MODEL-BASED LONG-RANGE TRANSPORTATION PLANNING TOOL FOR NEW JERSEY

Document Type

Journal Article

Publication Date

2002

Subject Area

operations - traffic, infrastructure - vehicle, planning - travel demand management, planning - travel demand management, land use - planning, ridership - forecasting, ridership - forecasting, ridership - demand, ridership - growth, policy - congestion, organisation - management, technology - intelligent transport systems, mode - subway/metro

Keywords

TSM, Trip reduction, Travel models (Travel demand), Travel demand management, Travel demand, Transportation systems management, Transportation system management, Transportation planning, Transportation demand management, Traffic congestion, TDM measures, Supply, Strategies, Strategic planning, Scenarios, RTI, Road transport informatics, Projections, Priorities, Population growth, Objectives, New Jersey, Multimodal transportation, Multimodal systems, Mobility, Metropolitan planning organizations, Mathematical models, Long range planning, IVHS, ITS (Intelligent transportation systems), Investments, Investment requirements, Intelligent vehicle highway systems, Intelligent transportation systems, Improvements, Gridlock (Traffic), Goals, Funding, Forecasting, Financing, Financial analysis, Employment, Demand, ATT, Advanced transport telematics

Abstract

The New Jersey Department of Transportation (NJDOT) updates its long-range transportation plan every 5 years. The plan sets forth strategies, provides a framework for directing investment, and identifies financial resources needed to sustain the plan's vision. Setting the direction of a long-range transportation program revolves around forecasting future transportation conditions and managing investments to address future needs. An analysis tool was needed to help assess the impact of growth on the statewide transportation system and predict system performance based on multimodal strategic investments. The development and use of an analysis tool based on a travel demand model to assess congestion and mobility issues in 2025 are described. The analysis tool linked the state's three metropolitan planning organization (MPO) regional travel demand models to perform a statewide assessment. Although the models were run independently, methods were developed to provide a common basis for forecasting future travel conditions. The models used MPO-generated trend-based growth in population and employment through 2025. Multimodal transportation supply and demand strategies, including transit improvements, capacity improvements, transportation demand management strategies, and intelligent transportation systems-transportation system management strategies, were simulated and tested to assess what types and combinations of improvements would be needed to relieve congestion and improve mobility. The tool proved very helpful in defining transportation needs and providing input to a financial assessment. The testing indicated that no single strategy is likely to improve future travel conditions, but a combination of multimodal strategies offers significant improvements over congestion levels predicted for 2025 if no improvements are made.

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