Promoting Peer-to-Peer Ridesharing Services as Transit System Feeders

Jayakrishnan, R.; Masoud, Neda; Jiangbo, Yu; Nam, Daisik · 2016 · ROSA P / California. Department of Transportation

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Summary

This study investigates the potential of peer-to-peer (P2P) ridesharing to augment public transit ridership rather than cannibalizing it, addressing the challenge of declining transit usage and urban congestion. The authors focus on the Los Angeles Metro Red Line, which has experienced recent ridership declines, as a case study. The core objective is to determine if efficient, real-time ride-matching algorithms can shift demand from private automobiles to a multi-modal transit-rideshare system, thereby reducing greenhouse gas emissions and vehicle congestion. To achieve this, the researchers developed a mobile application featuring a dynamic programming (DP) algorithm capable of solving complex, multi-hop ride-matching problems in real-time. Unlike traditional systems that pair single riders with single drivers, this algorithm allows drivers to carry multiple passengers and facilitates transfers between rideshare vehicles and fixed transit lines. The system architecture defines specific "go-points" for trip origins and destinations, and "transfer points" for switching modes, identified using Southern California Association of Governments (SCAG) travel demand data. The DP algorithm operates on a time-expanded network, optimizing routes based on a cost function that includes distance-based fares, value of travel time, and penalties for waiting and transfers. The study utilized parametric simulations with 1,000 riders and varying numbers of drivers (from 1,000 to 80,000) to assess matching rates and system performance. Results indicated that the percentage of served riders increased with driver supply, though at a diminishing rate. The proportion of riders utilizing the transit-rideshare option peaked at approximately 20,000 drivers. While the absolute percentage of drive-alone trips shifting to transit-rideshare was modest (around 1.7%), this translates to a significant volume of additional passengers; for instance, it could add roughly 250 passengers per train on the Red Line during peak hours. The analysis also revealed that multi-hop routes involving transfers were most prevalent at intermediate supply levels, with most riders experiencing zero or one transfer. The findings suggest that strategically designed P2P ridesharing services can effectively serve as feeders for transit systems, capturing demand from private auto users. The study concludes that the success of such systems depends heavily on system architecture, including the strategic placement of transfer points and dynamic pricing structures. By integrating ridesharing with fixed transit routes through advanced matching algorithms, cities can potentially reverse transit ridership declines and reduce reliance on single-occupancy vehicles.

Key finding

Simulations showed that with 20,000 drivers, the system achieved peak utilization of the transit-rideshare option, potentially adding approximately 12,500 additional passengers to the LA Metro Red Line during morning peak hours.

Methodology

modeling

Provenance

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Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.

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