改进的OVM交通流模型及数值模拟研究

摘要

传统的最优速度模型(OVM)中驾驶员灵敏度系数均取常数,这与实际情况不完全相符,为此,提出一种基于驾驶员灵敏度系数概率分布的最优速度模型(PDDS-OVM).该模型根据概率统计理论,将驾驶员的灵敏度系数归纳为按一定概率分布的函数,交通流队列中的每辆车对应该分布的一个值.在Matlab7.0仿真平台上,对驾驶员灵敏度系数在定值、均匀分布、正态分布3种情况下,分别进行反复数值模拟仿真,结果表明PDDS-OVM模型能更好地描述交通流的波动特性.%The driver's sensitivity factor in former Optimal Velocity Model(OVM) is always constant, which does not fully comply with realistic traffic flow characteristics. To gain a more realistic and objective model, a kind of probability distribution driver sensitivity OVM, i.e. PDDS-OVM is studied. In the model, the constant driver's sensitivity is substituted with probability distribution function, and each car driver in the queue matches a probability value. With Matlab7.0 platform, three kinds of simulations are made, in which the driver's sensitivity is fixed value, mean distribution value, and normal distribution value. The simulation after many times shows that the PDDS-OVM model is more realistic than traditional ones, and can better describe the dynamics and complexity of traffic flow.