Safety Risks of Self-driving Vehicle: Identification and Measurement

Autor: Dou Wenyue, Hu Ping, Wei Ping, Zheng Nanning
Jazyk: čínština
Rok vydání: 2021
Předmět:
Zdroj: 中国工程科学, Vol 23, Iss 6, Pp 167-177 (2021)
Druh dokumentu: article
ISSN: 2096-0034
DOI: 10.15302/J-SSCAE-2021.06.016
Popis: Self-driving vehicle is a hot application of artificial intelligence, and the identification and measurement of its safety risks has become an urgent research topic in the field of artificial intelligence safety. In this study, we collect qualitative information through case interviews and identify the key elements of safety risks using the qualitative research method and the grounded theory. Further, we propose for the first time a six-element frame for the safety risks of self-driving vehicle. These elements include single vehicle safety, networking safety, technological level, legal policies, public opinion, and industrial risks. Subsequently, we design a questionnaire and conduct two online questionnaires surveys to measure the safety risk elements. To cope with future safety risks of self-driving vehicle, enterprises should strengthen the research and manufacturing of key components, increase investment in information security, participate in the formulation of industry standards and regulations, and maintain a sustainable development. The government should strengthen the supervision over self-driving vehicle tests, improve regulations and standards, and guide talent training. Consumers should keep good driving habits and maintain rational regarding self-driving vehicle.
Databáze: Directory of Open Access Journals