一句话：从非确定性的系统级场景测试中抽取规划模块的确定性单元测试，消除复现的不稳定性。
自动驾驶系统（ADS）中规划模块历来是缺陷最多的模块之一。基于仿真的系统级场景测试虽能暴露规划决策问题，但由于 ADS 实时执行时事件的随机性，测试结果往往不一致、具有 flaky 与不可预测性，难以稳定复现失败。本文提出并评估 DeFT：它在系统级场景测试执行期间监控 ADS 各模块间交换的消息，据此重构规划模块的输入，从而复现规划模块的执行并从中抽取确定性测试用例。评估表明：由 DeFT 得到的规划模块测试能更准确地复现系统级场景测试中发生的规划执行；能确定性地检测出系统级场景测试所揭示的同一批 658 个碰撞失败；并将复现失败所需时间减少 43.69% 至 77.64%。
An Autonomous Driving System (ADS) is a complex software system often composed of multiple modules, each responsible for its own set of tasks. The ADS planning module is responsible for planning the autonomous vehicle’s future driving trajectories and has historically been the most buggy ADS module. In recent years, many approaches have been proposed to test an ADS in complex virtual scenarios through simulation, and these scenarios have been effective in revealing the ADS’s suboptimal decisions. However, due to the randomness of events that occur during the real-time execution of an ADS, test scenarios tend to produce varying outcomes and, in turn, make ADS testing non-deterministic, flaky, and unpredictable. To address this challenge, we propose and evaluate DeFT, an approach that extracts deterministic test cases for the ADS planning module from non-deterministic system-level scenario tests. DeFT monitors the messages exchanged by ADS modules during the execution of system-level scenario tests and reconstructs inputs to reproduce the planning module’s execution. By using DeFT, we find that planning module tests can (1) more accurately reproduce planning module executions that occurred during system-level scenario tests, (2) be used to deterministically detect the same 658 collision failures revealed by system-level scenario tests, and (3) reduce the time needed to reproduce failures by 43.69% to 77.64%.
@inproceedings{paperbot11519,
title = {DeFT: Maintaining Determinism and Extracting Unit Tests for Autonomous Driving Planning},
author = {Yuqi Huai and Yuntianyi Chen and Ziwen Wan and Qi Alfred Chen and Joshua Garcia},
booktitle = {ICSE},
year = {2026},
doi = {10.1145/3744916.3773252}
}