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Improved adaptive neuro fuzzy inference system car-following behaviour model based on the driver–vehicle delay

机译:基于驾驶员-车辆延迟的改进的自适应神经模糊推理系统跟车行为模型

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摘要

In the past decades, different forms of car-following behaviour model have been intensively studied, proposed and implemented. These models are increasingly used by transportation experts to utilise for appropriate intelligent transportation systems. Unlike previous works, where the reaction delay is considered to be fixed, an improved adaptive neuro fuzzy inference system (ANFIS) model is proposed to simulate and predict the car-following behaviour based on the reaction delay of the driver–vehicle unit. An idea is proposed to calculate the reaction delay. In this model, the reaction delay is used as an input and other inputs–outputs of the model are chosen with respect to this parameter. Using the real-world data, the performance of the model is evaluated and compared with the responses of other existing ANFIS car-following models. The simulation results show that the proposed model has a very close compatibility with the real-world data and reflects the situation of the traffic flow in a more realistic way. Also, the comparison shows that the error of the proposed model is smaller than that in the other models.
机译:在过去的几十年中,已经对各种形式的跟车行为模型进行了深入的研究,提出和实施。运输专家越来越多地使用这些模型来利用适当的智能运输系统。与先前的反应延迟被认为是固定的工作不同,本文提出了一种改进的自适应神经模糊推理系统(ANFIS)模型,用于基于驾驶员-车辆单元的反应延迟来模拟和预测跟车行为。提出了一种计算反应延迟的思路。在该模型中,将反应延迟用作输入,并根据该参数选择模型的其他输入-输出。使用真实数据,可以评估模型的性能,并将其与其他现有ANFIS汽车跟随模型的响应进行比较。仿真结果表明,所提出的模型与现实世界的数据具有非常紧密的兼容性,并且可以更真实地反映交通状况。同样,比较表明,所提出模型的误差小于其他模型。

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