A Workshop on Driving Style of Automated Vehicles in Ambiguous Driving Scenarios
- Authors
- Lee, S.C.; Sahin, H.; Zhang, Y.; Yoon, S.H.; Lee, J.; Boll, S.; Wintersberger, P.
- Issue Date
- Sep-2022
- Publisher
- Association for Computing Machinery, Inc
- Keywords
- automated driving; driving style; human-machine cooperation; shared control
- Citation
- Adjunct Proceedings - 14th International ACM Conference on Automotive User Interfaces and Interactive Vehicular Applications, AutomotiveUI 2022, pp 182 - 185
- Pages
- 4
- Indexed
- SCIE
SCOPUS
- Journal Title
- Adjunct Proceedings - 14th International ACM Conference on Automotive User Interfaces and Interactive Vehicular Applications, AutomotiveUI 2022
- Start Page
- 182
- End Page
- 185
- URI
- https://scholarworks.gnu.ac.kr/handle/sw.gnu/29959
- DOI
- 10.1145/3544999.3550160
- ISSN
- 0000-0000
- Abstract
- Highly automated driving systems have taken control of driving instead of human drivers, and this trend is expected to increase. However, we should have solutions if the driving algorithms cannot resolve ambiguous driving situations. What if a lead vehicle is significantly slower than the speed limit when an AV follows it? Should the AV overtake the leading vehicle, or should it continue following it at a lower speed? What if an AV lies in the gray area of passing a junction when the traffic light soon turns red? Should an AV stop or continue passing a junction? We must have answers to resolve such situations. As a starting point, this workshop explores user perceptions of AV driving behavior (i.e., driving style and policy) in potential ambiguous scenarios. Through this workshop, we will find out potential issues determining driving style and policy in ambiguous driving scenarios, enhancing road safety and convenience in future driving situations. © 2022 Owner/Author.
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Collections - 공과대학 > Department of Industrial and Systems Engineering > Journal Articles

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