Parallel Driving in CPSS:A Unified Approach for Transport Automation and Vehicle Intelligence

• Published in: IEEE/CAA journal of automatica sinica Vol. 4; no. 4; pp. 577 - 587
• Main Authors: Wang, Fei-Yue, Zheng, Nan-Ning, Cao, Dongpu, Martinez, Clara Marina, Li, Li, Liu, Teng
• Format: Journal Article
• Language: English
• Published: Piscataway Chinese Association of Automation (CAA) 01.01.2017; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Automation; Drivers; Learning (artificial intelligence); Road transportation; Testing; Trajectory; Transportation systems; Vehicles
• ISSN: 2329-9266; 2329-9274
• DOI: 10.1109/JAS.2017.7510598

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(CPSS) 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(iHorizon)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.