Simulation-Based Sensor Location Model for Arterial Street
Traffic sensors serve as an important way to a number of intelligent transportation system applications which rely heavily on real-time data. However, traffic sensors are costly. Therefore, it is necessary to optimize sensor placement to maximize various benefits. Arterial street traffic is highly d...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2015-01-01
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| Series: | Discrete Dynamics in Nature and Society |
| Online Access: | http://dx.doi.org/10.1155/2015/854089 |
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| _version_ | 1832562882797109248 |
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| author | Qinxiao Yu Ning Zhu Geng Li Shoufeng Ma |
| author_facet | Qinxiao Yu Ning Zhu Geng Li Shoufeng Ma |
| author_sort | Qinxiao Yu |
| collection | DOAJ |
| description | Traffic sensors serve as an important way to a number of intelligent transportation system applications which rely heavily on real-time data. However, traffic sensors are costly. Therefore, it is necessary to optimize sensor placement to maximize various benefits. Arterial street traffic is highly dynamic and the movement of vehicles is disturbed by signals and irregular vehicle maneuver. It is challenging to estimate the arterial street travel time with limited sensors. In order to solve the problem, the paper presents travel time estimation models that rely on speed data collected by sensor. The relationship between sensor position and vehicle trajectory in single link is investigated. A sensor location model in signalized arterial is proposed to find the optimal sensor placement with the minimum estimation error of arterial travel time. Numerical experiments are conducted in 3 conditions: synchronized traffic signals, green wave traffic signals, and vehicle-actuated signals. The results indicate that the sensors should not be placed in vehicle queuing area. Intersection stop line is an ideal sensor position. There is not any fixed sensor position that can cope with all traffic conditions. |
| format | Article |
| id | doaj-art-79910a270969459d83c7d1aad401d881 |
| institution | Kabale University |
| issn | 1026-0226 1607-887X |
| language | English |
| publishDate | 2015-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Discrete Dynamics in Nature and Society |
| spelling | doaj-art-79910a270969459d83c7d1aad401d8812025-02-03T01:21:31ZengWileyDiscrete Dynamics in Nature and Society1026-02261607-887X2015-01-01201510.1155/2015/854089854089Simulation-Based Sensor Location Model for Arterial StreetQinxiao Yu0Ning Zhu1Geng Li2Shoufeng Ma3Institute of Systems Engineering, College of Management & Economics, Tianjin University, Tianjin 300072, ChinaInstitute of Systems Engineering, College of Management & Economics, Tianjin University, Tianjin 300072, ChinaInstitute of Systems Engineering, College of Management & Economics, Tianjin University, Tianjin 300072, ChinaInstitute of Systems Engineering, College of Management & Economics, Tianjin University, Tianjin 300072, ChinaTraffic sensors serve as an important way to a number of intelligent transportation system applications which rely heavily on real-time data. However, traffic sensors are costly. Therefore, it is necessary to optimize sensor placement to maximize various benefits. Arterial street traffic is highly dynamic and the movement of vehicles is disturbed by signals and irregular vehicle maneuver. It is challenging to estimate the arterial street travel time with limited sensors. In order to solve the problem, the paper presents travel time estimation models that rely on speed data collected by sensor. The relationship between sensor position and vehicle trajectory in single link is investigated. A sensor location model in signalized arterial is proposed to find the optimal sensor placement with the minimum estimation error of arterial travel time. Numerical experiments are conducted in 3 conditions: synchronized traffic signals, green wave traffic signals, and vehicle-actuated signals. The results indicate that the sensors should not be placed in vehicle queuing area. Intersection stop line is an ideal sensor position. There is not any fixed sensor position that can cope with all traffic conditions.http://dx.doi.org/10.1155/2015/854089 |
| spellingShingle | Qinxiao Yu Ning Zhu Geng Li Shoufeng Ma Simulation-Based Sensor Location Model for Arterial Street Discrete Dynamics in Nature and Society |
| title | Simulation-Based Sensor Location Model for Arterial Street |
| title_full | Simulation-Based Sensor Location Model for Arterial Street |
| title_fullStr | Simulation-Based Sensor Location Model for Arterial Street |
| title_full_unstemmed | Simulation-Based Sensor Location Model for Arterial Street |
| title_short | Simulation-Based Sensor Location Model for Arterial Street |
| title_sort | simulation based sensor location model for arterial street |
| url | http://dx.doi.org/10.1155/2015/854089 |
| work_keys_str_mv | AT qinxiaoyu simulationbasedsensorlocationmodelforarterialstreet AT ningzhu simulationbasedsensorlocationmodelforarterialstreet AT gengli simulationbasedsensorlocationmodelforarterialstreet AT shoufengma simulationbasedsensorlocationmodelforarterialstreet |