中文摘要：

为设计一种能在保证准确率的条件下提高识别效率的驾驶人换道意图识别算法,分析驾驶人的换道决策,使用对驾驶人换道决策有影响的环境参数,设计了基于模糊逻辑理论的综合决策因子,反映驾驶人做出换道决策的可能性。提出一种基于隐Markov模型的换道意图识别算法,以综合决策因子与表征车辆横向运动的特征参数为观测变量,以驾驶人意图为隐状态,搭建并训练隐Markov模型,通过其解码方法实现驾驶人的换道意图识别。使用真实驾驶人在驾驶模拟器上进行换道的数据进行算法验证。结果表明：引入综合决策因子作为观测变量之一时,该换道意图识别算法能保证准确性并提高识别效率。

英文摘要：

An accurate lane change intention recognition algorithm is developed to improve real-time performance.The algorithm analyzes the drivers＇lane change decisions to develop a new symbol and a comprehensive decision index（CDI）based on fuzzy theory to assess the probability that the driver will change lanes.Then,the driver intention recognition algorithm is designed based on a hidden Markov model.Using the new symbol as well as representative lateral motion parameters as observed signals,and the driver＇s intention as the hidden state,a hidden Markov model is built and trained.The driver＇s intention is recognized by the HMM decoding method.Lane change data collected on a driving simulator are used to verify the overall algorithm performance.The results show that the algorithm with the CDI as one of the observation signals both guarantees the accuracy of the recognition results and improves the real-time performance.