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任睿晗 等: 面向整车系统的自动驾驶安全测试研究综述 175

References
[1] Kilgore T. Baidu debuts Robotaxi ride hailing service in China, using self-driving electric taxis. 2019. https://www.marketwatch.com/
story/baidu-debuts-robotaxi-ride-hailing-service-in-china-using-self-driving-electric-taxis-2019-09-26
[2] Version 2024: Intelligent automotive solution 2030. 2021. https://www-file.huawei.com/-/media/corp2020/pdf/giv/2024/intelligent_
automotive_solution_whitepaper_2030_en.pdf
[3] McFarland M. Uber self-driving car kills pedestrian in first fatal autonomous crash. 2018. https://money.cnn.com/2018/03/19/technology/
uber-autonomous-car-fatal-crash/index.html
[4] Warrier M. Nio ES8 accident rekindles concerns over safety with smart EVs in China. 2021. https://www.benzinga.com/government/21/
08/22504236/nio-es8-accident-rekindles-concerns-over-safety-with-smart-evs-in-china
[5] ISO. ISO 21448. Road vehicles—Safety of the intended functionality. 2022. https://cdn.standards.iteh.ai/samples/77490/d9843a45e11947
e0aa79aaf2f00b65a8/ISO-21448-2022.pdf
[6] ISO. ISO 26262-1. Road vehicles—Functional safety—Part 1: Vocabulary. 2018. https://cdn.standards.iteh.ai/samples/68383/4e26ddadc
54a4198bed652afe29669fa/ISO-26262-1-2018.pdf
[7] Eykholt K, Evtimov I, Fernandes E, Li B, Rahmati A, Xiao CW, Prakash A, Kohno T, Song D. Robust physical-world attacks on deep
learning visual classification. In: Proc. of the 2018 IEEE/CVF Conf. on Computer Vision and Pattern Recognition. Salt Lake City: IEEE,
2018. 1625–1634. [doi: 10.1109/CVPR.2018.00175]
[8] Eykholt K, Evtimov I, Fernandes E, Li B, Rahmati A, Tramer F, Prakash A, Kohno T, Song D. Physical adversarial examples for object
detectors. In: Proc. of the 12th USENIX Workshop on Offensive Technologies (WOOT). Baltimore: USENIX Association, 2018. 1–10.
[9] Althoff M, Lutz S. Automatic generation of safety-critical test scenarios for collision avoidance of road vehicles. In: Proc. of the 2018
IEEE Intelligent Vehicles Symp. (IV). Changshu: IEEE, 2018. 1326–1333. [doi: 10.1109/IVS.2018.8500374]
[10] Klischat M, Althoff M. Generating critical test scenarios for automated vehicles with evolutionary algorithms. In: Proc. of the 2019 IEEE
Intelligent Vehicles Symp. (IV). Paris: IEEE, 2019. 2352–2358. [doi: 10.1109/IVS.2019.8814230]
[11] Cao YL, Xiao CW, Anandkumar A, Xu DF, Pavone M. AdvDO: Realistic adversarial attacks for trajectory prediction. In: Proc. of the
17th European Conf. on Computer Vision (ECCV). Tel Aviv: Springer, 2022. 36–52. [doi: 10.1007/978-3-031-20065-6_3]
[12] Garcia J, Feng Y, Shen JJ, Almanee S, Xia Y, Chen QA. A comprehensive study of autonomous vehicle bugs. In: Proc. of the 42nd
IEEE/ACM Int’l Conf. on Software Engineering (ICSE). Seoul: ACM, 2020. 385–396. [doi: 10.1145/3377811.3380397]
[13] Tang SC, Zhang ZY, Tang J, Ma L, Xue YX. Issue categorization and analysis of an open-source driving assistant system. In: Proc. of the
2021 IEEE Int’l Symp. on Software Reliability Engineering Workshops (ISSREW). Wuhan: IEEE, 2021. 148–153. [doi: 10.1109/
ISSREW53611.2021.00057]
[14] Zhu XL, Wang HC, You HM, Zhang WH, Zhang YY, Liu S, Chen JJ, Wang Z, Li KQ. Survey on testing of intelligent systems in
autonomous vehicles. Ruan Jian Xue Bao/Journal of Software, 2021, 32(7): 2056–2077 (in Chinese with English abstract). http://www.jos.
org.cn/1000-9825/6266.htm [doi: 10.13328/j.cnki.jos.006266]
[15] Tang SC, Zhang ZY, Zhang Y, Zhou JX, Guo Y, Liu S, Guo SJ, Li YF, Ma L, Xue YX, Liu Y. A survey on automated driving system
testing: Landscapes and trends. ACM Trans. on Software Engineering and Methodology, 2023, 32(5): 124. [doi: 10.1145/3579642]
[16] Dai JR, Li ZR, Zhang WQ, Zhang Y, Yang M. Simulation-based fuzzing for autonomous driving systems: Landscapes, challenges and
prospects. Journal of Computer Research and Development, 2023, 60(7): 1433–1447 (in Chinese with English abstract). [doi: 10.7544/
issn1000-1239.202330156]
[17] Society of Automotive Engineers (SAE) International. Taxonomy and definitions for terms related to driving automation systems for on-
road motor vehicles. 2021. https://ca-times.brightspotcdn.com/54/02/2d5919914cfe9549e79721b12e66/j3016-202104.pdf
[18] Ben Abdessalem R, Nejati S, Briand LC, Stifter T. Testing advanced driver assistance systems using multi-objective search and neural
networks. In: Proc. of the 31st IEEE/ACM Int’l Conf. on Automated Software Engineering (ASE). Singapore: ACM, 2016. 63–74. [doi:
10.1145/2970276.2970311]
[19] Klück F, Zimmermann M, Wotawa F, Nica M. Genetic algorithm-based test parameter optimization for ADAS system testing. In: Proc. of
the 19th Int’l Conf. on Software Quality, Reliability and Security (QRS). Sofia: IEEE, 2019. 418–425. [doi: 10.1109/QRS.2019.00058]
[20] Baidu Apollo GitHub repository. 2024. https://github.com/ApolloAuto/apollo
[21] Autoware. https://autoware.org
[22] Johnson MA. PID control technology. In: PID Control. London: Springer, 2005. 1–46. [doi: 10.1007/1-84628-148-2_1]
[23] Camacho EF, Bordons C. Introduction to model predictive control. In: Model Predictive Control. 2nd ed., London: Springer, 2007. 1–11.
[doi: 10.1007/978-0-85729-398-5_1]
[24] Chen L, Wu PH, Chitta K, Jaeger B, Geiger A, Li HY. End-to-end autonomous driving: Challenges and frontiers. arXiv:2306.16927,