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首页> 外文会议>COTA international conference of transportation professionals >The Decision Making of Bus Entering Lane-Changing Behavior Analyzed by Back- Propagation Neural Network Model
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The Decision Making of Bus Entering Lane-Changing Behavior Analyzed by Back- Propagation Neural Network Model

机译：基于BP神经网络的公交车换道行为决策研究。

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When bus enter a bus stop, it has a mandatory lane-changing behavior which may cause capacity decrease in the upstream road. Firstly, based on the traffic survey, the lane changing location has been analyzed, and the bus entering lane-changing point distribution has been provided. This paper also figures out three main factors that impact buses entering lane changing: the traffic volume, the number of buses, and the bus location. Then, the three factors are used as the input variable to model the back-propagation neural network (BPNN) of which the output is the entering lane-changing point in upstream road. Lastly, the weight product method is used to analyze the sensitivity of those three factors. The result shows that traffic volume and bus location are positively correlated with the lane-changing point. However, there is a negative relationship between the bus number and the point. Furthermore, bus location has the largest sensitivity coefficient with the value being 0.22, and when 20% perturbation is added to the three factors, the sensitivity of bus number grows higher than the other two factors.
机译：当公交车进入公交车站时，具有强制性的换道行为，这可能会导致上游道路的通行能力下降。首先，基于交通调查，分析了换道位置，并提供了公交车进入换道点的分布。本文还找出影响公交车进入换道的三个主要因素：交通量，公交车数量和公交车位置。然后，将这三个因素用作输入变量，以对反向传播神经网络（BPNN）进行建模，其输出是上游道路的进入车道转换点。最后，使用权积法分析这三个因素的敏感性。结果表明，交通量和公交车位置与换道点成正相关。但是，公交车号和地点之间存在负相关关系。此外，母线位置具有最大的灵敏度系数，其值为0.22，并且当三个因素加上20％的扰动时，母线号的灵敏度会比其他两个因素更高。

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