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侧风对大跨度桥梁轿车行车安全影响的仿真分析
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  • 英文篇名:Simulation analysis of the influence of crosswind on traffic safety of long-span bridges
  • 作者:姜康 ; 尹宏 ; 冯忠祥
  • 英文作者:JIANG Kang;YIN Hongcheng;FENG Zhongxiang;School of Automobile and Traffic Engineering, Hefei University of Technology;
  • 关键词:侧风 ; CarSim仿真 ; 行车安全 ; 大跨度桥梁 ; 反向传播(BP)神经网络 ; 风险分析 ; 临界风速
  • 英文关键词:crosswind;;CarSim simulation;;traffic safety;;long-span bridge;;back propagation(BP) neural network;;risk analysis;;critical speed
  • 中文刊名:HEFE
  • 英文刊名:Journal of Hefei University of Technology(Natural Science)
  • 机构:合肥工业大学汽车与交通工程学院;
  • 出版日期:2019-02-28
  • 出版单位:合肥工业大学学报(自然科学版)
  • 年:2019
  • 期:v.42;No.310
  • 基金:国家自然科学基金资助项目(51678211)
  • 语种:中文;
  • 页:HEFE201902001
  • 页数:6
  • CN:02
  • ISSN:34-1083/N
  • 分类号:7-12
摘要
为了分析侧风对大跨度桥梁轿车行车安全的影响,文章综合考虑风速风向角、路面摩擦系数和车速等因素,利用CarSim软件建立了车辆动力学仿真模型;以轿车侧向偏移作为行车风险评价指标,通过数理统计理论分析各因素对行车安全的影响规律及显著性;建立了基于反向传播(back propagation,BP)神经网络的安全车速预测模型,对于不同道路环境、风环境下的安全车速进行预测。结果表明,该模型可以较好地预测安全车速,对于后期的研究以及制定大跨度桥梁行车管控的策略有一定的指导意义。
        In order to analyze the effect of crosswind on traffic safety of long-span bridges, vehicle dynamics simulation models were established using CarSim software considering factors such as wind speed, friction coefficient on road surface and vehicle speed. Then the lateral offset was taken as the risk evaluation index of driving, and the influence law of the factors on driving safety as well as the significance level was explored through the theory of mathematical statistics. Finally, the critical speed prediction models under different wind environments and road conditions were set up based on back propagation(BP) neural network. The results show that the model has good performance in predicting the critical speed, which is valuable for later researches and the design of traffic control strategies for long-span bridges.
引文
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