Understanding the mechanism of lane changing process and dynamics using microscopic traffic data

被引:39
作者
Chauhan, Prajwal [1 ]
Kanagaraj, Venkatesan [1 ]
Asaithambi, Gowri [2 ]
机构
[1] Indian Inst Technol Kanpur, Dept Civil Engn, Kanpur, Uttar Pradesh, India
[2] Indian Inst Technol Tirupati, Dept Civil & Environm Engn, Chindepalle, Andhra Pradesh, India
关键词
Lane change; Duration of lane change; Free lane change; Constraint lane Change; Microscopic Traffic Data; RELAXATION PHENOMENON; MODEL; SIMULATION; DURATION;
D O I
10.1016/j.physa.2022.126981
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
The lane changing manoeuvre is a fundamental driver behaviour that determines vehicle distribution across lanes. Lane-changing behaviour has a significant effect on traffic flow and may cause traffic oscillations, relaxation, moving bottleneck, and capacity drop/breakdown. This study aims to identify the lane change window and classify the lane change behaviour of vehicles using NGSIM data. Determination of the starting and ending points (time window) of lane change operation has a significant impact on the lane change duration and dynamics. In this study, a new approach is proposed to identify the time window of lane change operation using the absolute value of the derivative of the cumulative lateral speed which reduces unintended drifts of vehicles in lateral direction. Then, the lane changes are classified into free, forced and cooperative using Hidas definition (Hidas, 2005) which does not closely replicate the field conditions. This study proposes three different methods for the classification of lane changes based on microscopic traffic variables and vehicle kinematics in the vicinity of lane changing process and these methods are verified quantitatively. Statistical tests are performed to check if the types of lane changes are statistically different. Finally, two types of classification are considered such as free lane change and constraint lane change, and a log-normal distribution is fitted for the lane change duration of these two types. (c) 2022 Elsevier B.V. All rights reserved.
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页数:18
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