Results 18 * Effects in peak direction with lane addition for one hour * 95 th percentile TT 5 th percentile TT

20-Day Average Results 19

20-Day Average Results 20

21 Primary OD: 1→2 (Southbound) Freeway # Zone Number 1 2 Spreadsheet Application: Network Simplification is Required

Spreadsheet Application: Uses Simplified Travel Time Profiles 22 D: Good day on freeway E: Bad day on freeway A: Arterial street (we do not have randomized capacity on arterial street yet)

Spreadsheet Application: Results Are First Approximation 100 random scenarios (i.e. days) using calibrated stochastic capacity model from C05 Deterministic demand Two corridors –Route A: 2 lanes, free-flow travel time: 20 min –Route B: 3 lanes, free-flow travel time: 40 min 23

Response to TCC Feedback (Spring 2009) Validation on a bona fide network will increase comfort and add credibility Ability to model nonrecurrent congestion will make the tool substantially more useful to users and decision- makers

Portland Network: C05 Subarea Boundary

Portland Network Statistics Entire NetworkSubarea Network Traffic Analysis Zones2, Nodes9, Links22,7481,999 Vehicles1.2 M212 K Average Travel Time22 min14 min Demand Horizon: 4 hours (15:00-19:00)

Application Notes DTA modeling enhancements have been coded into two separate DTA models –Dynasmart-P v. 1.2(E) –DTA Lite Method: –Calibrate the entire network using DTA Lite –Apply DSP to the smaller subarea Current status: –DTA Lite network calibration is complete –DSP has recreated subarea base condition results –Diagnosis and evaluation of treatment options underway

Portland Subarea: Identified Active Bottlenecks

Adding Non-Recurrent Congestion Capability Develop strategy to represent effects of nonrecurring congestion Produce necessary software code Apply enhanced model to Portland network Summarize/document findings

1. Executive Summary 2. Introduction 3. Improved Methods for Modeling Network Performance –Measurement and Modeling of Network Performance –Uninterrupted Flow Facilities –Interrupted Flow Facilities 4. Strategies for Enhancing Sustainable Service Rate on Freeways and Arterials 5. Prototype Application of Methods, Metrics, and Strategies Final Report Outline

Schedule for Completion Portland NetworkMay 15 Draft Final ReportJune 30 Draft GuidebookJune 30 Project CompletionSeptember 30