Optimization Algorithm Design for the Taxi-Sharing Problem and Application

Yongjie Wang,Maolin Li,Samuel Yousefi

doi:10.1155/2021/5572200

Abstract

With the development of mobility techniques, the transportation systems become smarter, pursuing higher goals, such as convenience for passengers and low cost. In this work, we investigate the taxi-sharing system, which is a promising system recently. The passengers can share the same taxis to different destinations to save cost. Considering the property of taxis’ routes, the corresponding model is established and our aim is to design the trip for each taxi to reduce the total number of taxi trips in the whole system if one taxi can be shared by several passengers. Compared with the previous work, we do not have any constraint about the taxi stations. The taxi trips have more flexibility in reality. We analyze this problem and prove it is NP-Complete. There are two proposed algorithms to solve this problem, one is a heuristic algorithm and the other is an approximate algorithm. In the experiment, two real-world taxi data sets are tested, and our algorithm shows the superiority of our taxi-sharing system. Using the taxi-sharing system, the number of trips can be reduced by about 30 % .

Highlights

In recent years, with the increment of traveling and commuting, the numbers of private cars and public transportation are increased
With the increased price of gas line and limited parking space, an efficient car-sharing system has been introduced to a large number of people. is system is a method to share one car with more than one passenger who can follow a common route to similar or close destinations [6]
There are some issues about this system, such as reservation strategy, passengers having to walk to the nearest parking lot, it can bring a lot of benefits. It makes the private transportation flexible, produce less pollution, and traffic congestion. erefore, it is becoming more and more popular, and people are willing to engage in this new mode of transportation

Summary

Introduction

With the increment of traveling and commuting, the numbers of private cars and public transportation are increased. Given the pick-up location, time, and destinations of passengers, it is still hard to schedule taxi drivers and dispatch the delivery tasks. En, in the delivery process, taxi drivers pick-up all the satisfied passengers without exceeding the limitation of passengers on a taxi This algorithm can be applied into the online setting. We first try to find all the possible taxi-sharing trips, which is a timeconsuming task in the raw data To speed up this process, we convert these passengers into a graph network. If the requirement of taxi-sharing becomes loose, such as waiting time, waiting locations, and the maximum number of passengers on a taxi, the reduction can be enlarger, especially when there are a very large number of trips within a short period.

Related Work

Problem Definition

Algorithm Design

Numerical Experiments

Findings

Conclusion and Future Work