Spatiotemporal Interaction Pattern Recognition and Risk Evolution Analysis During Lane Changes
Artikel i vetenskaplig tidskrift, 2023

In complex lane change (LC) scenarios, semantic interpretation and safety analysis of dynamic interaction pattern are necessary for autonomous vehicles to make appropriate decisions. This study proposes a learning framework that combines primitive-based interaction pattern recognition and risk analysis. The Hidden Markov Model with the Gaussian mixture model (GMM-HMM) approach is developed to decompose the LC scenarios into primitives. Then K-means clustering with Dynamic Time Warping (DTW) is applied to gather the primitives into 13 LC interaction patterns. Finally, this study considers time-to-collision (TTC) of two conflict types involved in the LC process. And the TTC is used to analyze the risk of interaction patterns and extract high-risk LC interaction patterns. The LC events obtained from the Highway Drone Dataset (highD) demonstrate that the identified LC interaction patterns contain interpretable semantic information. This study identifies the dynamic spatiotemporal characteristics and risk formation mechanism of the LC interaction patterns. The findings are useful to comprehensively understand the latent interaction patterns, which can then be used to design and improve the decision-making process during lane changes and enhance the safety of autonomous vehicle.

Behavioral sciences

Spatiotemporal phenomena

interaction pattern

traffic risk

Lane change

Hidden Markov models

driving primitive

Autonomous vehicles

Vehicle dynamics




Yue Zhang

Tongji University

Yajie Zou

Tongji University

Selpi Selpi

Chalmers, Data- och informationsteknik, Data Science och AI

Yunlong Zhang

Texas A&M University

Lingtao Wu

IEEE Transactions on Intelligent Transportation Systems

1524-9050 (ISSN) 1558-0016 (eISSN)

Vol. 24 6 6663-6673

Heterogeneous Traffic Groups Cooperative Driving Behaviours Research under Mixed Traffic Condition

VINNOVA (2018-02891), 2019-04-01 -- 2021-03-31.


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