An Adaptive Approach for the Coordination of Autonomous Vehicles at Intersections

Our streets will be soon populated by multitudes of autonomous (i.e., self-driving) vehicles, calling for appropriate solutions to coordinate their collective movements in order to ensure safety and efficiency. In particular, crossing intersections can be based on a number of different coordination approaches, from traditional ones (e.g., traffic lights) to innovative ones (e.g., based on dynamic negotiations between vehicles). In this paper, after having introduced the general issues associated to intersection management in the presence of autonomous vehicles, we show by simulation experiments that no single approach exhibits the best behaviour for all traffic conditions and for all performance indicators. On this basis, we introduce an adaptation mechanism that enables an intersection to dynamically select the most proper coordination approach depending on traffic conditions and the performance indicator to be optimized. Simulation experiments show the effectiveness of such adaptive approach.