节点文献
基于神经网络的模糊推理车辆跟驰模型
Fuzzy Inference Car-following Model Based on Neural Network
【摘要】 根据BP神经网络自学习的特点 ,通过训练使模糊变量和隶属函数隐含在网络内部 ,并用模糊逻辑推理模拟驾驶员对车辆进行控制的过程 ,可以使模型更接近于真实的跟驰行为 ,最后用该模型进行了仿真 ,证明其可行性
【Abstract】 Car-following model is a basic model in traffic microscopic simulation and car-following behavior is one of the complex tasks of driving. It is hard to describe drivers behavior with precise algorithm because of the fuzzy and indetermination character and the circumstance factors which exist during the driving. In this paper,a car-following model is developed, which integrates the self-learning character of the neural network and uses the fuzzy inference theory to simulate the driver to control the vehicle. The simulation result shows the feasibility of the model.
【关键词】 微观仿真;
跟驰模型;
神经网络;
模糊推理;
【Key words】 microscopic simulation; car-following model; neural network; fuzzy inference;
【Key words】 microscopic simulation; car-following model; neural network; fuzzy inference;
- 【文献出处】 交通与计算机 ,Computer and Communications , 编辑部邮箱 ,2004年01期
- 【分类号】TP183
- 【被引频次】10
- 【下载频次】242