Professor Guangwen Kong

CSENG Industrial&Systems Eng
College of Science & Engineering
Twin Cities
Project Title: 
Management of On-demand Platform

Recently, there has been a rapid rise of on-demand ride-hailing platforms, such as Uber and Didi, which allow passengers with smartphones to submit trip requests and match them to drivers based on their locations and drivers' availability. This increased demand has raised questions about how such a new matching mechanism will affect the efficiency of the transportation system, particularly whether it will help reduce passengers' average waiting time compared to traditional street-hailing systems. This project addresses this question by building a stylized model of a circular road and comparing the average waiting times of passengers under various matching mechanisms. After identifying key tradeoffs between different mechanisms, it is found that, surprisingly, the on-demand matching mechanism could result in higher or lower efficiency than the traditional street-hailing mechanism, depending on the parameters of the system. To overcome the disadvantage of both systems, this project will next add response caps to the on-demand hailing mechanism and develop a heuristic method to calculate a near-optimal cap. The model is tested using more complex road networks to show that the key observations still exist.

Project Investigators

Guiyun Feng
Professor Guangwen Kong
Xiangzhen Kong
Yuanchen Su
 
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