Quadrant Dynamic Programming for Optimizing Velocity of Ecological Adaptive Cruise Control

Previous studies have proposed various algorithms, such as model predictive control, machine learning, and dynamic programming (DP), for ecological adaptive cruise control (ACC). However, industrial application of these algorithms is limited owing to their considerable computational cost. Moreover,...

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Veröffentlicht in:	IEEE/ASME transactions on mechatronics 2022-06, Vol.27 (3), p.1533-1544
Hauptverfasser:	Hattori, Mitsuhiro, Shimizu, Osamu, Nagai, Sakahisa, Fujimoto, Hiroshi, Sato, Koji, Takeda, Yusuke, Nagashio, Takuma
Format:	Artikel
Sprache:	eng
Schlagworte:	Adaptive control Adaptive cruise control (ACC) Algorithms Car following Computational efficiency Computing costs Cruise control Dynamic programming Ecological effects electric vehicle (EV) Electric vehicles Energy consumption Feedback control Heuristic algorithms Industrial applications Machine learning Mechatronics optimal control Optimization Predictive control quadrant dynamic programming (QDP) Quadrants Test vehicles Tradeoffs Trajectory
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