Effect model of urban traffic congestion on driver’s lane-changing behavior
Effect model of urban traffic congestion on driver’s lane-changing behavior
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DOI：
10.1177/1687814017724087
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发表时间：
2017-09
影响因子：
2.1
通讯作者：
Weiwei Qi;Huiying Wen;Yaping Wu;Lihui Qin
中科院分区：
文献类型：
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作者：
Weiwei Qi;Huiying Wen;Yaping Wu;Lihui Qin
道路交通拥堵已成为我国大城市的一种常态，并引发了许多问题，近年来换道模式越来越受到人们的关注。本研究旨在探讨城市交通拥挤状态下驾驶员心率与换道行为的变化趋势，并量化二者之间的逻辑关系。首先，设计了驾驶员心率和换道测试方案。严格选择测试驱动程序和测试路径，实现了实验。然后，结合驾驶员的行为相关数据，引入反向传播神经网络理论，以驾驶员的压力和状态为输入变量，驾驶员的反应为输出变量，建立了城市交通拥堵下驾驶员的“压力-状态-反应”模型。压力-状态-响应模型的结果表明，城市交通拥挤对驾驶员心率和换道比例的影响是显著的。验证结果表明，压力-状态-响应模型能较好地预测危险换道比例，可直接用于城市交通拥堵下的危险换道预警。
Road traffic congestion has become a normal state and caused many problems in large cities of China, and lane-changing model has attracted increased attention in recent years. This study is aimed to explore the changing trend and quantify the logical relationship between driver’s heart rate and lane-changing behavior under urban traffic congestion. First, the testing scheme of driver’s heart rate and lane-changing has been designed. Tested drivers and testing paths are chosen strictly to achieve the experiments as well. Then, with the drivers’ behavior-related data, the backpropagation neural network theory is introduced to build the driver’s “pressure–state–response” model under urban traffic congestion, which takes driver’s pressure and state as input variables, and driver’s response is selected as output variables. As the result of pressure–state–response model, it is significant that effect of urban traffic congestion on driver’s heart rate and lane-changing proportion. The validation results indicate that the pressure–state–response model works well to predict the proportion of risky lane-changing, and the pressure–state–response model can be used for warning the risky lane-changing directly under urban traffic congestion.