江苏大学学报（自然科学版）2026，Vol.47Issue(5)：497-505,516,10.DOI:10.3969/j.issn.1671-7775.2026.05.001
基于DRHMM的高速公路场景车辆换道意图识别方法
Vehicle lane-changing intention recognition method in highway scenarios based on DRHMM
摘要
Abstract
To address the issues of poor generalization,susceptibility to catastrophic forgetting and degraded recognition performance due to imbalanced sample distribution in traditional vehicle lane-changing intention vecognition models under dynamic high-speed driving scenarios,the dynamic replay hidden Markov model(DRHMM)integrating experience replay strategy was proposed.Based on the NGSIM I-80 highway dataset,three types of valid trajectories including straight driving,left lane-changing and right lane-changing were extracted through trajectory splicing and reconstruction.Using Gaussian distribution parameter fitting,the lateral displacement and lateral velocity were selected as input features for the model.The experience replay strategy was introduced into the Gaussian mixture model-hidden Markov model(GMM-HMM)framework,and the experience replay buffer was constructed to store historical training samples.By mixing the new and old samples during training,the catastrophic model forgetting was suppressed,and the adaptability to dynamic driving environments was enhanced.The sliding time window of 3.00 s was set to conduct the comparative experiments among three models of HMM,GMM-HMM and DRHMM.The results show that by the DRHMM,the lane-changing intention recognition accuracy of 92.99％is achieved with recognition delay of only 0.69 s,which demonstrates significantly better overall performance than the comparison models.关键词
车辆/高速公路场景/换道意图识别/DRHMM/经验回放策略/轨迹数据Key words
vehicle/highway scenarios/lane-changing intention recognition/DRHMM/experience replay strategy/trajectory data分类
交通工程引用本文复制引用
李胜琴,宫圣鑫..基于DRHMM的高速公路场景车辆换道意图识别方法[J].江苏大学学报（自然科学版）,2026,47(5):497-505,516,10.基金项目
黑龙江省自然科学基金资助青年项目A类(JQ2025E002) （JQ2025E002）
黑龙江省"双一流"学科协同创新成果项目(LJGXCG2023-107) （LJGXCG2023-107）
