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孙长乐,高宏岩. 基于修正因子的雾天可变限速交通流模型[J]. 科学技术与工程, 2020, 20(10): 4016-4021.
SUN Chang-le.Traffic Model with Variable Speed Limit Control Based on Correction Factor under Foggy Weather Condition[J].Science Technology and Engineering,2020,20(10):4016-4021.
基于修正因子的雾天可变限速交通流模型
Traffic Model with Variable Speed Limit Control Based on Correction Factor under Foggy Weather Condition
投稿时间:2019-07-20  修订日期:2019-11-12
DOI:
中文关键词:  可变限速控制 T-S模型  灰狼优化算法 平均绝对百分比误差  交通流模型
英文关键词:vsl  t-s  model gwo  algorithm mean  absolute percentage  error traffic  model
基金项目:山东省重点研发计划 项目
     
作者单位
孙长乐 山东科技大学电气与自动化工程学院
高宏岩 山东科技大学电气与自动化工程学院
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中文摘要:
      分析雾天可变限速控制作用下高速公路的特性,提出基于雾天修正因子的在线自调整可变限速交通流模型。雾天修正因子通过T-S模型根据高速公路实时能见度与曲面半径在线自我调整,进而实现雾天可变限速交通流模型自我调整。采用灰狼算法对交通流模型参数及T-S模型参数进行优化调整。采用速度与密度的平均绝对百分比误差对模型性能进行评价。使用VISSIM与MATLAB进行仿真研究,仿真结果表明:相比于一般可变限速交通流模型,本文提出的交通流模型在速度和密度的辨识精度方面分别提升了41. 5%和10.5%,可以更加准确反映出雾天可变限速作用下高速公路的特性。
英文摘要:
      A self-adjusted macroscopic traffic model with fog correction factor was proposed in this paper by studying the freeway characteristics with the effect of variable speed limit (VSL) control under the foggy weather condition. The freeway different visibility and curve radius were the input variables of Takagi-Sugeno (T-S) model, the fog correction factor was the output variables of T-S model. The fog correction factor can be regulated in real time by using the T-S model according the freeway different visibility and curve radius. The proposed traffic model with the effect of variable speed limit control under foggy weather condition was regulated in real time by the correction factor. The grey wolf optimization (GWO) algorithm was used to optimize parameters of traffic model and T-S model. The mean absolute percentage error of speed and density were used to evaluate proposed traffic model. The freeway traffic data under the foggy weather condition were derived from VISSIM and the experiment simulations are applied in MATLAB. Compared with conventional traffic model, the proposed traffic model improves speed and density performance by 41. 5% and 10.5%, respectively. Simulation results show that proposed traffic model is more accurate to reflect freeway characteristics with effect of VSL control under foggy weather condition.
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