Optimization of bus lines based on passenger group moving behaviors

Syed Muhammad Asim Ali Rizvi; Weifeng Lv; Bowen Du; Zhipu Xie; Runhe Huang

doi:10.1109/SmartWorld.2018.00044

Optimization of bus lines based on passenger group moving behaviors

Syed Muhammad Asim Ali Rizvi
, Weifeng Lv
, Bowen Du^*
, Zhipu Xie
, Runhe Huang

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Scopus citations

Abstract

Optimization of public bus routes in a transportation system is one of the keys to achieve smart city concept, delivers better quality, and cost-saving travel to the passengers. Compared to private vehicles, public transportation system has been chosen by millions of passengers each day with different routes, generates certain travel patterns. From these travel patterns, routes are optimized by the transportation experts to reduce the gap between existing routes and travel demands. Thus, the transportation system is depending upon experts to optimize it manually. This paper focuses on discovering the mobility pattern of passengers with buses and subways to optimize the routes of Beijing. To this end, we first illustrate the changes in certain bus lines by the experts in a specific interval of time during a year and their impact. Based upon mobility features, we propose Group Travel Demand Identification (GTDI) method that suggests the route adjustments for optimization of bus lines. We also demonstrate a comparison of our method with other optimization techniques. Route forecasting results are matched with the adjustments of experts to validate the performance and reliability, To solve route adjustment problem, we conducted an extensive study on sets of data records and adjustment records of bus lines collected from Beijing Public Transport Corporation (BPTC). To generate mobility pattern from Smart Card Data, we studied more than 845 million passengers.

Original language	English
Title of host publication	Proceedings - 2018 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovations, SmartWorld/UIC/ATC/ScalCom/CBDCom/IoP/SCI 2018
Editors	Frederic Loulergue, Guojun Wang, Md Zakirul Alam Bhuiyan, Xiaoxing Ma, Peng Li, Manuel Roveri, Qi Han, Lei Chen
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	53-60
Number of pages	8
ISBN (Electronic)	9781538693803
DOIs	https://doi.org/10.1109/SmartWorld.2018.00044
State	Published - 4 Dec 2018
Event	4th IEEE SmartWorld, 15th IEEE International Conference on Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovations, SmartWorld/UIC/ATC/ScalCom/CBDCom/IoP/SCI 2018 - Guangzhou, China Duration: 7 Oct 2018 → 11 Oct 2018

Publication series

Name	Proceedings - 2018 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovations, SmartWorld/UIC/ATC/ScalCom/CBDCom/IoP/SCI 2018

Conference

Conference	4th IEEE SmartWorld, 15th IEEE International Conference on Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovations, SmartWorld/UIC/ATC/ScalCom/CBDCom/IoP/SCI 2018
Country/Territory	China
City	Guangzhou
Period	7/10/18 → 11/10/18

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 11 Sustainable Cities and Communities

Keywords

Group Passengers Bus line Optimization
Route Prediction
Smart Transportation
Transport Planning
Transportation Mobility Patterns

Access to Document

10.1109/SmartWorld.2018.00044

Cite this

Rizvi, S. M. A. A., Lv, W., Du, B., Xie, Z., & Huang, R. (2018). Optimization of bus lines based on passenger group moving behaviors. In F. Loulergue, G. Wang, M. Z. A. Bhuiyan, X. Ma, P. Li, M. Roveri, Q. Han, & L. Chen (Eds.), Proceedings - 2018 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovations, SmartWorld/UIC/ATC/ScalCom/CBDCom/IoP/SCI 2018 (pp. 53-60). Article 8560022 (Proceedings - 2018 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovations, SmartWorld/UIC/ATC/ScalCom/CBDCom/IoP/SCI 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SmartWorld.2018.00044

Rizvi, Syed Muhammad Asim Ali ; Lv, Weifeng ; Du, Bowen et al. / Optimization of bus lines based on passenger group moving behaviors. Proceedings - 2018 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovations, SmartWorld/UIC/ATC/ScalCom/CBDCom/IoP/SCI 2018. editor / Frederic Loulergue ; Guojun Wang ; Md Zakirul Alam Bhuiyan ; Xiaoxing Ma ; Peng Li ; Manuel Roveri ; Qi Han ; Lei Chen. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 53-60 (Proceedings - 2018 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovations, SmartWorld/UIC/ATC/ScalCom/CBDCom/IoP/SCI 2018).

