Understanding common human driving semantics for autonomous vehicles

• Published in: Patterns (New York, N.Y.) Vol. 4; no. 7; p. 100730
• Main Authors: Xia, Yingji, Geng, Maosi, Chen, Yong, Sun, Sudan, Liao, Chenlei, Zhu, Zheng, Li, Zhihui, Ochieng, Washington Yotto, Angeloudis, Panagiotis, Elhajj, Mireille, Zhang, Lei, Zeng, Zhenyu, Zhang, Bing, Gao, Ziyou, Chen, Xiqun (Michael)
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 14.07.2023; Elsevier
• Subjects: autonomous vehicle; driving behavior perception; driving semantics; electroencephalography; hierarchical understanding abstraction; human-machine interaction; neural-informed model; neuroscience; driving semantics; electroencephalography; human-machine interaction; hierarchical understanding abstraction; neuroscience; driving behavior perception; autonomous vehicle; neural-informed model; DSML 2: Proof-of-concept: Data science output has been formulated, implemented, and tested for one domain/problem

Autonomous vehicles will share roads with human-driven vehicles until the transition to fully autonomous transport systems is complete. The critical challenge of improving mutual understanding between both vehicle types cannot be addressed only by feeding extensive driving data into data-driven mode...