Deadlock detection, cooperative avoidance and recovery protocol for mixed autonomous vehicles in unstructured environment

Abstract

Abstract Deadlock is an extreme traffic flow operational state during rush hours. Many literatures have studied autonomous vehicle coordination under the umbrella of deadlock‐free conditions. These researches either assume the trajectories are fixed or state spaces are discrete and limited on structured road spaces or don't consider the influence of human‐driven vehicles (HDV), which are not controllable from the system's viewpoint. This manuscript relaxes the above limitations and proposes a method to detect, avoid, and recover from deadlock for mixed autonomous vehicles flow. Firstly, two types of deadlocks, weak and strong , are defined based on deadlock properties. Next, two detection algorithms based on evasion distance propagation are proposed. After that, we present a cooperative control method to avoid deadlock based on chain‐spillover‐free and loop‐free strategies. If a deadlock has already happened, cooperative protocols based on re‐routing and backward‐forward strategies are designed. The proposed model is tested in Carla. The results show that the deadlocks can be detected 13 seconds earlier than their occurrence, and it takes about 6 seconds to unlock the existing deadlock. The results also show that with the proposed deadlock avoidance algorithm, the traffic throughput can be increased by 35.7%, and with the proposed deadlock recovery protocol, the traffic throughput can be increased by another 18%.

Keywords

• connected and automated vehicle
• cooperative driving
• deadlock