车联网邻域系统动态状态估计研究进展

IF 2.8 Q2 TRANSPORTATION SCIENCE & TECHNOLOGY
Yan Wang, Henglai Wei, Lie Yang, Bin-Bin Hu, Binbin Hu, Chen Lv
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引用次数: 2

摘要

准确的车辆状态和周围交通信息是智能网联车辆决策和动态控制的基础。在发展状态估计技术方面已经投入了大量的研究工作。本文综述了近年来该领域的研究进展。为了能够统一描述多个交通要素的状态,提出了车辆邻域系统的概念来描述由车辆及其周围交通要素组成的系统,并将其与传统的宏观交通研究领域区分开来。在这项工作中,车辆邻里系统由三个主要交通要素组成:主车辆、前车和道路。因此,围绕上述三个交通目标,对车辆邻域系统的状态估计方法进行了综述。本文对这些方法进行了全面的分析,并描述了它们的优缺点。此外,对车辆邻域系统状态估计的未来研究方向进行了进一步探讨。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Review of Dynamic State Estimation for the Neighborhood System of Connected Vehicles
Precise vehicle state and the surrounding traffic information are essential for decision-making and dynamic control of intelligent connected vehicles. Tremendous research efforts have been devoted to developing state estimation techniques. This work investigates the research progress in this field over recent years. To be able to describe the state of multiple traffic elements uniformly, the concept of a vehicle neighborhood system is proposed to describe the system composed of vehicles and their surrounding traffic elements and to distinguish it from the traditional macroscopic traffic research field. In this work, the vehicle neighborhood system consists of three main traffic elements: the host vehicle, the preceding vehicle, and the road. Therefore, a review of state estimation methods for the vehicle neighborhood system is presented around the three traffic objects mentioned earlier. This article performs a comprehensive analysis of these approaches and depicts their strengths and drawbacks. In addition, future research directions on the state estimation of the vehicle neighborhood system are further discussed.
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CiteScore
6.40
自引率
41.20%
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