STCLocker：面向自动驾驶系统的死锁避免测试
STCLocker: Deadlock Avoidance Testing for Autonomous Driving Systems
AI总结：
针对多车协同场景下的死锁问题，提出时空冲突引导的死锁避免测试技术STCLocker，通过黑盒检测与冲突感知生成机制，有效生成死锁场景并优于现有基线方法。
摘要：
自动驾驶系统（ADS）测试对于确保自动驾驶车辆（AVs）在部署前的安全性和可靠性至关重要。然而，现有技术主要侧重于在单车环境下评估ADS的功能。随着ADS日益广泛地部署于多车交通场景中，评估其协同性能变得尤为关键，特别是在死锁方面。死锁是一种基本的协调失败，即多辆AVs无限期进入循环等待状态，导致运动规划失败。尽管死锁问题十分重要，但ADS在预防死锁方面的协同能力仍未得到充分探索。为弥补这一空白，我们提出了首个专用的时空冲突引导死锁避免测试技术STCLocker，用于生成死锁场景（DLSs），在此场景中，受测ADS控制的一组AVs处于循环等待状态。STCLocker包含三个关键组件：Deadlock Oracle、Conflict Feedback和Conflict-aware Scenario Generation。Deadlock Oracle提供了一种可靠的黑盒机制，用于在给定场景中检测多辆AVs之间的死锁循环。Conflict Feedback和Conflict-aware Scenario Generation协同工作，主动引导AVs在空间冲突资源（即共享通行区域）上展开同时竞争，并产生时间上的竞争行为（即在同一时间到达冲突区域），从而提高生成易冲突死锁的有效性。我们在两类ADS上对STCLocker进行了评估：端到端ADS Roach，以及支持协同通信的模块化ADS OpenCDA。实验结果表明，平均而言，STCLocker生成的DLS数量多于表现最佳的基线方法。
英文摘要：
Autonomous Driving System (ADS) testing is essential to ensure the safety and reliability of autonomous vehicles (AVs) before deployment. However, existing techniques primarily focus on evaluating ADS functionalities in single-AV settings. As ADSs are increasingly deployed in multi-AV traffic, it becomes crucial to assess their cooperative performance, particularly regarding deadlocks, a fundamental coordination failure in which multiple AVs enter a circular waiting state indefinitely, resulting in motion planning failures. Despite its importance, the cooperative capability of ADSs to prevent deadlocks remains insufficiently underexplored. To address this gap, we propose the first dedicated Spatio-Temporal Conflict-Guided Deadlock Avoidance Testing technique, STCLocker, for generating DeadLock Scenarios (DLSs), where a group of AVs controlled by the ADS under test are in a circular wait state. STCLocker consists of three key components: Deadlock Oracle, Conflict Feedback, and Conflict-aware Scenario Generation. Deadlock Oracle provides a reliable black-box mechanism for detecting deadlock cycles among multiple AVs within a given scenario. Conflict Feedback and Conflict-aware Scenario Generation collaborate to actively guide AVs into simultaneous competition over spatial conflict resources (i.e., shared passing regions) and temporal competitive behaviors (i.e., reaching the conflict region at the same time), thereby increasing the effectiveness of generating conflict-prone deadlocks. We evaluate STCLocker on two types of ADSs: Roach, an end-to-end ADS, and OpenCDA, a module-based ADS supporting cooperative communication. Experimental results show that, on average, STCLocker generates more DLS than the best-performing baseline.
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