关键词: 城市交通运输, 合乘匹配, 弹性分析, 双层规划模型

Abstract:

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.

Key words: urban transportation, carpooling matching, elasticity analysis, two-level planning model