Identification of Metro-Bikeshare Transfer Trip Chains by Matching Docked Bikeshare and Metro Smartcards

Xinwei Ma,Minqing Zhu,Yufei Yuan,Yuchuan Jin,Shuai Zhang

doi:10.3390/en15010203

Xinwei Ma, Minqing Zhu + Show 3 more

Open Access

https://doi.org/10.3390/en15010203

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Abstract

Metro-bikeshare integration, an important way of improving the efficiency of public transportation, has grown rapidly during the last decades in many countries. However, most previous analysis of metro-bikeshare transfer trips were based on limited sample size and the number of recognized metro-bikeshare trips were not sufficient. The primary objective of this study is to derive a method to recognize metro-bikeshare transfer trips. The two data sources are provided by Nanjing Metro Company and Nanjing Public Bicycle Company over the same period from 9–29 March 2016. The identifying method includes three steps: (1) Matching Card Pairs (2) Filtering Card Pairs and (3) Identifying Card Pairs. The case study indicates that the Support Vector Classification (SVC) performs best with a high prediction accuracy of 95.9% using seamless smartcards. The identifying method is then used to recognize the transfer trips from other types of cards, resulting in 17,022 valid metro-bikeshare transfer trips made by 2948 travelers. Finally, travel patterns extracted from the two groups of identified transfer trips are analyzed comparatively. The method proposed presents new opportunities for analyzing metro-bikeshare transfer trip characteristics.

Highlights

Due to the heavy reliance on the automobile, several problems such as traffic congestion, air pollution, respiratory health issues and climate change have been caused around the world [1,2,3]
Bikeshare smartcards used in Nanjing fall into two categories: seamless smartcards that are sold by Nanjing Metro Company and dedicated bikeshare cards that are released by Nanjing Public Bicycle Company
As a basic element in the algorithm, we introduce a concept called Card Pair, which describes the potential connection between two smartcard types according to two attributes: maximal transfer time and transfer distance

Summary

Introduction

Due to the heavy reliance on the automobile, several problems such as traffic congestion, air pollution, respiratory health issues and climate change have been caused around the world [1,2,3]. To reduce energy consumption and air pollution, the construction or extension of an existing metro system with sufficient capacity is often promoted [4]. The metro network cannot be too dense regarding the feeding of traffic demand, especially in the suburban areas of a city, due to the high construction costs and low service efficiency [5]. Transit use is affected by the first mile/last mile problems [6], by the access/egress distances between metro stations and trip origin/destination locations that are greater than that which travelers are typically willing to walk [7]. The combination of bikes and metro is considered as a competitive alternative to private cars and feeder buses, because of the seamless connections [9,10,11]

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