Batch-Light: An adaptive intelligent intersection control policy for autonomous vehicles

The existing intelligent intersection management solutions try to leverage global positioning, wireless communications, in-vehicle sensing and computation technologies to enable autonomous vehicles to drive through the non-signal urban intersections safely and efficiently. Control policy as the brain of the whole system has a direct impact on system performance. This paper proposes a reservation-based control policy called Batch-Light which can make full use of existing Intelligent Transportation System (ITS) technologies to make the management system adaptive to constantly changing traffic. A greedy-based Conflict Matrix decision algorithm is proposed to get more vehicles reserve successfully on the premise of ensuring certain fairness. Furthermore, a k-Shift optimization algorithm is proposed to help some unlucky vehicles to pass through the intersection as much as possible by acceleration or deceleration. Our experiment results show that Batch-Light outperforms FCFS and traditional traffic signal control policy both in unbalanced traffic and balanced traffic.