从出租车轨迹中提取司机经验并应用于大众出行引导是出租车轨迹数据的重要应用领域． 在经验提取上，为了避免传统方法中因忽视 OD 而导致结果不准确的问题，提
出了 OD 约束的经验模型(ODCEM)． 以深圳市为例，分别用传统的经验模型、ODCEM 及最短路径模型进行实验． 结果显示:ODCEM 在经验提取和路径推荐时能够成功地模拟出租车司机的经验;3 种方法的比较中，ODCEM 推荐的路径在通行时间和平均通行速度上体现出 93． 3%和 76． 7%以上的优势，通行长度位于其他两种模型推荐的路径之间． 最后对约束的尺度进行了讨论． 结果显示，约束尺度为 2km ×2km 时效果比较理想．

Extracting the driver's experience from taxi trajectories to guide the public travel is an important applica- tion of trajectory data.In order to avoid the inaccurate results caused by ignoring the origin and destination in the experience extracting process of traditional methods,this paper proposes an origin destination constraint experience model (ODCEM). Then,the traditional experience model,the ODCEM and the shortest path model are com- pared by the experiments in Shenzhen city.The results shows that (1) the ODCEM can successfully simulate the taxi driver's travel experience during the experience extracting and the path planning; (2) in comparison with the other two methods,the ODCEM increases the travel time and the speed respectively by more than 93. 3% and more than 76. 7%; and (3) the travel distance of the ODCEM is between those recommended by the other two methods.Finally,the influence of the constraint scale is discussed.It is found that the desirable constraint size is 2km ×2km.