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    史彦军

    • 教授     博士生导师   硕士生导师
    • 性别:男
    • 毕业院校:大连理工大学
    • 学位:博士
    • 所在单位:机械工程学院
    • 学科:工业工程. 机械电子工程. 机械设计及理论. 机械制造及其自动化
    • 办公地点:西部校区机械工程学院知方楼
    • 联系方式:Tel: 86-411-84709130 Mobile: 86-13940800853
    • 电子邮箱:syj@dlut.edu.cn

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    A Center-Rule-Based Neighborhood Search Algorithm for Roadside Units Deployment in Emergency Scenarios

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    论文类型:期刊论文

    第一作者:史彦军

    通讯作者:Lv, Lingling,Yu, Hao,Yu, Liangjie,Zhang, Zihui

    发表时间:2021-01-10

    发表刊物:MATHEMATICS

    卷号:8

    期号:10

    关键字:smart transportation; roadside units deployment; V2X; IoT; center-rule-based neighborhood search algorithm

    摘要:Roadside Units Deployment (RSUD) is of great importance to smart transportation with the Internet of Things (IoT). It is believed to be not feasible for RSUD to cover and perceive the whole area due to the high installation and maintenance costs. The candidate locations set of RSUD may be huge for a future urban area with vehicle-to-everything (V2X) networks. Most of the previous studies tried to maximize the Roadside Units (RSU) coverage only and made few reports on emergency scenarios, such as accidents happening. We tried to find better candidate locations of RSUD in some grid road networks with equal length streets, and then chose some of these locations for final installation with a given budget to minimize the average reporting time of emergency messages in V2X networks. Firstly, we analyzed candidate locations of RSUD for different cases of RSUs and vehicles. Then we proposed a message dissemination model for RSUD with the V2X network, and a center-rule-based neighborhood search algorithm (CNSA for short). In this algorithm, we generated initial solutions with the center rule and then obtained better neighbor solutions. Numerical simulation results from small-scale urban streets showed that the proposed algorithm performs well on execution time. Simulation results with Veins and Simulation of Urban Mobility) (SUMO) verified the proposed model and CNSA for evaluating the RSUD scheme by distance instead of accident reporting time in urban areas with large-scale traffic flow.