为提高合乘匹配概率和合乘满意度，提出一种考虑乘客合乘时间-价格弹性的动态合乘匹配方法。采用RP+SP（综合显示性偏好+陈述偏好）问卷调查方法，收集用户的个体属性、不同场景出行下的合乘与非合乘方式选择行为。根据用户合乘偏好进行聚类，将乘客分为3类，建立非集计弹性分析模型，得到3种类别乘客的合乘、非合乘的时间-价格弹性值，并将时间-价格弹性纳入到出行成本中，建立所有乘客和司机的广义成本函数。然后构建双层规划模型，其中上层模型考虑司机和出行者的效益，下层模型以系统内所有乘客的选择概率最大为目标；考虑路径约束和载客量约束，设计合乘匹配算法。最后，以西安市出租车数据为例，分别对系统内乘客具有不同合乘弹性值时的匹配方案进行求解，并比较匹配方案的差异性。结果表明：当乘客具有较高的合乘弹性值（2.22和0.99）时，其非合乘成本低于合乘成本，系统无法进行有效的合乘匹配；当乘客具有较低的合乘弹性值（0.12）时，可将多个乘客与其匹配。研究结论证明了合乘弹性的必要性，可用于指导政府部门的网约车、出租车的订单分配和调度。

In order to improve the carpooling matching probability and satisfaction, this paper proposed a dynamic carpooling matching method that considering passengers’ time-price elasticity. RP+SP(Revealed Preference + Stated Preference) questionnaire survey method was adopted to collect passengers’ individual attributes and carpooling choosing behavior under different travel scenarios. Clustering passengers based on the carpooling prefe-rences, passengers were divided into three categories. A discrete elasticity analysis model was established to obtain the time-price elasticity of carpooling and non-carpooling passengers for the three categories. Incorporating time-price elasticity into travel costs, a generalized cost function was established for all passengers and drivers. Then a two-level planning model was constructed, for which, the upper-level model considered the benefits of drivers and passengers, while the lower-level model aimed to maximize the carpooling probability of all passengers. A carpooling matching algorithm was designed considering route and capacity constraints. Finally, taking taxi trajectory data of Xi’an as a case study, matching schemes were solved under varying levels of carpooling elasticity among passengers within the system, and the differences between the resulting matching schemes were compared and analyzed. The results indicate that when passengers have higher time-price elasticity values (2.22, 0.99), their non-carpooling costs are lower than those of carpooling, making effective matching infeasible. In contrast, when passengers have lower time-price elasticity value (0.12), multiple passengers can be successfully matched. These findings demonstrate the necessity of considering carpooling elasticity and can serve as a reference for government agencies in the order allocation and dispatching of ride-hailing and taxi services.