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title = "Optimization of bus lines based on passenger group moving behaviors",

abstract = "Optimization of public bus routes in a transportation system is one of the keys to achieve smart city concept, delivers better quality, and cost-saving travel to the passengers. Compared to private vehicles, public transportation system has been chosen by millions of passengers each day with different routes, generates certain travel patterns. From these travel patterns, routes are optimized by the transportation experts to reduce the gap between existing routes and travel demands. Thus, the transportation system is depending upon experts to optimize it manually. This paper focuses on discovering the mobility pattern of passengers with buses and subways to optimize the routes of Beijing. To this end, we first illustrate the changes in certain bus lines by the experts in a specific interval of time during a year and their impact. Based upon mobility features, we propose Group Travel Demand Identification (GTDI) method that suggests the route adjustments for optimization of bus lines. We also demonstrate a comparison of our method with other optimization techniques. Route forecasting results are matched with the adjustments of experts to validate the performance and reliability, To solve route adjustment problem, we conducted an extensive study on sets of data records and adjustment records of bus lines collected from Beijing Public Transport Corporation (BPTC). To generate mobility pattern from Smart Card Data, we studied more than 845 million passengers.",

keywords = "Group Passengers Bus line Optimization, Route Prediction, Smart Transportation, Transport Planning, Transportation Mobility Patterns",

author = "Rizvi, \{Syed Muhammad Asim Ali\} and Weifeng Lv and Bowen Du and Zhipu Xie and Runhe Huang",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 4th IEEE SmartWorld, 15th IEEE International Conference on Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovations, SmartWorld/UIC/ATC/ScalCom/CBDCom/IoP/SCI 2018 ; Conference date: 07-10-2018 Through 11-10-2018",

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doi = "10.1109/SmartWorld.2018.00044",

language = "英语",

series = "Proceedings - 2018 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovations, SmartWorld/UIC/ATC/ScalCom/CBDCom/IoP/SCI 2018",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "53--60",

editor = "Frederic Loulergue and Guojun Wang and Bhuiyan, \{Md Zakirul Alam\} and Xiaoxing Ma and Peng Li and Manuel Roveri and Qi Han and Lei Chen",

booktitle = "Proceedings - 2018 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovations, SmartWorld/UIC/ATC/ScalCom/CBDCom/IoP/SCI 2018",

address = "美国",

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Rizvi, SMAA, Lv, W , Du, B, Xie, Z & Huang, R 2018, Optimization of bus lines based on passenger group moving behaviors. in F Loulergue, G Wang, MZA Bhuiyan, X Ma, P Li, M Roveri, Q Han & L Chen (eds), Proceedings - 2018 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovations, SmartWorld/UIC/ATC/ScalCom/CBDCom/IoP/SCI 2018., 8560022, Proceedings - 2018 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovations, SmartWorld/UIC/ATC/ScalCom/CBDCom/IoP/SCI 2018, Institute of Electrical and Electronics Engineers Inc., pp. 53-60, 4th IEEE SmartWorld, 15th IEEE International Conference on Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovations, SmartWorld/UIC/ATC/ScalCom/CBDCom/IoP/SCI 2018, Guangzhou, China, 7/10/18. https://doi.org/10.1109/SmartWorld.2018.00044

Optimization of bus lines based on passenger group moving behaviors. / Rizvi, Syed Muhammad Asim Ali; Lv, Weifeng ; Du, Bowen et al.
Proceedings - 2018 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovations, SmartWorld/UIC/ATC/ScalCom/CBDCom/IoP/SCI 2018. ed. / Frederic Loulergue; Guojun Wang; Md Zakirul Alam Bhuiyan; Xiaoxing Ma; Peng Li; Manuel Roveri; Qi Han; Lei Chen. Institute of Electrical and Electronics Engineers Inc., 2018. p. 53-60 8560022 (Proceedings - 2018 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovations, SmartWorld/UIC/ATC/ScalCom/CBDCom/IoP/SCI 2018).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Optimization of bus lines based on passenger group moving behaviors

