Car following behavioral stochasticity analysis and modeling: Perspective from wave travel time. (January 2021) - Tian, Junfang; Zhu, Chenqiang; Chen, Danjue; Jiang, Rui; Wang, Guanying; Gao, Ziyou
Highlights: Car following behavioral stochasticity has been analyzed based on two sets of field experimental trajectory data. Wave travel time does not follow a consistent pattern. Changing rate of wave travel time follows a mean reversion process. A new stochastic Newell type model is proposed. Stochastic factors exhibit common feature from different perspectives. Abstract: This paper analyzes the car following behavioral stochasticity based on two sets of field experimental trajectory data by measuring the wave travel time series τ ˜ n ( t ) of vehicle n . The analysis shows that (i) No matter the speed of leading vehicle oscillates significantly or slightly, τ ˜ n ( t ) might change significantly; (ii) A follower's τ ˜ n ( t ) can vary from run to run even if the leader travels at the same stable speed; (iii) Sometimes, even if the leader's speed fluctuates significantly, the follower can keep a nearly constant value of τ ˜ n ( t ) . The Augmented Dickey-Fuller test indicates that the time series ξ n ( t ) = d τ ˜ n ( t ) / d t follows a mean reversion process, no matter the oscillations fully developed or not. Based on the finding, a simple stochastic Newell model is proposed. The concave growth pattern of traffic oscillations has been derived analytically. Furthermore, simulation results demonstrate that the new model well captures both macroscopic characteristic of traffic flow evolution and microscopic characteristic of car following.