The stability for CACC system with time delays and reconstitution information of vehicles for compensating delays based on Bi-LSTM

IF 5.8 2区计算机科学 Q1 TELECOMMUNICATIONS

Vehicular Communications Pub Date : 2024-12-06 DOI:10.1016/j.vehcom.2024.100868

Chenmin Zhang, Yonggui Liu, Zeming Li

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引用次数: 0

Abstract

The vehicle platoon using the cooperative adaptive cruise control (CACC) transmits information between vehicles via communication networks to increase the control performance. However, time delays are inevitable during the network transmission of information, which influence the stability of the CACC vehicle system. This paper proposes a method for compensating information affected by time delays based on a Bi-LSTM model. First, the third-order dynamics of the CACC vehicle systems are established, and the control strategies are proposed with the leading, preceding and following vehicles. The conditions of local stability and string stability for the CACC vehicle systems without time delays are derived based on the Routh-Hurwitz stability criterion and the frequency domain methods, which reveal the relationship between the model parameters and the controller parameters. For the CACC vehicle systems with time delays, the maximum time delays that ensure the local stability and string stability are achieved using the similar methods accordingly. However, the stability of the CACC vehicle systems is destroyed, when the time delay exceeds the maximum value. To deal with the impact of time delays, the bidirectional long short term memory (Bi-LSTM) model is adopted to predict and reconstitute the information affected by time delays. Furthermore, the relevant parameters are set and the real vehicle data is used for calculation and simulation. The simulation results confirm the local and string stability can be ensured, and further show the boundary of the maximum time delay may reach 0.45s for the CACC vehicle systems in this paper. In order to highlight superiority of Bi-LSTM, by comparing LSTM and KF with BiLSTM, the simulation results show Bi-LSTM has the highest correlation coefficient and the smallest root mean square error, which verify that Bi-LSTM reconstructing information affected by time delays is more effective than KF and LSTM.

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基于 Bi-LSTM 的具有时间延迟和补偿延迟的车辆重组信息的 CACC 系统的稳定性

使用协同自适应巡航控制系统（CACC）的车辆排通过通信网络在车辆之间传输信息，以提高控制性能。然而，在网络传输信息的过程中不可避免地会出现时间延迟，从而影响 CACC 车辆系统的稳定性。本文基于 Bi-LSTM 模型提出了一种补偿受时间延迟影响的信息的方法。首先，建立了 CACC 车辆系统的三阶动力学，并提出了前车、前车和后车的控制策略。基于 Routh-Hurwitz 稳定性准则和频域方法，得出了无时间延迟 CACC 车辆系统的局部稳定和串稳定条件，揭示了模型参数和控制器参数之间的关系。对于有时间延迟的 CACC 车辆系统，利用类似方法相应地获得了确保局部稳定性和串稳定性的最大时间延迟。然而，当时间延迟超过最大值时，CACC 车辆系统的稳定性就会被破坏。为了应对时间延迟的影响，采用了双向长短期记忆（Bi-LSTM）模型来预测和重组受时间延迟影响的信息。此外，还设置了相关参数，并使用真实车辆数据进行计算和仿真。仿真结果表明，本文中的 CACC 车辆系统可以确保局部稳定性和串稳定性，并进一步表明最大时间延迟的边界可能达到 0.45s。为了突出 Bi-LSTM 的优越性，通过比较 LSTM 和 KF 与 BiLSTM，仿真结果表明 Bi-LSTM 具有最高的相关系数和最小的均方根误差，这验证了 Bi-LSTM 重构受时间延迟影响的信息比 KF 和 LSTM 更有效。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Vehicular Communications Engineering-Electrical and Electronic Engineering

CiteScore

12.70

自引率

10.40%

发文量

审稿时长

62 days

期刊介绍： Vehicular communications is a growing area of communications between vehicles and including roadside communication infrastructure. Advances in wireless communications are making possible sharing of information through real time communications between vehicles and infrastructure. This has led to applications to increase safety of vehicles and communication between passengers and the Internet. Standardization efforts on vehicular communication are also underway to make vehicular transportation safer, greener and easier. The aim of the journal is to publish high quality peer–reviewed papers in the area of vehicular communications. The scope encompasses all types of communications involving vehicles, including vehicle–to–vehicle and vehicle–to–infrastructure. The scope includes (but not limited to) the following topics related to vehicular communications: Vehicle to vehicle and vehicle to infrastructure communications Channel modelling, modulating and coding Congestion Control and scalability issues Protocol design, testing and verification Routing in vehicular networks Security issues and countermeasures Deployment and field testing Reducing energy consumption and enhancing safety of vehicles Wireless in–car networks Data collection and dissemination methods Mobility and handover issues Safety and driver assistance applications UAV Underwater communications Autonomous cooperative driving Social networks Internet of vehicles Standardization of protocols.