Autonomous Detection and Anticipation of Jam Fronts from Messages Propagated by Intervehicle Communication

Abstract

A minimalist, completely distributed freeway traffic information system is introduced. It involves autonomous, vehicle-based jam-front detection, information transmission via intervehicle communication, and forecast of the spatial position of jam fronts by reconstructing the spatiotemporal traffic situation on the basis of the transmitted information. The whole system is simulated with an integrated traffic simulator, which is based on a realistic microscopic traffic model for longitudinal movements and lane changes. The function of its communication module has been explicitly validated by comparing the simulation results with analytical calculations. By means of simulations, it is shown that the algorithms for congestion-front recognition, message transmission, and processing reliably predict the existence and position of jam fronts for vehicle equipment rates as low as 3%. A reliable mode of operation for small market penetrations is crucial for successful introduction of intervehicle communication. The short-term prediction of jam fronts is not only useful for the driver but also essential for enhancing road safety and road capacity by intelligent adaptive cruise control systems.