Many public transportation systems are unable to keep up with growing passenger demand as the population grows in urban areas. The slow or lack of improvements for public transportation pushes people to use private transportation modes, such as carpooling and ridesharing. However, the occupancy rate of personal vehicles has been dropping in many cities. In this paper, we describe a centralized transit system that integrates public transit and ridesharing, which matches drivers and transit riders such that the riders would result in shorter travel time using both transit and ridesharing. The optimization goal of the system is to assign as many riders to drivers as possible for ridesharing. We give an exact approach and approximation algorithms to achieve the optimization goal. As a case study, we conduct an extensive computational study to show the effectiveness of the transit system for different approximation algorithms, based on the real-world traffic data in Chicago City; the data sets include both public transit and ridesharing trip information. The experiment results show that our system is able to assign more than 60% of riders to drivers, leading to a substantial increase in occupancy rate of personal vehicles and reducing riders' travel time.
翻译:许多公共交通系统无法跟上城市地区人口增长带来的日益增长的客运需求。公共交通的缓慢或缺乏改善促使人们使用私人运输模式,如汽车搭配和搭车。然而,许多城市个人车辆的占用率一直在下降。本文描述了一个集中的过境系统,将公共交通和搭车结合起来,使司机和搭车者能够利用过境和搭车方式缩短旅行时间。该系统的最优化目标是尽可能多地为司机分配乘车司机。我们给出精确的方法和近似算法以实现优化目标。作为案例研究,我们进行了广泛的计算研究,以显示基于芝加哥市实际交通数据的不同近似算法的过境系统的有效性;数据集包括公共过境和搭车者的旅行信息。实验结果表明,我们的系统能够为司机分配超过60%的乘车者,导致个人车辆的占用率大幅提高,并缩短司机的旅行时间。