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A neural network based modeling and simulation of bicycle conflict avoidance behaviors at non-signalized intersections

机译:基于神经网络的非信号交叉口自行车避碰行为建模与仿真

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The modeling and simulation of bicycle conflict avoidance behaviors with other vehicles (motor-carother bicyclespedestrians) and the obstacle (safety island, fence etc.) at non-signalized intersections is of great importance in junction analysis. However, it is very difficult to simulate the conflict avoidance behaviors of individual bicycle because of the great variations in the cycling behaviors, conflict characteristics and traffic environment. A computer-based four-layered back propagation neural network (NN) model was developed for bicycle conflict avoidance behaviors modeling. The NN model was trained, validated with field data and then compared with Social Force model. Results showed that the NN model could produce reasonable estimates for individual bicycle conflict avoidance behaviors at non-signalized intersections.
机译:在交叉路口分析中,与其他车辆(机动车辆的自行车行人)和障碍物(安全岛,围栏等)的非机动车交叉避让行为的建模和仿真在交叉路口分析中非常重要。然而,由于自行车行为,冲突特征和交通环境的巨大变化,很难模拟单个自行车的冲突避免行为。建立了基于计算机的四层反向传播神经网络(NN)模型,用于自行车避碰行为建模。训练了NN模型,使用现场数据进行了验证,然后与Social Force模型进行了比较。结果表明,NN模型可以为非信号交叉口的单个自行车避碰行为提供合理的估计。

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