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PoolLines: Modeling Carpooling as Ephemeral Lines in GTFS for Effective Integration with Public Transit

Youssef Chaabouni, André de Palma (), Andrea Araldo and Souhila Arib ()
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Souhila Arib: Université de Cergy-Pontoise, THEMA

No 2022-24, THEMA Working Papers from THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise

Abstract: In carpooling systems, a set of drivers owning a private car can accept a small detour to pick-up and drop-off other riders. However, carpooling is widely used for long-distance trips, where rider-driver matching can be done days ahead. Making carpooling a viable option for daily commute is more challenging, as trips are shorter and, proportionally, the detours tolerated by drivers are more tight. As a consequence, finding riders and drivers sharing close-enough origins, destinations and departure time is less likely, which limits potential matching. In this paper we propose an Integrated System, where carpooling matching is synchronized with Public Transit (PT) schedules, so as to serve as a feeder service to PT in the first mile. Driver detours are proposed towards PT selected stations, which are used as consolidation points, thus increasing matching probability. We present a computationally efficient method to represent PT schedules and drivers trajectory in a single General Transit Feed Specification database, which allows to compute multimodal rider journeys using any off the shelf planners. We showcase our approach in the metropolitan area of Portland, Oregon, considering 8k randomly generated trips. We show the benefits of our Integrated System. We find that 10% more riders find a feasible matching with respect to the status quo, where carpooling and PT are operated separately. We release our code as open source.

Keywords: Transportation; Carpooling; Public Transit; GTFS; Open Data. (search for similar items in EconPapers)
JEL-codes: R41 R48 (search for similar items in EconPapers)
Date: 2022
New Economics Papers: this item is included in nep-tre and nep-ure
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