基于协作反馈控制算法的车联网行车安全动态强化模型

doi:10.11772/j.issn.1001-9081.2019101808

计算机应用 ›› 2020, Vol. 40 ›› Issue (4): 1209-1214.DOI: 10.11772/j.issn.1001-9081.2019101808

• 应用前沿、交叉与综合 • 上一篇下一篇

基于协作反馈控制算法的车联网行车安全动态强化模型

黄辰¹, 曹建农², 王时绘¹, 张龑¹

1. 湖北大学计算机与信息工程学院, 武汉 430062;
2. 香港理工大学工程学院, 香港

收稿日期:2019-10-25 修回日期:2019-12-13 出版日期:2020-04-10 发布日期:2020-04-17
通讯作者: 黄辰
作者简介:黄辰(1983-),男,福建龙岩人,副教授,博士,主要研究方向:物联网、智能驾驶;曹建农(1958-),男,江苏南京人,教授,博士,CCF高级会员,主要研究方向:人工智能、大数据分析;王时绘(1965-),男,河南郑州人,教授,硕士,CCF会员,主要研究方向:软件工程、信息化系统;张龑(1974-),男,湖北宜昌人,教授,博士,CCF会员,主要研究方向:软件工程、信息安全。
基金资助:
国家自然科学基金资助项目（61977021）；湖北省科学技术创新重大专项（2019ACA144）；湖北省自然科学基金资助项目（2018CFB692）。

Dynamic reinforcement model for driving safety based on cooperative feedback control in Internet of vehicles

HUANG Chen¹, CAO Jiannong², WANG Shihui¹, ZHANG Yan¹

1. School of Computer and Information Engineering, Hubei University, Hubei Wuhan 430062, China;
2. Faculty of Engineering, The Hong Kong Polytechnic University, Hongkong, China

Received:2019-10-25 Revised:2019-12-13 Online:2020-04-10 Published:2020-04-17
Supported by:
This work is partially supported by the National Natural Science Foundation of China (61977021), the Science and Technology Innovation Major Program of Hubei Province (2019ACA144), the Natural Science Foundation of Hubei Province(2018CFB692).

摘要/Abstract

摘要： 针对车联网（IoV）环境下，单车的信息采集和处理能力不足以满足时间敏感的行车安全应用需求，需要通过多车协作增强车间信息共享和信道接入能力等问题，提出一种基于协作反馈控制算法的行车安全动态强化模型。首先，提出虚拟车队协作模型，提升交通信息的采集精度，扩大采集范围，建立车间的稳定协作关系，在形成协作虚拟车队的同时降低信道拥塞；然后，实现一个针对消息传输和驾驶控制的联合优化模型，通过异构交通数据的深度融合最大化IoV的安全效用；最后，在对车流量时空变化进行预测的基础上，提出自适应的反馈控制模型实时调整驾驶安全策略。仿真结果表明，所提出的行车安全动态强化模型在各种车流分布模型下，均能够取得良好的性能指标，可以有效支持驾驶辅助控制系统，在保障行车安全的同时降低信道拥塞。

关键词: 车联网, 协作反馈控制, 安全驾驶, 驾驶辅助控制

Abstract: In Internet of Vehicles(IoV)environment,a single vehicle cannot meet all the time-sensitive driving safety requirements because of limited capability on information acquiring and processing. Cooperation among vehicles to enhance information sharing and channel access ability is inevitable. In order to solve these problems,a cooperative feedback control algorithm based dynamic reinforcement model for driving safety was proposed. Firstly,a virtual fleet cooperation model was proposed to improve the precision and expand the range of global traffic sensing,and a stable cooperation relationship was constructed among vehicles to form cooperative virtual fleet while avoiding channel congestion. Then,a joint optimization model focusing on message transmission and driving control was implemented,and the deep fusion of heterogeneous traffic data was used to maximize the safety utility of IoV. Finally,an adaptive feedback control model was proposed according to the prediction on spatial-temporal change of traffic flow,and the driving safety strategy was able to be adjusted in real-time. Simulation results demonstrate that the proposed model can obtain good performance indexes under different traffic flow distribution models, can effectively support driving assisted control system, and reduce channel congestion while maintaining driving safety.

Key words: Internet of Vehicles (IoV), collaborative feedback control, safe driving, driving assisted control

中图分类号:

TP31

黄辰, 曹建农, 王时绘, 张龑. 基于协作反馈控制算法的车联网行车安全动态强化模型[J]. 计算机应用, 2020, 40(4): 1209-1214.

HUANG Chen, CAO Jiannong, WANG Shihui, ZHANG Yan. Dynamic reinforcement model for driving safety based on cooperative feedback control in Internet of vehicles[J]. Journal of Computer Applications, 2020, 40(4): 1209-1214.

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基于协作反馈控制算法的车联网行车安全动态强化模型

Dynamic reinforcement model for driving safety based on cooperative feedback control in Internet of vehicles

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