Car following behavioral stochasticity analysis and modeling: Perspective from wave travel time

被引:48
作者
Tian, Junfang [1 ]
Zhu, Chenqiang [1 ]
Chen, Danjue [2 ]
Jiang, Rui [3 ]
Wang, Guanying [1 ]
Gao, Ziyou [3 ]
机构
[1] Tianjin Univ, Coll Management & Econ, Tianjin 300072, Peoples R China
[2] Univ Massachusetts Lowell, Dept Civil & Environm Engn, Lowell, MA USA
[3] Beijing Jiaotong Univ, Key Lab Transport Ind Big Data Applicat Technol C, Minist Transport, Beijing 100044, Peoples R China
基金
中国国家自然科学基金;
关键词
Car following; Traffic oscillation; Wave travel time; Stochasticity; VEHICLE DYNAMICS;
D O I
10.1016/j.trb.2020.11.008
中图分类号
F [经济];
学科分类号
02 ;
摘要
This paper analyzes the car following behavioral stochasticity based on two sets of field experimental trajectory data by measuring the wave travel time series (tau) over tilde (n)(t) of vehicle n. The analysis shows that (i) No matter the speed of leading vehicle oscillates significantly or slightly, (tau) over tilde (n)(t) might change significantly; (ii) A follower's (tau) over tilde (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 (tau) over tilde (n)(t). The Augmented Dickey-Fuller test indicates that the time series xi(n)(t) = d (tau) over tilde (n)(t)/dt 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. (C) 2020 Elsevier Ltd. All rights reserved.
引用
收藏
页码:160 / 176
页数:17
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