Identifying dynamic interaction patterns in mandatory and discretionary lane changes using graph structure

Author:

Zhang Yue1,Zou Yajie1,Xie Yuanchang2,Chen Lei3

Affiliation:

1. Key Laboratory of Road and Traffic Engineering of Ministry of Education Tongji University Shanghai China

2. Department of Civil and Environmental Engineering University of Massachusetts Lowell Lowell Massachusetts USA

3. Department of Mobility and systems Research Institutes of Sweden Borås Sweden

Abstract

AbstractA quantitative understanding of dynamic lane‐changing interaction patterns is indispensable for improving the decision‐making of autonomous vehicles (AVs), especially in mixed traffic with human‐driven vehicles. This paper develops a novel framework combining the hidden Markov model (HMM) and graph structure to identify the difference in dynamic interaction patterns between mandatory lane changes (MLC) and discretionary lane changes (DLC). An HMM is developed to separate the interaction patterns considering heterogeneity in lane‐changing processes and reveal the temporal properties of these patterns. Conditional mutual information is used to quantify the interaction intensity, and the graph structure is used to characterize the relationship between vehicles. Finally, a case study is conducted to demonstrate the practical value of the proposed framework and validate its effectiveness in predicting lane‐changing trajectories. Based on the lane‐changing events extracted from a real‐world trajectory dataset, the proposed analytical framework is applied to model MLC and DLC under congested traffic with levels of service E and F. The results show that there could be multiple heterogeneous dynamic interaction patterns in a lane‐changing process. A comparison of MLC and DLC demonstrates that MLC involves more intense interactions and more frequent transitions of the interaction network structure, while the evolution rules of interaction patterns in DLC do not exhibit a clear trend. The findings in this study are useful for understanding the connectivity structure between vehicles in lane‐changing interactions and for designing safe and smooth driving decision‐making models for AVs and advanced driver‐assistance systems.

Funder

National Basic Research Program of China

Science and Technology Commission of Shanghai Municipality

Publisher

Wiley

Subject

Computational Theory and Mathematics,Computer Graphics and Computer-Aided Design,Computer Science Applications,Civil and Structural Engineering,Building and Construction

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