Optimal Placement of Bus Stops using Particle Swarm Optimization

Changyu Li; Ran Ge; Xiangcheng Wu; Alaa Khamis

doi:10.1109/SM57895.2023.10112283

Optimal Placement of Bus Stops using Particle Swarm Optimization

Changyu Li
, Ran Ge
, Xiangcheng Wu
, Alaa Khamis

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

3 Scopus citations

Abstract

Bus systems play an important role in the modern city. Carefully designed bus stop locations can lift up overall transportation efficiency and save more time for passengers. In this paper, Particle Swarm Optimization (PSO)-based approach is proposed to find the optimal placement of bus stops in Waterloo/Kitchener area. The selection of the bus stops placements takes into account neighborhood population, family income, age distribution, and other factors. The overall goal is to minimize the average travel time of the passengers which is composed of two parts namely passenger time in the bus and out of the bus. Experimental results on real bus lines in Waterloo/Kitchener region, Canada showed that both PSO and adaptive PSO provide shorter average commuting time compared to the original bus routes. Moreover, the optimized placement needs less number of bus stops compared to the original number of stations.

Original language	English
Title of host publication	2023 IEEE International Conference on Smart Mobility, SM 2023
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	15-20
Number of pages	6
ISBN (Electronic)	9798350312751
DOIs	https://doi.org/10.1109/SM57895.2023.10112283
State	Published - 2023
Externally published	Yes
Event	2023 IEEE International Conference on Smart Mobility, SM 2023 - Thuwal, Saudi Arabia Duration: 19 Mar 2023 → 21 Mar 2023

Publication series

Name	2023 IEEE International Conference on Smart Mobility, SM 2023

Conference

Conference	2023 IEEE International Conference on Smart Mobility, SM 2023
Country/Territory	Saudi Arabia
City	Thuwal
Period	19/03/23 → 21/03/23

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

Keywords

Adaptive PSO
Bus Stop Placement
Metaheuristics
Particle Swarm Optimization (PSO)

ASJC Scopus subject areas

Artificial Intelligence
Computer Networks and Communications
Computer Vision and Pattern Recognition
Control and Optimization
Transportation

UN SDGs

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

Access to Document

10.1109/SM57895.2023.10112283

Cite this

@inproceedings{8a1c7aa1d6a648eda7edc34d17f2932d,

title = "Optimal Placement of Bus Stops using Particle Swarm Optimization",

abstract = "Bus systems play an important role in the modern city. Carefully designed bus stop locations can lift up overall transportation efficiency and save more time for passengers. In this paper, Particle Swarm Optimization (PSO)-based approach is proposed to find the optimal placement of bus stops in Waterloo/Kitchener area. The selection of the bus stops placements takes into account neighborhood population, family income, age distribution, and other factors. The overall goal is to minimize the average travel time of the passengers which is composed of two parts namely passenger time in the bus and out of the bus. Experimental results on real bus lines in Waterloo/Kitchener region, Canada showed that both PSO and adaptive PSO provide shorter average commuting time compared to the original bus routes. Moreover, the optimized placement needs less number of bus stops compared to the original number of stations.",

keywords = "Adaptive PSO, Bus Stop Placement, Metaheuristics, Particle Swarm Optimization (PSO)",

author = "Changyu Li and Ran Ge and Xiangcheng Wu and Alaa Khamis",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE International Conference on Smart Mobility, SM 2023 ; Conference date: 19-03-2023 Through 21-03-2023",

year = "2023",

doi = "10.1109/SM57895.2023.10112283",

language = "English",

series = "2023 IEEE International Conference on Smart Mobility, SM 2023",

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

pages = "15--20",

booktitle = "2023 IEEE International Conference on Smart Mobility, SM 2023",

address = "United States",

}

Li, C, Ge, R, Wu, X & Khamis, A 2023, Optimal Placement of Bus Stops using Particle Swarm Optimization. in 2023 IEEE International Conference on Smart Mobility, SM 2023. 2023 IEEE International Conference on Smart Mobility, SM 2023, Institute of Electrical and Electronics Engineers Inc., pp. 15-20, 2023 IEEE International Conference on Smart Mobility, SM 2023, Thuwal, Saudi Arabia, 19/03/23. https://doi.org/10.1109/SM57895.2023.10112283

Optimal Placement of Bus Stops using Particle Swarm Optimization. / Li, Changyu; Ge, Ran; Wu, Xiangcheng et al.
2023 IEEE International Conference on Smart Mobility, SM 2023. Institute of Electrical and Electronics Engineers Inc., 2023. p. 15-20 (2023 IEEE International Conference on Smart Mobility, SM 2023).

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

TY - GEN

T1 - Optimal Placement of Bus Stops using Particle Swarm Optimization

AU - Li, Changyu

AU - Ge, Ran

AU - Wu, Xiangcheng

AU - Khamis, Alaa

PY - 2023

Y1 - 2023

N2 - Bus systems play an important role in the modern city. Carefully designed bus stop locations can lift up overall transportation efficiency and save more time for passengers. In this paper, Particle Swarm Optimization (PSO)-based approach is proposed to find the optimal placement of bus stops in Waterloo/Kitchener area. The selection of the bus stops placements takes into account neighborhood population, family income, age distribution, and other factors. The overall goal is to minimize the average travel time of the passengers which is composed of two parts namely passenger time in the bus and out of the bus. Experimental results on real bus lines in Waterloo/Kitchener region, Canada showed that both PSO and adaptive PSO provide shorter average commuting time compared to the original bus routes. Moreover, the optimized placement needs less number of bus stops compared to the original number of stations.

AB - Bus systems play an important role in the modern city. Carefully designed bus stop locations can lift up overall transportation efficiency and save more time for passengers. In this paper, Particle Swarm Optimization (PSO)-based approach is proposed to find the optimal placement of bus stops in Waterloo/Kitchener area. The selection of the bus stops placements takes into account neighborhood population, family income, age distribution, and other factors. The overall goal is to minimize the average travel time of the passengers which is composed of two parts namely passenger time in the bus and out of the bus. Experimental results on real bus lines in Waterloo/Kitchener region, Canada showed that both PSO and adaptive PSO provide shorter average commuting time compared to the original bus routes. Moreover, the optimized placement needs less number of bus stops compared to the original number of stations.

KW - Adaptive PSO

KW - Bus Stop Placement

KW - Metaheuristics

KW - Particle Swarm Optimization (PSO)

UR - https://www.scopus.com/pages/publications/85159850255

U2 - 10.1109/SM57895.2023.10112283

DO - 10.1109/SM57895.2023.10112283

M3 - Conference contribution

AN - SCOPUS:85159850255

T3 - 2023 IEEE International Conference on Smart Mobility, SM 2023

SP - 15

EP - 20

BT - 2023 IEEE International Conference on Smart Mobility, SM 2023

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2023 IEEE International Conference on Smart Mobility, SM 2023

Y2 - 19 March 2023 through 21 March 2023

ER -

Optimal Placement of Bus Stops using Particle Swarm Optimization

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

UN SDGs

Access to Document

Fingerprint

Cite this