Evaluation of red-light camera enforcement using traffic violations
The State of Qatar started to use red-light cameras in 2007 at key signalized intersections and the rate of installation has subsequently increased. In 2017, 19.2% of signalized intersections are equipped with red-light cameras. In many cases, the cameras are not installed on all approaches to the i...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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KeAi Communications Co., Ltd.
2018-02-01
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| Series: | Journal of Traffic and Transportation Engineering (English ed. Online) |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2095756416301659 |
| _version_ | 1818610608762781696 |
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| author | Khaled Shaaban Anurag Pande |
| author_facet | Khaled Shaaban Anurag Pande |
| author_sort | Khaled Shaaban |
| collection | DOAJ |
| description | The State of Qatar started to use red-light cameras in 2007 at key signalized intersections and the rate of installation has subsequently increased. In 2017, 19.2% of signalized intersections are equipped with red-light cameras. In many cases, the cameras are not installed on all approaches to the intersections. The purpose of this study is to compare the red-light running violations on approaches with and without red-light running enforcement cameras at the same intersections. Actual field observations were used in this study. Different variables were investigated, including the day of the week, time of day, traffic volume, the possibility of glare on an approach, and the lengths of the yellow and all-red times. A regression tree model was used to explain the characteristics associated with the violations. The results showed that the number of violations on low-volume approaches was five times higher than on high-volume approaches. The results also showed that the presence of the cameras significantly lowered red-light running violations. High-volume approaches without cameras had an approximately eight times higher rate of violations than high-volume approaches with cameras. The analysis also showed that bringing the all-red interval closer to the values recommended by the Institute of Transportation Engineers formula may bring down the rates of violations for low-volume approaches. As with any observational data mining method, the study could benefit from a larger sample size. The method used in the study was effective and is easily transferable to other locations. The results of this study can be used in developing new strategies to improve safety at signalized intersections. |
| first_indexed | 2024-12-16T15:17:09Z |
| format | Article |
| id | doaj.art-6c660dcea3d54561957c8f8050d050da |
| institution | Directory Open Access Journal |
| issn | 2095-7564 |
| language | English |
| last_indexed | 2024-12-16T15:17:09Z |
| publishDate | 2018-02-01 |
| publisher | KeAi Communications Co., Ltd. |
| record_format | Article |
| series | Journal of Traffic and Transportation Engineering (English ed. Online) |
| spelling | doaj.art-6c660dcea3d54561957c8f8050d050da2022-12-21T22:26:46ZengKeAi Communications Co., Ltd.Journal of Traffic and Transportation Engineering (English ed. Online)2095-75642018-02-0151667210.1016/j.jtte.2017.04.005Evaluation of red-light camera enforcement using traffic violationsKhaled Shaaban0Anurag Pande1Department of Civil and Architectural Engineering, Qatar University, Doha, QatarDepartment of Civil and Environmental Engineering, California Polytechnic State University, San Luis Obispo, CA 93407, USAThe State of Qatar started to use red-light cameras in 2007 at key signalized intersections and the rate of installation has subsequently increased. In 2017, 19.2% of signalized intersections are equipped with red-light cameras. In many cases, the cameras are not installed on all approaches to the intersections. The purpose of this study is to compare the red-light running violations on approaches with and without red-light running enforcement cameras at the same intersections. Actual field observations were used in this study. Different variables were investigated, including the day of the week, time of day, traffic volume, the possibility of glare on an approach, and the lengths of the yellow and all-red times. A regression tree model was used to explain the characteristics associated with the violations. The results showed that the number of violations on low-volume approaches was five times higher than on high-volume approaches. The results also showed that the presence of the cameras significantly lowered red-light running violations. High-volume approaches without cameras had an approximately eight times higher rate of violations than high-volume approaches with cameras. The analysis also showed that bringing the all-red interval closer to the values recommended by the Institute of Transportation Engineers formula may bring down the rates of violations for low-volume approaches. As with any observational data mining method, the study could benefit from a larger sample size. The method used in the study was effective and is easily transferable to other locations. The results of this study can be used in developing new strategies to improve safety at signalized intersections.http://www.sciencedirect.com/science/article/pii/S2095756416301659Driver behaviorTraffic signalPolice enforcementRisky drivingAutomated enforcementRoad policing |
| spellingShingle | Khaled Shaaban Anurag Pande Evaluation of red-light camera enforcement using traffic violations Journal of Traffic and Transportation Engineering (English ed. Online) Driver behavior Traffic signal Police enforcement Risky driving Automated enforcement Road policing |
| title | Evaluation of red-light camera enforcement using traffic violations |
| title_full | Evaluation of red-light camera enforcement using traffic violations |
| title_fullStr | Evaluation of red-light camera enforcement using traffic violations |
| title_full_unstemmed | Evaluation of red-light camera enforcement using traffic violations |
| title_short | Evaluation of red-light camera enforcement using traffic violations |
| title_sort | evaluation of red light camera enforcement using traffic violations |
| topic | Driver behavior Traffic signal Police enforcement Risky driving Automated enforcement Road policing |
| url | http://www.sciencedirect.com/science/article/pii/S2095756416301659 |
| work_keys_str_mv | AT khaledshaaban evaluationofredlightcameraenforcementusingtrafficviolations AT anuragpande evaluationofredlightcameraenforcementusingtrafficviolations |