Department of Civil Engineering, Bogazici University, Istanbul, Turkey.
Department of Civil Engineering, Turkish-German University, Istanbul, Turkey.
PLoS One. 2020 Mar 4;15(3):e0229674. doi: 10.1371/journal.pone.0229674. eCollection 2020.
Increasing traffic congestion and the advancements in technology have fostered the growth of alternative transportation modes such as dynamic ride-sharing. Smartphone technologies have enabled dynamic ride-sharing to thrive, as this type of transportation aims to establish ride matches between people with similar routes and schedules on short notice. Many automated matching methods are designed to improve system performance; such methods include minimizing process time, minimizing total system cost or maximizing total distance savings. However, the results may not provide the maximum benefits for the participants. This paper intends to develop an algorithm for optimizing matches when considering participants' gender, age, employment status and social tendencies. The proposed matching algorithm also splits unmatched parts of drivers' routes and creates new travel requests to find additional matches using these unmatched parts. Accordingly, this paper performs an extensive simulation study to assess the performance of the proposed algorithm. The simulation results indicate that route splits may increase the number of matches significantly when there is a shortage of drivers. Furthermore, the paper demonstrates the effects and potential benefits of utilizing a social compatibility score in the objective function.
交通拥堵的加剧和技术的进步促进了替代交通方式的发展，如动态拼车。智能手机技术使动态拼车得以蓬勃发展，因为这种交通方式旨在在短时间内为具有相似路线和日程安排的人建立乘车匹配。许多自动化匹配方法旨在提高系统性能；例如，方法包括最小化处理时间、最小化总成本或最大化总距离节省。然而，结果可能不会为参与者带来最大的利益。本文旨在开发一种算法，用于在考虑参与者的性别、年龄、就业状况和社会趋势时优化匹配。所提出的匹配算法还会拆分驾驶员路线中不匹配的部分，并使用这些不匹配的部分创建新的出行请求以找到更多匹配。因此，本文进行了广泛的模拟研究来评估所提出算法的性能。模拟结果表明，当司机短缺时，路线拆分可能会显著增加匹配数量。此外，本文还展示了在目标函数中使用社交兼容性评分的效果和潜在好处。
