Intersection crossing with reduced number of conflicts

Paper in proceeding, 2018

In this paper, an optimization based algorithm for safe and efficient collaborative driving in intersections is formulated. The problem is to determine the optimal order in which vehicles should travel through an intersection under the assumptions that the longitudinal velocity of all vehicles can be controlled along a predefined path. In the original formulation one quadratic optimization program was solved for each possible crossing order of the vehicles and collisions were avoided by formulating constraints that only allowed one vehicle at the time inside the intersection. To make this algorithm more effective, we formulate less restrictive collision avoidance constraints by introducing one critical zone for each point where two predefined paths cross. It is shown that this formulation leads to a decrease in the number of quadratic optimization programs that need to be solved to find the best crossing order. Further, an algorithm is provided that finds the number of crossing sequences which yield unique formulations of the optimization program. The results show that when simulating more complex scenarios, like four vehicles traveling through an ordinary intersection, the reduction of computational time and the total time it takes for all vehicles to make it through the intersection can be significantly reduced using these less restrictive constraints.