Space Domain based Ecological Cooperative and Adaptive Cruise Control on Rolling Terrain

Lei, Mingyue, Wang, Haoran, Li, Duo, Li, Zhenning, Dhamaniya, Ashish, Hu, Jia

arXiv.org Artificial Intelligence 

Ecological Cooperative and Adaptive Cruise Control (Eco-CACC) is widely focused to enhance sustainability of CACC. However, state-of-the-art Eco-CACC studies are still facing challenges in adopting on rolling terrain. Furthermore, they cannot ensure both ecology optimality and computational efficiency. Hence, this paper proposes a nonlinear optimal control based Eco-CACC controller. It has the following features: i) enhancing performance across rolling terrains by modeling in space domain; ii) enhancing fuel efficiency via globally optimizing all vehicle's fuel consumptions; iii) ensuring computational efficiency by developing a differential dynamic programming-based solving method for the non-linear optimal control problem; iv) ensuring string stability through theoretically proving and experimentally validating. The performance of the proposed Eco-CACC controller was evaluated. Results showed that the proposed Eco-CACC controller can improve average fuel saving by 37.67% at collector road and about 17.30% at major arterial.

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