Roadside Infrastructure Support for Urban Automated Driving

Abstract

Automated driving offers excellent opportunities for ecology, economy as well as society. Especially in urban intersections, there is a considerable margin for benefits in these sectors. This work takes a structured simulation approach to find answers on the benefit of additional information about surrounding objects of automated vehicles provided by roadside ITS stations to utilize collective perception. We are using advanced sub-microscopic 3D hardware in the loop simulation framework to generate data based on which we can achieve reliable conclusions. Our simulation data set, consisting of 400 simulation iterations, suggests that automated vehicles greatly benefit from collective perception. A lack of roadside ITS station support might lead to a disruptive impact of automated vehicles on the macroscopic traffic flow of urban road networks. If roadside collective perception is introduced to the problem, maneuver time is reduced, and traffic efficiency is increased by 19.8% on average.