STIP: Spatio-temporal intersection protocols for autonomous vehicles

Autonomous driving is likely to be the heart of urban transportation in the future. Autonomous vehicles have the potential to increase the safety of passengers and also to make road trips shorter and more enjoyable. As the first steps toward these goals, many car manufacturers are investing in designing and equipping their vehicles with advanced driver-assist systems. Road intersections are considered to be serious bottlenecks of urban transportation, as more than 44% of all reported crashes in U.S. occur within intersection areas which in turn lead to 8,500 fatalities and approximately 1 million injuries every year. Furthermore, the impact of road intersections on traffic delays leads to enormous waste of human and natural resources. In this paper, we therefore focus on intersection management in Intelligent Transportation Systems (ITS) research. In the future, when dealing with autonomous vehicles, it is critical to address safety and throughput concerns that arise from autonomous driving through intersections and roundabouts. Our goal is to provide vehicles with a safe and efficient passage method through intersections and roundabouts. We have been investigating vehicle-to-vehicle (V2V) communications as a part of co-operative driving in the context of autonomous driving. We have designed and developed efficient and reliable intersection protocols to avoid vehicle collisions at intersections and increase traffic throughput. In this paper, we introduce new V2V intersection protocols to achieve the above goals. We show that, in addition to intersections, these protocols are also applicable to vehicle crossings at roundabouts. Additionally, we study the effects of position inaccuracy of commonly-used GPS devices on some of our V2V intersection protocols and suggest required modifications to guarantee their safety and efficiency despite these impairments. Our simulation results show that we are able to avoid collisions and also increase the throughput of the interse- tions up to 87.82% compared to common traffic-light signalized intersections.