基于随机效用理论的城市道路车辆自由换道行为研究

周红媚,孙叶,徐秀娟

交通运输研究 ›› 2017, Vol. 3 ›› Issue (2) : 9-16.

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PDF(1536 KB)
交通运输研究 ›› 2017, Vol. 3 ›› Issue (2) : 9-16.
专题

基于随机效用理论的城市道路车辆自由换道行为研究

  • 周红媚,孙叶,徐秀娟
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Behavior of Discretionary Lane Changing on Urban Streets Based on Random Utility Theory

  • ZHOU Hong-mei, SUN Ye and XU Xiu-juan
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摘要

为深入分析城市道路驾驶员换道行为的影响因素,基于大连市西南路路段的车辆运行轨迹 数据,引入随机效用理论,建立了城市道路车辆自由换道模型,并对模型进行了标定和验证,且 应用弹性理论定量分析了换道概率对不同因素的敏感度。结果表明,所建模型可以较好地预测车 辆的自由换道行为;驾驶员换道决策对本车与当前车道前方车辆之间的车头间距最为敏感;相对 于当前车道前方空隙的刺激,相邻车道驾驶环境的诱惑对驾驶员换道决策的影响较小,说明在前 方无不利刺激(狭小的驾驶空间或加速空间) 的情况下,驾驶员在行驶过程中倾向于保持在当前 车道。该研究结果可进一步应用于城市道路换道行为的微观仿真研究中,以提高其仿真精度。

Abstract

In order to study the impact of various factors on drivers′ lane changing behavior on urban street, using the vehicle trajectory data collected from Southwest Road of Dalian city, the discretionary lane changing model on urban street was set up based on the random utility theory. The built model was calibrated and validated, and the sensitivity of lane changing probability to different factors was quantitatively evaluated by using elasticity analysis theory. The results show that the model can predict the behavior of discretionary lane changing well; the probability of lane changing is most sensitive to the space headway between the vehicle and its leading vehicle; comparatively, the temptation of the driving environment on the adjacent lane has less impact; in the absence of unfavorable stimulus (narrow driving space or acceleration space) in front of the vehicle, drivers tend to keep on the current lane while driving. The result can be furtherly applied in the microscopic simulations of the lane changing behavior on urban streets so as to enhance the precision of the simulations.

关键词

城市交通 / 驾驶员行为 / 自由换道模型 / 随机效用理论 / 弹性分析

Key words

urban traffic / driver behavior / discretionary lane changing model / random utility theory / elasticity analysis

引用本文

导出引用
周红媚,孙叶,徐秀娟. 基于随机效用理论的城市道路车辆自由换道行为研究[J]. 交通运输研究. 2017, 3(2): 9-16
ZHOU Hong-mei, SUN Ye and XU Xiu-juan. Behavior of Discretionary Lane Changing on Urban Streets Based on Random Utility Theory[J]. Transport Research. 2017, 3(2): 9-16

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