Predictive longitudinal vehicle control based on vehicle-to-infrastructure communication

Abstract

Governments, industries and last but not least customer's demand for low-pollutant, efficient and comfortable vehicles has extended the system development scope towards the combination of in-vehicle systems and environment. Whereas the information from the on-board systems is available for several functions per se, the environmental information has to be grabbed using sensors and/or communication devices. Optimizing fuel efficiency whilst offering a high driving comfort is the goal of the predictive cruise control functionality. An assistance function for intersections is presented within this paper. Traffic signal data is used to automatically adjust the optimal vehicle velocity during urban drive cycles through passages with intersections. The target is to avoid unnecessary acceleration and braking maneuvers which results in reduced fuel consumption. In combination with the adaptive cruise control function a full takeover of the longitudinal vehicle control is realized. Communication between vehicle and traffic lights is done using a wireless vehicle-to-infrastructure communication technique. The presented work describes the developed algorithm `Predictive Cruise Control - Intersection Assist' such as the coupled simulation environment for the examination of the function performance. The later one involves vehicle, driver, traffic lights and wireless transmission. The effect of varying communication ranges is considered using a probability distribution function. Within the study several scenarios with and without traffic were analyzed and evaluated. As a result the fuel efficiency of the implemented assistance function is confirmed. Furthermore a trip time reduction could be achieved in most of the scenarios.