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A Review and Outlook on Predictive Cruise Control of Vehicles and Typical Applications Under Cloud Control System

巡航控制 现状 云计算 智能交通系统 汽车工业 控制(管理) 计算机科学 模型预测控制 运输工程 巡航 工程类 系统工程 人工智能 航空航天工程 经济 操作系统 市场经济
作者
Bolin Gao,Keke Wan,Qien Chen,Zhou Wang,Rui Li,Yu Jiang,Run Mei,Yinghui Luo,Keqiang Li
出处
期刊:Machine Intelligence Research [Springer Science+Business Media]
卷期号:20 (5): 614-639 被引量:23
标识
DOI:10.1007/s11633-022-1395-3
摘要

Abstract With the application of mobile communication technology in the automotive industry, intelligent connected vehicles equipped with communication and sensing devices have been rapidly promoted. The road and traffic information perceived by intelligent vehicles has important potential application value, especially for improving the energy-saving and safe-driving of vehicles as well as the efficient operation of traffic. Therefore, a type of vehicle control technology called predictive cruise control (PCC) has become a hot research topic. It fully taps the perceived or predicted environmental information to carry out predictive cruise control of vehicles and improves the comprehensive performance of the vehicle-road system. Most existing reviews focus on the economical driving of vehicles, but few scholars have conducted a comprehensive survey of PCC from theory to the status quo. In this paper, the methods and advances of PCC technologies are reviewed comprehensively by investigating the global literature, and typical applications under a cloud control system (CCS) are proposed. Firstly, the methodology of PCC is generally introduced. Then according to typical scenarios, the PCC-related research is deeply surveyed, including freeway and urban traffic scenarios involving traditional vehicles, new energy vehicles, intelligent vehicles, and multi-vehicle platoons. Finally, the general architecture and three typical applications of the cloud control system (CCS) on PCC are briefly introduced, and the prospect and future trends of PCC are proposed.
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