Developing Optimal Peer-to-Peer Ridesharing Strategies

Lee, Young-Jae; Nickkar, Amirezza

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Developing Optimal Peer-to-Peer Ridesharing Strategies

2023-08-01
By Lee, Young-Jae ; Nickkar, Amirezza

File Language:

English

Details

Creators:

Lee, Young-Jae ; Nickkar, Amirezza
Corporate Creators:

Morgan State University ; Urban Mobility & Equity Center
Corporate Contributors:

United States. Department of Transportation. University Transportation Centers (UTC) Program ; United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology
Subject/TRT Terms:
Publication/ Report Number:

UMEC-022
Resource Type:

Tech Report
Geographical Coverage:

United States
Edition:

Final Report
Corporate Publisher:

Urban Mobility & Equity Center
Abstract:

Thanks to recent developments in ride-hailing transit services, the Peer-to-Peer (P2P) ride-matching problem has been actively considered in academia in recent years. P2P ride-matching not only reduces travel costs for riders but also benefits drivers by saving them money in exchange for their additional travel time and costs. However, assigning riders to drivers in an efficient way is a complex problem that requires a focus on maximizing the benefits for both riders and drivers. This study first aims to formulate a multi-driver multi-rider (MDMR) P2P ride-matching problem based on rational preferences and cost allocation for both driver and rider. This model also enables riders to transfer between multiple drivers to complete their journeys if needed. To solve the ride-matching problem, a Tabu Search (TS) for system optimum ride-matchings and Greedy Matching (GM) algorithm for the stable ride-matchings were created to produce stable ride-matchings.
Format:

PDF
Funding:

69A43551747123
Download URL:

https://rosap.ntl.bts.gov/view/dot/68858/dot_68858_DS1.pdf
File Type:

[PDF - 1.59 MB]
Collection(s):

University Transportation Centers
Main Document Checksum:

urn:sha-512:695e9184a690667569f8fdfaa278e4ddf741f4f81cb971f33acb489edcf21fa1d2da44ad8534cb3972146dfae1f9f0c9aaba4f769d278697621d22e601ac9537

File Language:

English

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