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Matching algorithm for improving ride-sharing by incorporating route splits and social factors.
Omer Faruk Aydin1,2, Ilgin Gokasar1, Onur Kalan3
1Department of Civil Engineering, Bogazici University, Istanbul, Turkey.
Plos One
|March 5, 2020
Summary
This study introduces a new algorithm for dynamic ride-sharing that optimizes matches based on participant characteristics and route splitting. This approach significantly increases ride matches, especially when driver supply is low.
Area of Science:
- Transportation Science
- Computer Science
- Sociology
Background:
- Rising traffic congestion and technological advancements drive the need for alternative transportation.
- Dynamic ride-sharing leverages smartphone technology for on-demand ride matching.
- Existing matching algorithms often prioritize system efficiency over participant benefits.
Purpose of the Study:
- To develop an optimized matching algorithm for dynamic ride-sharing.
- To incorporate participant demographics and social tendencies into the matching process.
- To enhance ride-sharing efficiency by splitting routes and creating new requests.
Main Methods:
- Development of a novel matching algorithm considering gender, age, employment, and social tendencies.
- Implementation of a route-splitting strategy for unmatched route segments.
- Extensive simulation study to evaluate algorithm performance.
Main Results:
- The proposed algorithm significantly increases the number of successful ride matches.
- Route splitting proves effective in boosting matches, particularly during driver shortages.
- Incorporating a social compatibility score enhances the objective function's potential benefits.
Conclusions:
- The developed algorithm offers a more participant-centric approach to dynamic ride-sharing.
- Route splitting is a viable strategy to improve ride-sharing system utilization.
- Social compatibility is a key factor for maximizing participant satisfaction in ride-sharing.
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