论文标题
Lawbreaker：指定交通法和模糊自动驾驶汽车的方法
LawBreaker: An Approach for Specifying Traffic Laws and Fuzzing Autonomous Vehicles
论文作者
论文摘要
在将自动驾驶系统（ADS）进行分部之前，必须对其进行彻底测试。高保真模拟器允许对各种情况进行测试，包括在现实世界测试场上难以重现的情况。虽然先前的方法表明可以自动生成测试案例，但它们倾向于将重点放在弱小的甲骨文（例如，在没有碰撞的情况下到达目的地）而无需评估旅程本身是否安全并满足法律。在这项工作中，我们提出了Lawbreaker，这是一个针对现实世界流量法的自动化框架，该框架旨在与不同的方案描述语言兼容。 Lawbreaker提供了一种以驾驶员为导向的规范语言，用于描述交通法律，以及一个模糊的引擎，通过最大化规范覆盖范围来寻找不同的方式来违反它们。为了评估我们的方法，我们为Apollo+LGSVL实施了它，并指定了中国的交通法律。 Lawbreaker能够发现14个违反这些法律的行为，其中包括173例导致事故的测试案件。
Autonomous driving systems (ADSs) must be tested thoroughly before they can be deployed in autonomous vehicles. High-fidelity simulators allow them to be tested against diverse scenarios, including those that are difficult to recreate in real-world testing grounds. While previous approaches have shown that test cases can be generated automatically, they tend to focus on weak oracles (e.g. reaching the destination without collisions) without assessing whether the journey itself was undertaken safely and satisfied the law. In this work, we propose LawBreaker, an automated framework for testing ADSs against real-world traffic laws, which is designed to be compatible with different scenario description languages. LawBreaker provides a rich driver-oriented specification language for describing traffic laws, and a fuzzing engine that searches for different ways of violating them by maximising specification coverage. To evaluate our approach, we implemented it for Apollo+LGSVL and specified the traffic laws of China. LawBreaker was able to find 14 violations of these laws, including 173 test cases that caused accidents.
