Artificial Intelligence for Automated Vehicle Control and Traffic Operations: Challenges and Opportunities-Reference-Cited by-同舟云学术

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Artificial Intelligence for Automated Vehicle Control and Traffic Operations: Challenges and Opportunities

Published:2021-07-09 Issue: Volume: Page:60-72
ISSN:2196-5544
Container-title:Road Vehicle Automation 8
language:
Short-container-title:

Author:

Abbink David A.,Hao Peng,Laval Jorge,Shalev-Shwartz Shai,Wu Cathy,Yang Terry,Hamdar Samer,Chen Danjue,Xie Yuanchang,Li Xiaopeng,Haque Mohaiminul

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-80063-5_6

Reference11 articles.

1. Abbink, D.A., Mulder, M., Boer, E.R.: Haptic shared control: smoothly shifting control authority? Cogn. Technol. Work 14(1), 19–28 (2012)

2. Hao, P., Wu, G., Boriboonsomsin, K., Barth, M.J.: Developing a framework of eco-approach and departure application for actuated signal control. In: 2015 IEEE Intelligent Vehicles Symposium (IV), pp. 796–801. IEEE (2015)

3. Hao, P., Wei, Z., Bai, Z., Barth, M.J.: Developing an adaptive strategy for connected eco-driving under uncertain traffic and signal conditions. UC Davis: National Center for Sustainable Transportation (2020). https://doi.org/10.7922/G2F18WZ1

4. Kolekar, S., de Winter, J., Abbink, D.: Which parts of the road guide obstacle avoidance? Quantifying the driver’s risk field. Appl. Ergon. 89, 103196 (2020a)

5. Kolekar, S., de Winter, J., Abbink, D.: Human-like driving behaviour emerges from a risk-based driver model. Nat. Commun. 11(1), 1–13 (2020b)

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