PAC: Partial Area Clustering for Re-Adjusting the Layout of Traffic Stations in City's Public Transport

Now public transportation, included bus and subway occupies a greater role in city transport, and the layout of traffic stations is the most important part of planning and design. However, some unpredicted factors for construction of traffic stations results in a low utilization rate of public trans...

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Bibliographic Details
Published in:IEEE transactions on intelligent transportation systems 2023-01, Vol.24 (1), p.1251-1260
Main Authors: Pei, Jiaming, Zhong, Kaiyang, Li, Jinhai, Yu, Zhi
Format: Article
Language:English
Subjects:
Algorithms
Behavioral sciences
Bus stops
Buses (vehicles)
Clustering
clustering analysis
Layout
Layouts
Machine learning
Optimization
Picture archiving and communication systems
Public transport
Public transportation
Rails
station layout and optimization
Subway stations
Traffic planning
Trajectory
Transportation networks
Transportation systems
Urban areas
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Summary:Now public transportation, included bus and subway occupies a greater role in city transport, and the layout of traffic stations is the most important part of planning and design. However, some unpredicted factors for construction of traffic stations results in a low utilization rate of public transportation resources, for example, the layout of bus stops is chaotic, there is no clear layout scope, and there is a lack of integration with residents' travel hotspots. Towards these challenges modern transport faces, we firstly analyze the distribution of bus stops and subway stations to determine the area range needs to be optimized in the traffic net from the perspective of time and space. And then, we propose an optimization method, called 'partial area clustering' (PAC), to improve the utilization by changing and renewing the original distribution. The novel method was based on the K-means algorithm in the field of machine learning. PAC worked to search the suitable bus platforms as the center and modified the original one to the subway. Experiment has shown that the use of public transport resources has increased by 20%. The study uses a similar cluster algorithm to solve transport networks' problems in a novel but practical term. As a result, the PAC is expected to be used extensively in the transportation system construction process.
ISSN:1524-9050
1558-0016
DOI:10.1109/TITS.2022.3179024