Mathematical Modeling and Parameter Estimation of Lane-Changing Vehicle Behavior Decisions

Jianghui Wen, Yebei Xu, Min Dai () and Nengchao Lyu
Additional contact information
Jianghui Wen: School of Mathematics and Statistics, Wuhan University of Technology, Wuhan 430070, China
Yebei Xu: School of Mathematics and Statistics, Wuhan University of Technology, Wuhan 430070, China
Min Dai: School of Mathematics and Statistics, Wuhan University of Technology, Wuhan 430070, China
Nengchao Lyu: Intelligent Transportation Systems Research Center, Wuhan University of Technology, Wuhan 430070, China

Mathematics, 2025, vol. 13, issue 6, 1-20

Abstract: Lane changing is a crucial scenario in traffic environments, and accurately recognizing and predicting lane-changing behavior is essential for ensuring the safety of both autonomous vehicles and drivers. Through considering the multi-vehicle information interaction characteristics in lane-changing behavior for vehicles and the impact of driver experience needs on lane-changing decisions, this paper proposes a lane-changing model for vehicles to achieve safe and comfortable driving. Firstly, a lane-changing intention recognition model incorporating interaction effects was established to obtain the initial lane-changing intention probability of the vehicles. Secondly, by accounting for individual driving styles, a lane-changing behavior decision model was constructed based on a Gaussian mixture hidden Markov model (GMM-HMM) along with a parameter estimation method. The initial lane-changing intention probability serves as the input for the decision model, and the final lane-changing decision is made by comparing the probabilities of lane-changing and non-lane-changing scenarios. Finally, the model was validated using real-world data from the Next Generation Simulation (NGSIM) dataset, with empirical results demonstrating its high accuracy in recognizing and predicting lane-changing behavior. This study provides a robust framework for enhancing lane-changing decision making in complex traffic environments.

Keywords: lane changing behavior; lane-changing intention recognition model; Gaussian mixture hidden Markov model; parameter estimation; lane-changing decision (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2025
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2227-7390/13/6/1014/pdf (application/pdf)
https://www.mdpi.com/2227-7390/13/6/1014/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:13:y:2025:i:6:p:1014-:d:1616735

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().