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Driving Intention Recognition Based on Gaussian Mixture-Hidden Markov Model
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Yu Shen1, 2, Guanghui Liu2, Xuanpeng Ma1, Jiawen Xu2, Yuan Yan2
Automobile Technology | 2025, (5) : 22 - 28
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Automobile Technology | 2025, (5): 22-28
Driving Intention Recognition Based on Gaussian Mixture-Hidden Markov Model
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Yu Shen1, 2, Guanghui Liu2, Xuanpeng Ma1, Jiawen Xu2, Yuan Yan2
Affiliations
  • 1 School of Information Engineering, Gansu Minzu Normal University, Hezuo 747000
  • 2 School of Electronic and Information Engineering, Lanzhou Jiaotong University, Lanzhou 730070
Published: 2025-05-24 doi: 10.19620/j.cnki.1000-3703.20231201
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To achieve accurate recognition of vehicle driving intentions in highway scenarios, this paper proposes a driving intention recognition model that combines dual reference lines in the Frenet coordinate with Gaussian Mixture Models (GMMs) and Hidden Markov Models (HMMs). The model selects driving data from different reference lines in the Frenet coordinate based on vehicle position as observed variables. By integrating the observation probabilities output by the GMM at previous and subsequent time steps with the HMM, the model identifies the vehicles’ driving intention at the current moment. The effectiveness of the model is validated using the US-101 dataset from NGSIM. The results show that the dual-reference-line GMM-HMM model achieves recognition accuracies of 93.33% for lane keeping and 92.24% for lane changing, indicating excellent recognition performance.

Autonomous driving  /  Driving intention recognition  /  Gaussian Mixture Model (GMM)  /  Hidden Markov Model (HMM)  /  Frenet coordinate
Yu Shen, Guanghui Liu, Xuanpeng Ma, Jiawen Xu, Yuan Yan. Driving Intention Recognition Based on Gaussian Mixture-Hidden Markov Model[J]. Automobile Technology, 2025 , (5) : 22 -28 . DOI: 10.19620/j.cnki.1000-3703.20231201
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doi: 10.19620/j.cnki.1000-3703.20231201
  • Online Date：2025-11-14
  • Published：2025-05-24
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  • Revised：2025-01-26
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    1 School of Information Engineering, Gansu Minzu Normal University, Hezuo 747000
    2 School of Electronic and Information Engineering, Lanzhou Jiaotong University, Lanzhou 730070
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