Parallel driving in CPSS: a unified approach for transport automation and vehicle intelligence

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Parallel_driving_in_CPSS-2017.pdf (14.68 MB)

Date published

2017-09-15

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Authors

Wang, Fei-Yue
Zheng, Nan-Ning
Cao, Dongpu
Martinez, Clara Marina
Li, Li
Liu, Teng

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Volume Title

Publisher

IEEE

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Article

ISSN

2329-9266

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URI

http://dx.doi.org/10.1109/JAS.2017.7510598
 https://dspace.lib.cranfield.ac.uk/handle/1826/12631

Citation

Wang F, Zheng N, Cao D, Martinez C. Li L, Liu T, Parallel driving in CPSS: A unified approach for transport automation and vehicle intelligence, IEEE Caa Journal of Automatica Sinica, Vol. 4, Issue 4, 2017, pp. 577-587

Abstract

The emerging development of connected and automated vehicles imposes a significant challenge on current vehicle control and transportation systems. This paper proposes a novel unified approach, Parallel Driving, a cloud-based cyberphysical-social systems U+0028 CPSS U+0029 framework aiming at synergizing connected automated driving. This study first introduces the CPSS and ACP-based intelligent machine systems. Then the parallel driving is proposed in the cyber-physical-social space, considering interactions among vehicles, human drivers, and information. Within the framework, parallel testing, parallel learning and parallel reinforcement learning are developed and concisely reviewed. Development on intelligent horizon U+0028 iHorizon U+0028 and its applications are also presented towards parallel horizon. The proposed parallel driving offers an ample solution for achieving a smooth, safe and efficient cooperation among connected automated vehicles with different levels of automation in future road transportation systems.

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Github

Keywords

Automation, Vehicles, Testing, Trajectory, Learning (artificial intelligence), Road transportation

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