Document Type
Technical Report
Publication Date
2-28-2024
Keywords
Ride-sharing, taxi, scheduling, congestion
Digital Object Identifier (DOI)
https://doi.org/10.5038/CUTR-NICR-Y3-2-8
Abstract
This research introduces practical optimization model for implementing ride-sharing in taxi services and studies the effects of ride-sharing on the congestion status through the case study of Chicago. Ride-sharing combines trips into one ride-shared trip with the objective of maximizing the total mileage saving. This research proposes a multi-stage model to optimize rider matches, aiming to reduce the total travel distance and enhance the matching of multiple riders. To validate the effectiveness of the model, real taxi data from Chicago is used, demonstrating significant improvements in distance reduction. Next, this study conduct congestion analysis by investigating the differences in congestion before and after the implementation of ridesharing mode. The traffic state is assessed through the computed congestion index before being graphically represented on congestion maps. After comparing the congestion map of community areas and census tracts before and after ride-sharing, we conclude that ride-sharing can improve the overall congestion status at the city level. This is particularly crucial given the increasing public awareness of environmental issues and the need for sustainable transportation solutions in cities.
Scholar Commons Citation
Quadrifoglio, Luca; Zhang, Cheng; Sun, Min-Ci; delle Monache, Maria Laura; and Yeo, Yuneil, "Multi-stage Models for Dynamic Ride-Sharing in Taxi Services and Congestion Analysis" (2024). Research Reports. 38.
https://digitalcommons.usf.edu/cutr_nicr/38
Policy brief
