Incorporating Reliability Performance Measures in Operations and Planning Modeling Tools

Recent research evidence (see Special Note 1) suggests that travel time reliability is an element of a traveler’s choice of departure time, route, mode, and perhaps, whether to travel at all. This implies that traffic conditions influence the demand for and nature of travel. Furthermore, as demand changes, travel conditions, including volumes, change on the network. While as travelers we know this to be true from our experience, traditional methods used to assign traffic to links of the network or forecast travel demand cannot cope with this degree of complexity. In order to make traffic patterns and travel demand forecasting sensitive to traffic conditions, there is a need to develop the underlying relationships between travel time reliability and travel demand and to upgrade analysis and forecasting tools accordingly. A new generation of models and computer analysis offers the potential, but the techniques have yet to be developed. In this Request for Proposals, models that use historical or static data to forecast one or more dimensions of travel are “planning models.” Models applied to real time data in order to manage current conditions on the network are “traffic operations models.” Simulation models are often categorized into three types: micro-simulation, meso-simulation, and macro-simulation. Micro- and meso-simulation are of most concern here. In micro-simulation, the physical characteristics of vehicles, kinematics of motion, and models of driver behavior are used to move each vehicle in very small increments of time (e.g. second by second). However, ultimately the focus should be on the movement of people, not just vehicles, in order to link the simulation results back to the demand models. Dynamic traffic assignment (DTA) is a type of meso-simulation that can address time varying (dynamic) features of networks but DTA also includes aggregate relationships, such as speed, density, and flow to simplify computation. There are distinct versions of DTA for planning and operations management. The category of travel demand forecasting models includes traditional four-step approaches, discrete choice models, and activity-based approaches. Activity-based models may also include simulation. A fusion is in progress as some approaches to travel demand forecasting are incorporating traffic operations approaches and some traffic operations techniques have demand forecasting capability. There is also extensive on-going work to develop feedback between traffic conditions on the network and travel demand. The emphasis in Project L04 is on improving traffic operations and planning models to reflect travel time reliability and generate travel time reliability as a model output. Phases I and II focus on incorporating travel time reliability in such models. Phase III considers ways to account for the feedback between travel demand and traffic conditions on the network, such as traffic impedances including the variability of travel time. Extensive research and operational testing is underway by many parties on these topics, including related projects in SHRP 2. See Special Note 2. The objectives of this project are to (1) develop the capability of producing measures of reliability performance as output in traffic simulation models and planning models, and (2) determine how travel demand forecasting models can use reliability measures to produce revised estimates of travel patterns.

Language

  • English

Project

  • Status: Completed
  • Funding: $1248880.00
  • Contract Numbers:

    Project L04

  • Sponsor Organizations:

    Strategic Highway Research Program 2

    Transportation Research Board
    500 Fifth Street, NW
    Washington, DC    20001
  • Project Managers:

    Hyman, William

  • Performing Organizations:

    Delcan International Corporation

    133 Wynford Drive
    North York, M3C 1K1,    
  • Principal Investigators:

    Stogias, Yannis

  • Start Date: 20090206
  • Expected Completion Date: 0
  • Actual Completion Date: 20131031
  • Source Data: RiP Project 15538

Subject/Index Terms

Filing Info

  • Accession Number: 01462725
  • Record Type: Research project
  • Source Agency: Transportation Research Board
  • Contract Numbers: Project L04
  • Files: TRB, RiP
  • Created Date: Jan 3 2013 2:09PM