AU - Rizvi, Syed Muhammad Asim Ali

AU - Lv, Weifeng

AU - Du, Bowen

AU - Xie, Zhipu

AU - Huang, Runhe

PY - 2018/12/4

Y1 - 2018/12/4

N2 - Optimization of public bus routes in a transportation system is one of the keys to achieve smart city concept, delivers better quality, and cost-saving travel to the passengers. Compared to private vehicles, public transportation system has been chosen by millions of passengers each day with different routes, generates certain travel patterns. From these travel patterns, routes are optimized by the transportation experts to reduce the gap between existing routes and travel demands. Thus, the transportation system is depending upon experts to optimize it manually. This paper focuses on discovering the mobility pattern of passengers with buses and subways to optimize the routes of Beijing. To this end, we first illustrate the changes in certain bus lines by the experts in a specific interval of time during a year and their impact. Based upon mobility features, we propose Group Travel Demand Identification (GTDI) method that suggests the route adjustments for optimization of bus lines. We also demonstrate a comparison of our method with other optimization techniques. Route forecasting results are matched with the adjustments of experts to validate the performance and reliability, To solve route adjustment problem, we conducted an extensive study on sets of data records and adjustment records of bus lines collected from Beijing Public Transport Corporation (BPTC). To generate mobility pattern from Smart Card Data, we studied more than 845 million passengers.

AB - Optimization of public bus routes in a transportation system is one of the keys to achieve smart city concept, delivers better quality, and cost-saving travel to the passengers. Compared to private vehicles, public transportation system has been chosen by millions of passengers each day with different routes, generates certain travel patterns. From these travel patterns, routes are optimized by the transportation experts to reduce the gap between existing routes and travel demands. Thus, the transportation system is depending upon experts to optimize it manually. This paper focuses on discovering the mobility pattern of passengers with buses and subways to optimize the routes of Beijing. To this end, we first illustrate the changes in certain bus lines by the experts in a specific interval of time during a year and their impact. Based upon mobility features, we propose Group Travel Demand Identification (GTDI) method that suggests the route adjustments for optimization of bus lines. We also demonstrate a comparison of our method with other optimization techniques. Route forecasting results are matched with the adjustments of experts to validate the performance and reliability, To solve route adjustment problem, we conducted an extensive study on sets of data records and adjustment records of bus lines collected from Beijing Public Transport Corporation (BPTC). To generate mobility pattern from Smart Card Data, we studied more than 845 million passengers.

KW - Group Passengers Bus line Optimization

KW - Route Prediction

KW - Smart Transportation

KW - Transport Planning

KW - Transportation Mobility Patterns

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M3 - 会议稿件

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T3 - Proceedings - 2018 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovations, SmartWorld/UIC/ATC/ScalCom/CBDCom/IoP/SCI 2018

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BT - Proceedings - 2018 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovations, SmartWorld/UIC/ATC/ScalCom/CBDCom/IoP/SCI 2018

A2 - Loulergue, Frederic

A2 - Wang, Guojun

A2 - Bhuiyan, Md Zakirul Alam

A2 - Ma, Xiaoxing

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A2 - Roveri, Manuel

A2 - Han, Qi

A2 - Chen, Lei

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 4th IEEE SmartWorld, 15th IEEE International Conference on Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovations, SmartWorld/UIC/ATC/ScalCom/CBDCom/IoP/SCI 2018

Y2 - 7 October 2018 through 11 October 2018

ER -

Rizvi SMAA, Lv W , Du B, Xie Z, Huang R. Optimization of bus lines based on passenger group moving behaviors. In Loulergue F, Wang G, Bhuiyan MZA, Ma X, Li P, Roveri M, Han Q, Chen L, editors, Proceedings - 2018 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovations, SmartWorld/UIC/ATC/ScalCom/CBDCom/IoP/SCI 2018. Institute of Electrical and Electronics Engineers Inc. 2018. p. 53-60. 8560022. (Proceedings - 2018 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovations, SmartWorld/UIC/ATC/ScalCom/CBDCom/IoP/SCI 2018). doi: 10.1109/SmartWorld.2018.00044

Optimization of bus lines based on passenger group moving behaviors

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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