Static network equilibrium models and analyses for the design of dynamic route guidance systems

This study considers issues related to the design and deployment of a Dynamic Route Guidance System (DRGS), a technology satisfying the operational characteristics of an Advanced Traveler Information System. Such a system is intended to provide dynamic traffic information and routing instructions to operators of vehicles in the system's geographical area. The analyses presented seek to provide DRGS designers with information regarding the impact of design decisions and the effects of these decisions on the operating characteristics of system components. Moreover, they provide a basis for anticipating problems and identifying relationships between the system and its users which require further study.;Aggregate network performance measures are determined from model applications to a highway network representing the test area roadway system for ADVANCE, a DRGS demonstration project currently being designed in a suburban location northwest of Chicago, Illinois. Results indicate a decrease in total travel time as high as nine percent for a fully deployed system. Average travel times are found to decrease for both guided and unguided travelers. A DRGS designed to minimize total system travel time was shown to provide greater benefits than one designed to minimize individual travel times. Relationships between market share and coverage of the highway network allows vehicle requirements and frequency of probe traffic reports to be estimated.;This research establishes a foundation for further study in network equilibrium models with multiple classes and with link interactions. The work on stochastic equilibrium may be extended to consider new distributions of traveler's perception errors as sophisticated data collection methods improve our survey capability.;The methodology used in this study is a comparative analysis of design issues studied in the framework of mathematical programming. Two modeling approaches are presented. The first involves formulation of a route choice model which considers two classes of travelers, guided and unguided, each with a different capability of perceiving network travel time. The second procedure infers information regarding traveler choices from a conventional static user-optimal route choice model and uses that information to evaluate important design considerations.