Author Index to Volume 18

Abstract:   Route guidance system (RGS) is considered as a low-cost alternative for reducing congestion by providing real-time information to drivers to redistribute traffic in space and time so as to use roadway networks more efficiently. This article focuses on the behavioral component, one of the three components (the other two being dynamic traffic component and information supply strategy component) of a practical RGS developed through a 4-year project at the University of Delaware. Development of the behavioral model is based on the premise that different drivers perceive and behave differently in response to the information provided. Understanding the behavior of RGS-equipped drivers' acceptance or nonacceptance of provided information is essential for understanding the reliability of the system. Backpropagation neural network with its ability to map complex input–output relationships has been used to structure the model. This model was tested on two networks under both recurring and nonrecurring congestion. A comparative analysis of the measures of effectiveness revealed that the performance of the developed RGS is significantly better than the performance under existing non-RGS conditions.