Using GPS Trajectories to Adaptively Plan Bus Lanes

Since bus prioritization policies can help mitigate urban traffic jams, the planning of bus lanes has drawn considerable attention. Existing methods suffer from a common limitation, which is that the limited spatial adaptability resulting from certain road condition information cannot be directly sp...

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Main Authors: Yanjie Sun, Mingguang Wu, Huien Li
Format: Article
Language:English
Published: MDPI AG 2021-01-01
Series:Applied Sciences
Subjects:
Online Access:https://www.mdpi.com/2076-3417/11/3/1035
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spelling doaj-665ecc143cae4a078e05b7a2e97509022021-01-25T00:00:33ZengMDPI AGApplied Sciences2076-34172021-01-01111035103510.3390/app11031035Using GPS Trajectories to Adaptively Plan Bus LanesYanjie Sun0Mingguang Wu1Huien Li2Key Laboratory of Virtual Geographic Environment of Ministry of Education, Nanjing Normal University, Nanjing 210023, Jiangsu, ChinaKey Laboratory of Virtual Geographic Environment of Ministry of Education, Nanjing Normal University, Nanjing 210023, Jiangsu, ChinaJiangsu Institute of Geographic Information Industry, Nanjing 210023, Jiangsu, ChinaSince bus prioritization policies can help mitigate urban traffic jams, the planning of bus lanes has drawn considerable attention. Existing methods suffer from a common limitation, which is that the limited spatial adaptability resulting from certain road condition information cannot be directly specified. Many bus GPS trajectories have been accumulated and can be contiguously gathered if needed. This paper proposes a trajectory-based bus lane planning method. First, we formulize the bus lane planning problem as a multiobjective optimization problem in which the road conditions, traffic flow, connectivity of bus lanes, and construction cost are organized as four constraints, and road utilization and bus punctuality are modeled as two objectives. Then, an evolutionary algorithm-based method is presented to solve the problem. We tested the model in the Nanshan District, Shenzhen City, China. Through a comparison with existing survey-based methods, the parameters associated with road conditions in this method are directly extracted from GPS trajectories, and this method is more effectively deployed than other methods. Since GPS trajectories can cover a wide area if needed, and because the proposed method can be effectively executed, this method can be adapted to large urban scales.https://www.mdpi.com/2076-3417/11/3/1035traffic congestionbus lane planningGPS trajectorymultiobjective optimization
collection DOAJ
language English
format Article
sources DOAJ
author Yanjie Sun
Mingguang Wu
Huien Li
spellingShingle Yanjie Sun
Mingguang Wu
Huien Li
Using GPS Trajectories to Adaptively Plan Bus Lanes
Applied Sciences
traffic congestion
bus lane planning
GPS trajectory
multiobjective optimization
author_facet Yanjie Sun
Mingguang Wu
Huien Li
author_sort Yanjie Sun
title Using GPS Trajectories to Adaptively Plan Bus Lanes
title_short Using GPS Trajectories to Adaptively Plan Bus Lanes
title_full Using GPS Trajectories to Adaptively Plan Bus Lanes
title_fullStr Using GPS Trajectories to Adaptively Plan Bus Lanes
title_full_unstemmed Using GPS Trajectories to Adaptively Plan Bus Lanes
title_sort using gps trajectories to adaptively plan bus lanes
publisher MDPI AG
series Applied Sciences
issn 2076-3417
publishDate 2021-01-01
description Since bus prioritization policies can help mitigate urban traffic jams, the planning of bus lanes has drawn considerable attention. Existing methods suffer from a common limitation, which is that the limited spatial adaptability resulting from certain road condition information cannot be directly specified. Many bus GPS trajectories have been accumulated and can be contiguously gathered if needed. This paper proposes a trajectory-based bus lane planning method. First, we formulize the bus lane planning problem as a multiobjective optimization problem in which the road conditions, traffic flow, connectivity of bus lanes, and construction cost are organized as four constraints, and road utilization and bus punctuality are modeled as two objectives. Then, an evolutionary algorithm-based method is presented to solve the problem. We tested the model in the Nanshan District, Shenzhen City, China. Through a comparison with existing survey-based methods, the parameters associated with road conditions in this method are directly extracted from GPS trajectories, and this method is more effectively deployed than other methods. Since GPS trajectories can cover a wide area if needed, and because the proposed method can be effectively executed, this method can be adapted to large urban scales.
topic traffic congestion
bus lane planning
GPS trajectory
multiobjective optimization
url https://www.mdpi.com/2076-3417/11/3/1035
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AT huienli usinggpstrajectoriestoadaptivelyplanbuslanes
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