Graph-Based Modeling, Scheduling, and Verification for Intersection Management of Intelligent Vehicles

Abstract

Intersection management is one of the most representative applications of intelligent vehicles with connected and autonomous functions. The connectivity provides environmental information that a single vehicle cannot sense, and the autonomy supports precise vehicular control that a human driver cannot achieve. Intersection management solves the fundamental conflict resolution problem for vehicles—two vehicles should not appear at the same location at the same time, and, if they intend to do that, an order should be decided to optimize certain objectives such as the traffic throughput or smoothness. In this paper, we first propose a graph-based model for intersection management. The model is general and applicable to different granularities of intersections and other conflicting scenarios. We then derive formal verification approaches which can guarantee deadlock-freeness. Based on the graph-based model and the verification approaches, we develop a centralized cycle removal algorithm for the graph-based model to schedule vehicles to go through the intersection safely (without collisions) and efficiently without deadlocks. Experimental results demonstrate the expressiveness of the proposed model and the effectiveness and efficiency of the proposed algorithm.