中国安全科学学报 ›› 2021, Vol. 31 ›› Issue (S1): 149-153.doi: 10.16265/j.cnki.issn 1003-3033.2021.S1.026

• 安全工程技术 • 上一篇    下一篇

车联网在水电企业行车安全管理变革中的应用

张洪涛1 政工师, 李光华2 工程师, 谢凤祥2 高级工程师, 韩名亮3   

  1. 1 国能大渡河流域水电开发有限公司, 四川 成都 610041;
    2 国能大渡河大数据服务有限公司, 四川 成都 610041;
    3 成都嘉捷信诚信息技术有限公司, 四川 成都 610095
  • 收稿日期:2021-09-12 修回日期:2021-11-15 出版日期:2021-12-30 发布日期:2022-06-30
  • 作者简介:张洪涛 (1971—),男,四川仁寿人,硕士,政工师,主要从事政策理论、综合事务管理、安全风险智能防控体系等方面的工作。E-mail:2550973890@qq.com。

Application of internet of vehicles technology in reform of driving safety management in hydropower enterprises

ZHANG Hongtao, LI Guanghua, XIE Fengxiang, HAN Mingliang   

  1. 1 CHN Energy Dadu River Hydropower Development Co., Ltd., Chengdu Sichuan 610041, China;
    2 CHN Energy Dadu River Big Data Services Co., Ltd., Chengdu Sichuan 610041, China;
    3 Chengdu Jiajie Xincheng Information Technology Co. Ltd., Chengdu Sichuan 610095, China
  • Received:2021-09-12 Revised:2021-11-15 Online:2021-12-30 Published:2022-06-30

摘要: 为避免行车安全事故,利用车联网和大数据技术,融合人工智能算法模型,研究行车安全风险因素,通过国能大渡河公司车联网智能管控系统实践,结合多年水电企业车辆管理经验,探讨行车安全风险识别和风险应对措施,防控各项行车安全风险。研究结果表明:车辆网技术应用在水电企业行车安全风险管控中,能够有效预警和防范包括车辆自身、道路环境以及驾驶人员等在内的各类风险隐患,增强车辆管理流程的覆盖度,提高行车安全的预见性和安全监管水平。

关键词: 车联网, 水电企业, 车辆管理, 风险预警, 安全管理

Abstract: In order to avoid traffic accidents, risk factors of traffic safety were studied by using internet of vehicles and big data technology as well as artificial intelligence algorithm model. Then, through a case study on the intelligent management and control system of Guoneng Daduhe company's internet of vehicles, traffic safety risk identification and response measures were discussed based on years of vehicle management experience in hydropower enterprises so as to prevent and control various traffic risks. The results show that the application of vehicle network technology in driving risk management and control of such enterprises can effectively pre-warn and prevent various potential risks concerning vehicles, road environment and drivers, enhance the coverage of vehicle management process, and improve the predictability of driving safety and supervision.

Key words: vehicle networking, hydropower enterprise, vehicle management, risk warning, safety management

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