A Matching Model for Door-to-Door Multimodal Transit by Integrating Taxi-Sharing and Subways
We present a sustainable multimodal transit system that integrates taxi-sharing with subways to alleviate traffic congestion and restore the cooperative relationship between taxis and subways. This study proposes a two-phase matching model based on optimization theory, in which pick-up/drop-off sequ...
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doaj-4619dd5b9eaf428380dad1d6ed880c1e2021-07-23T13:45:01ZengMDPI AGISPRS International Journal of Geo-Information2220-99642021-07-011046946910.3390/ijgi10070469A Matching Model for Door-to-Door Multimodal Transit by Integrating Taxi-Sharing and SubwaysRui Wang0Feng Chen1Xiaobin Liu2Xiaobing Liu3Zhiqiang Li4Yadi Zhu5School of Civil Engineering, Beijing Jiaotong University, Beijing 100044, ChinaSchool of Civil Engineering, Beijing Jiaotong University, Beijing 100044, ChinaBaidu.com Times Technology Co., Ltd., Beijing 100085, ChinaMOT Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, ChinaThe First Construction Engineering Company Ltd. of China Construction Second Engineering Bureau, Beijing 100176, ChinaSchool of Civil Engineering, Beijing Jiaotong University, Beijing 100044, ChinaWe present a sustainable multimodal transit system that integrates taxi-sharing with subways to alleviate traffic congestion and restore the cooperative relationship between taxis and subways. This study proposes a two-phase matching model based on optimization theory, in which pick-up/drop-off sequences for participants, as well as their motivation to shift to a TSS service, were considered. For the transportation system, achieving a reduction in vehicle miles is considered to be the matching objective. We tested the matching model using empirical taxi global positioning system (GPS) data for a typical morning rush hour in Beijing. The optimization model performs well for large-scale data and the optimal solution can be calculated quickly, which is ideal in a dynamic system. Furthermore, several sensitive analysis experiments were conducted to evaluate the performance of the TSS system. We found that approximately 23.13% of taxi users can be served by TSS transit, total taxi mileage can be reduced by 20.17%, and carbon dioxide emissions may be reduced by 15.16%. The proposed model and findings demonstrate that the TSS service considered here is a feasible multimodal transit mode, with the advantages of flexibility and sustainability, and has great potential for improving social benefits.https://www.mdpi.com/2220-9964/10/7/469taxi-sharingsubwaymultimodalmatching modelMaaS service |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Rui Wang Feng Chen Xiaobin Liu Xiaobing Liu Zhiqiang Li Yadi Zhu |
spellingShingle |
Rui Wang Feng Chen Xiaobin Liu Xiaobing Liu Zhiqiang Li Yadi Zhu A Matching Model for Door-to-Door Multimodal Transit by Integrating Taxi-Sharing and Subways ISPRS International Journal of Geo-Information taxi-sharing subway multimodal matching model MaaS service |
author_facet |
Rui Wang Feng Chen Xiaobin Liu Xiaobing Liu Zhiqiang Li Yadi Zhu |
author_sort |
Rui Wang |
title |
A Matching Model for Door-to-Door Multimodal Transit by Integrating Taxi-Sharing and Subways |
title_short |
A Matching Model for Door-to-Door Multimodal Transit by Integrating Taxi-Sharing and Subways |
title_full |
A Matching Model for Door-to-Door Multimodal Transit by Integrating Taxi-Sharing and Subways |
title_fullStr |
A Matching Model for Door-to-Door Multimodal Transit by Integrating Taxi-Sharing and Subways |
title_full_unstemmed |
A Matching Model for Door-to-Door Multimodal Transit by Integrating Taxi-Sharing and Subways |
title_sort |
matching model for door-to-door multimodal transit by integrating taxi-sharing and subways |
publisher |
MDPI AG |
series |
ISPRS International Journal of Geo-Information |
issn |
2220-9964 |
publishDate |
2021-07-01 |
description |
We present a sustainable multimodal transit system that integrates taxi-sharing with subways to alleviate traffic congestion and restore the cooperative relationship between taxis and subways. This study proposes a two-phase matching model based on optimization theory, in which pick-up/drop-off sequences for participants, as well as their motivation to shift to a TSS service, were considered. For the transportation system, achieving a reduction in vehicle miles is considered to be the matching objective. We tested the matching model using empirical taxi global positioning system (GPS) data for a typical morning rush hour in Beijing. The optimization model performs well for large-scale data and the optimal solution can be calculated quickly, which is ideal in a dynamic system. Furthermore, several sensitive analysis experiments were conducted to evaluate the performance of the TSS system. We found that approximately 23.13% of taxi users can be served by TSS transit, total taxi mileage can be reduced by 20.17%, and carbon dioxide emissions may be reduced by 15.16%. The proposed model and findings demonstrate that the TSS service considered here is a feasible multimodal transit mode, with the advantages of flexibility and sustainability, and has great potential for improving social benefits. |
topic |
taxi-sharing subway multimodal matching model MaaS service |
url |
https://www.mdpi.com/2220-9964/10/7/469 |
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