ISSTA 2024
Mon 16 - Fri 20 September 2024 Vienna, Austria
co-located with ISSTA/ECOOP 2024
Fri 20 Sep 2024 13:30 - 13:50 at EI 3 Sahulka - Safety-Critical Systems Chair(s): Lingming Zhang

As highlighted in authoritative standards (e.g., ISO21448), traffic law compliance is a fundamental prerequisite for the commercialization of autonomous driving systems (ADS). Hence, manufacturers are in severe need of techniques to detect harsh driving situations in which the target ADS would violate traffic laws. To achieve this goal, existing works commonly resort to searching-based simulation testing, which continuously adjusts the scenario configurations (e.g., add new vehicles) of initial simulation scenarios and hunts for critical scenarios. Specifically, they apply pre-defined heuristics on each mutated scenario to approximate the likelihood of triggering ADS traffic violations, and accordingly perform searching scheduling. However, with those comparably more critical scenarios in hand, they fail to offer deterministic guidance on which and how scenario configurations should be further mutated to reliably trigger the target ADS misbehaviors. Hence, they inevitably suffer from meaningless efforts to traverse the huge scenario search space.

In this work, we propose VioHawk, a novel simulation-based fuzzer that hunts for scenarios that imply ADS traffic violations. Our key idea is that, traffic law regulations can be formally modeled as hazardous/non-hazardous driving areas on the map at each timestamp during ADS simulation testing (e.g., when the traffic light is red, the intersection is marked as hazardous areas). Following this idea, VioHawk works by inducing the autonomous vehicle to drive into the law-specified hazardous areas with deterministic mutation operations. We evaluated the effectiveness of VioHawk in testing industry-grade ADS (i.e., Apollo). We constructed a benchmark dataset that contains 42 ADS violation scenarios against real-world traffic laws. Compared to existing tools, VioHawk can reproduce 3.1X~13.3X more violations within the same time budget, and save 1.6X~8.9X the reproduction time for those identified violations. Finally, with the help of VioHawk, we identified 9+8 previously unknown violations of real-world traffic laws on Apollo 7.0/8.0.

Fri 20 Sep

Displayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change

13:30 - 14:50
Safety-Critical SystemsTechnical Papers at EI 3 Sahulka
Chair(s): Lingming Zhang University of Illinois Urbana-Champaign
13:30
20m
Talk
VioHawk: Detecting Traffic Violations of Autonomous Driving Systems through Criticality-guided Simulation Testing
Technical Papers
Zhongrui Li Fudan University, Jiarun Dai Fudan University, Zongan Huang Fudan University, Nianhao You Fudan University, Yuan Zhang Fudan University, Min Yang Fudan University
13:50
20m
Talk
Exploration-Driven Reinforcement Learning for Avionic System Fault Detection (Experience Paper)
Technical Papers
14:10
20m
Talk
DiaVio: LLM-Empowered Diagnosis of Safety Violations in ADS Simulation Testing
Technical Papers
You Lu Fudan University, Yifan Tian Fudan University, Yuyang Bi Fudan University, Bihuan Chen Fudan University, Xin Peng Fudan University
DOI
14:30
20m
Talk
CooTest: An Automated Testing Approach for V2X Communication Systems
Technical Papers
An Guo Nanjing University, Xinyu Gao , Zhenyu Chen Nanjing University, Yuan Xiao Nanjing University, Jiakai Liu Nanjing University, Xiuting Ge Nanjing University, Weisong Sun Nanjing University, Chunrong Fang Nanjing University
Pre-print

Information for Participants
Fri 20 Sep 2024 13:30 - 14:50 at EI 3 Sahulka - Safety-Critical Systems Chair(s): Lingming Zhang
Info for room EI 3 Sahulka:

Map: https://tuw-maps.tuwien.ac.at/?q=CF0205

Room tech: https://raumkatalog.tiss.tuwien.ac.at/room/15663