Control of connected and automated vehicles: State of the art and future challenges

被引：439
作者：
Guanetti, Jacopo [1 ]
Kim, Yeojun [1 ]
Borrelli, Francesco [1 ]
机构：
[1] Univ Calif Berkeley, Dept Mech Engn, Berkeley, CA 94720 USA
来源：
ANNUAL REVIEWS IN CONTROL | 2018年 / 45卷
关键词：
MODEL-PREDICTIVE CONTROL; HYBRID ELECTRIC VEHICLES; ADAPTIVE CRUISE CONTROL; COSTLY ENERGY MANAGEMENT; CONTROL STRATEGIES; CONTROL FRAMEWORK; COLLISION-AVOIDANCE; CONTROL ALGORITHMS; TRAFFIC CONTROL; LATERAL CONTROL;
D O I：
10.1016/j.arcontrol.2018.04.011
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Autonomous driving technology pledges safety, convenience, and energy efficiency. Its challenges include the unknown intentions of other road users: communication between vehicles and with the road infrastructure is a possible approach to enhance awareness and enable cooperation. Connected and automated vehicles (CAVs) have the potential to disrupt mobility, extending what is possible with driving automation and connectivity alone. Applications include real-time control and planning with increased awareness, routing with micro-scale traffic information, coordinated platooning using traffic signals information, and eco-mobility on demand with guaranteed parking. This paper introduces a control and planning architecture for CAVs, and surveys the state of the art on each functional block therein; the main focus is on techniques to improve energy efficiency. We provide an overview of existing algorithms and their mutual interactions, we present promising optimization based approaches to CAVs control and identify future challenges.
引用
收藏
页码：18 / 40
页数：23
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