具有加权顾前势的交通流模型

交通流随机行为的研究对于理解交通系统的内在演化规律具有重要作用. 基于元胞自动机模型和顾前势模型, 提出了一种考虑加权顾前势的交通流模型. 通过引入顾前势加权系数及对越靠近自身车辆的相互作用势赋予越大的权重, 使得建模过程更符合实际交通中司机根据前面车辆和环境情况进行随机决策的过程. 通过数值模拟, 再现了丰富的高密度交通行为. 仿真结果表明, 加权系数在高密度情况下作用明显, 更有利于在保持较高交通密度的同时, 具有较高的交通流量和道路通行能力. 关键词： 交通流 顾前势 随机模型 加权

On traffic flow mo del with weighted lo ok-ahead p otential

Research on the stochastic behavior of traffic flow is important to understand the intrinsic evolution rule of traffic system. On the basis of cellular automata model and traffic flow model with look-ahead potential, in this paper, a novel traffic flow model with weighted look-ahead potential is presented. By introducing the weighting coefficient into the look-ahead potential and endowing the potential of vehicle closer to itself with a greater weight, the modeling process is more suitable for the driver's random decision-making process which is based on the vehicle and enviroment situation in front of him in actual traffic. Complex high-density traffic behavior is reproduced by numerical simulations. The simulation results show that the weighting coefficient has an obvious effect on high-density traffic flux, and the weighted model is more conducive to keeping high traffic flux and road capacity while maintaining a high traffic density.
Keywords： traffic flow look-ahead potential stochastic model weighted