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作 者:黄辰 曹建农[2] 王时绘 张龑 HUANG Chen;CAO Jiannong;WANG Shihui;ZHANG Yan(School of Computer and Information Engineering,Hubei University,Hubei Wuhan 430062,China;Faculty of Engineering,The Hong Kong Polytechnic University,Hongkong,China)
机构地区:[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,中国香港
出 处:《计算机应用》2020年第4期1209-1214,共6页journal of Computer Applications
基 金: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)。
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。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.
分 类 号:TP31[自动化与计算机技术—计算机软件与理论]
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