Abstract

Public Bicycle System (PBS) has been developed for short-distance transportation as a part of the mass transportation system. The supply and demand of bikes in PBS is usually unbalanced at different stations and needs to be continuously and widely monitored and redistributed. The bicycle redistribution is a part of the vehicle routing problem (VRP). We can apply solutions to the VRP to redistribute bicycle efficiently. However, most solutions to the VRP use the Euclidean distance as the condition factor, which does not take road conditions, traffic regulations, and geographical factors into account, resulting in unnecessary waste of delivery time and human resources. In this work, we propose an actual path distance optimization method for the VRP to adapt the several additional constraints of road problems. We also implement a system that integrates real-time station information, Web GIS, the urban road network, and heuristics algorithms for PBS. The system includes a simulator inside that can assist PBS managers to do the route planning efficiently and find the best scheduling strategy to achieve hotspot analysis and the adjustment of station deployment strategies to reduce PBS operation cost.

Highlights

  • In recent years, issues on carbon emission and energy saving have been taken seriously

  • The bicycle redistribution is a part of the vehicle routing problem (VRP)

  • They proposed a spatial decision support system based on the Web aiming to generate optimized trash collection routes for capacitated arc routing problem (CARP) that involves serving the demand, respectively, about a set of arcs on an urban road network

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Summary

A Geo-Aware and VRP-Based Public Bicycle Redistribution System

Public Bicycle System (PBS) has been developed for short-distance transportation as a part of the mass transportation system. The bicycle redistribution is a part of the vehicle routing problem (VRP). We can apply solutions to the VRP to redistribute bicycle efficiently. Most solutions to the VRP use the Euclidean distance as the condition factor, which does not take road conditions, traffic regulations, and geographical factors into account, resulting in unnecessary waste of delivery time and human resources. We implement a system that integrates real-time station information, Web GIS, the urban road network, and heuristics algorithms for PBS. The system includes a simulator inside that can assist PBS managers to do the route planning efficiently and find the best scheduling strategy to achieve hotspot analysis and the adjustment of station deployment strategies to reduce PBS operation cost

Introduction
Related Work
The Actual Path Distance Optimization Method
System Design and Implementation
10 Figure 12
Experimental Results
Conclusions
Full Text
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