An algorithm for integrating peer-to-peer ridesharing and schedule-based\n transit system for first mile/last mile access

Abstract

Due to limited transit network coverage and infrequent service, suburban\ncommuters often face the transit first mile/last mile (FMLM) problem. To deal\nwith this, they either drive to a park-and-ride location to take transit, use\ncarpooling, or drive directly to their destination to avoid inconvenience.\nRidesharing, an emerging mode of transportation, can solve the transit first\nmile/last mile problem. In this setup, a driver can drive a ride-seeker to a\ntransit station, from where the rider can take transit to her respective\ndestination. The problem requires solving a ridesharing matching problem with\nthe routing of riders in a multimodal transportation network. We develop a\ntransit-based ridesharing matching algorithm to solve this problem. The method\nleverages the schedule-based transit shortest path to generate feasible matches\nand then solves a matching optimization program to find an optimal match\nbetween riders and drivers. The proposed method not only assigns an optimal\ndriver to the rider but also assigns an optimal transit stop and a transit\nvehicle trip departing from that stop for the rest of the rider's itinerary. We\nalso introduce the application of space-time prism (STP) (the geographical area\nwhich can be reached by a traveler given the time constraints) in the context\nof ridesharing to reduce the computational time by reducing the network search.\nAn algorithm to solve this problem dynamically using a rolling horizon approach\nis also presented. We use simulated data obtained from the activity-based\ntravel demand model of Twin Cities, MN to show that the transit-based\nridesharing can solve the FMLM problem and save a significant number of\nvehicle-hours spent in the system.\n