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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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 |
work_keys_str_mv |
AT yanjiesun usinggpstrajectoriestoadaptivelyplanbuslanes AT mingguangwu usinggpstrajectoriestoadaptivelyplanbuslanes AT huienli usinggpstrajectoriestoadaptivelyplanbuslanes |
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