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An ANFIS design for prediction of future state of a vehicle in lane change behavior

机译:ANFIS设计,用于预测车道变更行为中车辆的未来状态

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摘要

The lane change maneuver is one of the most common driving behaviors in highways or rural roads. Each driver usually conducts at least one lane change maneuver during his trip. Therefore, it is chosen as the object behavior in this study and novel adaptive neuro-fuzzy inference models are proposed for this behavior. These models are able to simulate and predict the future behavior of a Driver-Vehicle-Unit in the lane change maneuver for various time delays. Using the field data, the outputs of the models are validated and compared with the real traffic data. The simulation results show that these models have a very close compatibility with the field data and reflect the situation of the traffic flow in a more realistic way.
机译:变道操纵是高速公路或乡村道路上最常见的驾驶行为之一。每个驾驶员在旅途中通常至少进行一次换道操作。因此,在本研究中将其选择为对象行为,并针对该行为提出了新型的自适应神经模糊推理模型。这些模型能够模拟和预测驾驶员车辆单元在各种时间延迟的换道操作中的未来行为。使用现场数据,对模型的输出进行验证,并将其与实际交通数据进行比较。仿真结果表明,这些模型与现场数据具有非常紧密的兼容性,可以更真实地反映交通状况。

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