Tuesday, November 14, 2023 | 12:00 – 1:00 PM (ET)
About the Webinar:
This research introduces a 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 savings. 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 conducts 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.
About the Presenter:
Min-Ci Sun is a doctoral student at Texas A&M University with interests in transportation planning and modeling, traffic assignment, transportation optimization, and evacuation planning. In 2021, Min-Ci earned a Master of Science degree in civil engineering from National Taiwan University. At Central Police University, he obtained a Bachelor of Science in traffic science.
Yuneil Yeo is a doctoral student at the University of California, Berkeley with interests in transportation networks, optimization and control, and intelligent transportation systems. Yuneil completed his master’s degree in advanced infrastructure systems (2020) and his bachelor’s degree in civil engineering (2019) at Carnegie Mellon University.
Cheng Zhang is a doctoral student at Texas A&M University with interests in transportation planning and modeling, scheduling and optimization, and intelligent transportation systems. He completed a master’s degree in civil and environmental engineering at Carnegie Mellon University in 2019. Cheng earned a bachelor’s degree in engineering management from Chang’an University in 2015.