基于扰动传播特征的随机Newell跟驰模型

为研究快速路场景下小汽车跟驰行为，本文从北京市快速路交通流视频中提取高时间分辨率的机动车运行轨迹数据.统计发现，在不同跟驰速度下，小汽车车头时距均服从对数正态分布；利用动态时间规整算法提取小汽车的反应时间与扰动传播速度等特征参数，分别标定其概率分布函数，证明跟驰过程中小汽车的反应时间分布峰值和数学期望分别为1.0 s 和1.57 s；在挖掘反应时间、扰动传播速度与车头时距量化关系的基础上，建立基于交通扰动传播特征的随机Newell跟驰模型，并标定得到分速度区间的模型参数.仿真结果表明，本文提出的随机Newell跟驰模型能有效刻画跟驰行为与扰动传播间的关联特征，同时生成符合预期的交通流基本图.新模型能够为跟驰行为随机特征对交通状态的影响研究(如交通流陡降、宽移动阻塞等)提供支持.

Stochastic Newell Car-following Model Based on Propagation of Disturbances

In order to study the car following behavior on expressways, high-time resolution trajectory data of motor- vehicles were extracted from the traffic video of the expressway in Beijing. First, it is found that under different speed intervals, the headway of the following vehicle obeys the lognormal distribution. Second, the Dynamic Time Warping algorithm was used to extract parameters including reaction time and disturbance propagation speed, and the probability distribution functions were respectively calibrated. It is proved that the peak of the reaction time distribution falls into the interval of 1.0 s and the mathematical expectation of the reaction time is 1.57 s. Further, a novel stochastic Newell car- following model based on the disturbance propagation characteristics was proposed considering the relationship among reaction time, disturbance propagation speed, and time headway. The parameters of disturbance propagation speed under different speed intervals were demarcated. Finally, the simulation analysis shows that the new stochastic Newell model can better characterize the stochastic characteristics of car-following behavior and disturbance propagation, and generate the expected traffic flow fundamental diagram.