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A new ride‐sharing model incorporating the passengers' efforts
Author(s) -
Yao Danli,
He Simai,
Wang Zhen
Publication year - 2021
Publication title -
naval research logistics (nrl)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.665
H-Index - 68
eISSN - 1520-6750
pISSN - 0894-069X
DOI - 10.1002/nav.21965
Subject(s) - carpool , computer science , notice , robustness (evolution) , operations research , travel time , bike sharing , service (business) , transport engineering , engineering , business , marketing , biochemistry , chemistry , law , political science , gene
Abstract We address a novel ride‐sharing model aiming to improve the quality of carpool services, by means of incorporation of passengers' efforts. In densely populated areas, locating and picking up passengers are often time costly. These phenomena, which are rarely considered in literature, will hurdle the service efficiency of ride‐sharing businesses by a significant amount, and contribute to the performance gap between theoretical estimation and practical performance. We notice that major platforms, such as DiDi, Uber, and Lyft are all starting innovative ways to encourage passengers to take efforts to walk to the assigned stations. We present a static optimization model for the planning stage of the service and establish an estimation of the carpooling rate for each station together with robustness consideration. In addition, we provide simple and efficient optimization algorithms with theoretical performance guarantee. At the same time, we conduct simulation studies based on both random generated data and open accessible data from DiDi. By applying our model and algorithm to the data of DiDi, we can achieve carpooling rates of 90% while passengers are located within an average radius of 250 m spending an extra waiting time of less than 3 min for their shared rides during rush hour.