Volume 2: Innovative Solutions for Energy Transitions: Part I

GPS Data in Urban Online Car-Hailing: The Potential Reduction of Invalid Emission by A Stochastic Optimization-Based Smart Matching System Haoran Zhang* , Jinyu Chen , Wenjing Li , Qiong Zhang , Yin Long , Xuan Song , Ryosuke Shibasaki

Abstract

Online ride-hailing is an emerging and popular transportation mode under the framework of sharing economy. Its emission issue has been focused by researchers for seeking a clean and efficient way to service passengers. In this paper, we based on stochastic optimization to proposed a smart matching method. The GPS dataset of Didi company in Chengdu city is employed to test the method. Compared with the shortest distance based matching method, the proposed method is able to reduce the invalid emission rate from 0.2834 to 0.2554 which proves the practicability of our method.

Keywords GPS data, online car-hailing, invalid emission, stochastic optimization, matching system