Incorporating Reliability Performance Measures in Operations and Planning Modeling Tools

Dr. Mahmassani is one of three principal investigators on the team led by Delcan, Inc. to undertake this project.  Northwestern’s role focuses on the theoretical and methodological underpinnings of integrated supply-demand models that incorporate reliability.  The objectives are to advance the state of the art in planning and operations models to produce measures of reliability performance of proposed system changes, and determine how travel demand forecasting models can use reliability measures to produce more realistic estimates of travel patterns.  Project L04 draws on the quantitative measures of reliability as well as the impacts of reliability on route choice, time-of-day choice, and mode choice substantiated in “Improving Our Understanding of How Highway Congestion and Pricing Affect Travel Demand, SHRP2 C04”.

This project is developing approaches and tools to incorporate reliability as an input as well a key output in traffic models used for both operations and planning applications.  A unifying framework for reliability analysis is proposed, applicable in conjunction with any particle-based micro- or meso- simulation model that produces trajectories.  Vehicle trajectories are introduced and discussed as a central building block in this framework. The methodology is demonstrated using a simulation-based DTA platform

In addition, to capture travel time variability introduced by random events, a repeatable framework is developed for modeling and evaluating incidents and events. A key variability-inducing phenomenon is traffic flow breakdown, which is modeled as an inherently stochastic phenomenon with structural dependence on state variables of the system.   Reliability-improving measures highlighted in the report include information supply and dynamic pricing, whose effectiveness increases considerably when applied in real-time on the basis of predicted conditions.

Finally, possible applications of travel time reliability in operations-oriented models are presented.