HazSim: An Urban Driving Simulator for Testing Perception Systems of ADSes Against Hazards
Perception systems play a crucial role in ensuring the safety of autonomous vehicles. In intricate scenarios of self-driving technology, these vehicles need to effectively handle a range of natural hazards, including heavy rainfall or the presence of raindrops on camera lenses. Consequently, it is imperative to thoroughly evaluate the robustness of perception systems in autonomous vehicles against hazards, aligned with the stringent testing requirements set by regulatory bodies in many nations for conventional drivers.
Authors
- Yulong Shen (ORCID: https://orcid.org/0000-0002-8448-705X)
- Xiaodong Zhang (ORCID: https://orcid.org/0000-0002-8380-1019)
- Qin Xia
- Zhicheng Yang
- Jie Bao
Institutions
- Xidian University (CN)
- National Synchrotron Radiation Laboratory (CN)
- Xi'an Jiaotong University (CN)
Publication Details
- Published
- 2025-06-23
- DOI
- https://doi.org/10.1145/3696630.3728589
- Primary Topic
- Software Testing and Debugging Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China