Conflict Probability Prediction and Safety Assessment of Straight-Left Traffic Flow at Signalized Intersections
The safety of signalized intersections is of great concern. To allow for an effective evaluation measure on the safety level of intersections, traffic conflict analysis methods are commonly used. However, the existing literature has mainly focused on the statistical prediction of conflicts by using...
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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2022/8233424 |
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| _version_ | 1832549168006037504 |
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| author | Yingying Ma Zihao Zhang Jiabin Wu |
| author_facet | Yingying Ma Zihao Zhang Jiabin Wu |
| author_sort | Yingying Ma |
| collection | DOAJ |
| description | The safety of signalized intersections is of great concern. To allow for an effective evaluation measure on the safety level of intersections, traffic conflict analysis methods are commonly used. However, the existing literature has mainly focused on the statistical prediction of conflicts by using surrogate measurements, among which the spatial-temporal characteristics of the potential conflicts have been less addressed. In addition, most of the relevant studies rely on precise trajectory data, and the results could be limited to engineering applications when real-time/comprehensive trajectory data are not available. To address these issues, this study proposes a SICP (signalized intersection conflict probability) model to predict a straight-left traffic flow conflict with a spatial-temporal distribution in the heat map, which could effectively evaluate the traffic safety of the existing or prebuilt signalized intersections on urban roads. Firstly, the impact of vehicle movement characteristics on traffic conflict at signalized intersections was considered by incorporating the vehicle movement trajectory. Secondly, the signal phase was categorized in several stages (each phase contains switching and nonswitching stages); then, a vehicle-vehicle conflicts probability prediction model was established by integrating both horizontal and vertical arrival probability. Finally, to validate the performance of the proposed model, the measured data were collected from the intersection of Wushan road and Yuehan road in Tianhe District, Guangzhou, China. SSAM（Surrogate Safety Assessment Model）traffic conflict simulation was used to analyze the traffic conflict in the actual data and compared to the SICP model. A case study was conducted to reveal the evolution mechanism of the conflict risk coefficient at the signalized intersection and to estimate the safety status under the various security optimization strategies. The experimental results verified the effectiveness of the SICP model, indicating that the proposed model is effective in evaluating the safety level of existing or prebuilt signalized intersections. |
| format | Article |
| id | doaj-art-72b9aec03e104ffeb7496475a5eaaf5f |
| institution | Kabale University |
| issn | 2042-3195 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Advanced Transportation |
| spelling | doaj-art-72b9aec03e104ffeb7496475a5eaaf5f2025-02-03T06:11:56ZengWileyJournal of Advanced Transportation2042-31952022-01-01202210.1155/2022/8233424Conflict Probability Prediction and Safety Assessment of Straight-Left Traffic Flow at Signalized IntersectionsYingying Ma0Zihao Zhang1Jiabin Wu2Department of Transportation EngineeringDepartment of Transportation EngineeringDepartment of Transportation EngineeringThe safety of signalized intersections is of great concern. To allow for an effective evaluation measure on the safety level of intersections, traffic conflict analysis methods are commonly used. However, the existing literature has mainly focused on the statistical prediction of conflicts by using surrogate measurements, among which the spatial-temporal characteristics of the potential conflicts have been less addressed. In addition, most of the relevant studies rely on precise trajectory data, and the results could be limited to engineering applications when real-time/comprehensive trajectory data are not available. To address these issues, this study proposes a SICP (signalized intersection conflict probability) model to predict a straight-left traffic flow conflict with a spatial-temporal distribution in the heat map, which could effectively evaluate the traffic safety of the existing or prebuilt signalized intersections on urban roads. Firstly, the impact of vehicle movement characteristics on traffic conflict at signalized intersections was considered by incorporating the vehicle movement trajectory. Secondly, the signal phase was categorized in several stages (each phase contains switching and nonswitching stages); then, a vehicle-vehicle conflicts probability prediction model was established by integrating both horizontal and vertical arrival probability. Finally, to validate the performance of the proposed model, the measured data were collected from the intersection of Wushan road and Yuehan road in Tianhe District, Guangzhou, China. SSAM（Surrogate Safety Assessment Model）traffic conflict simulation was used to analyze the traffic conflict in the actual data and compared to the SICP model. A case study was conducted to reveal the evolution mechanism of the conflict risk coefficient at the signalized intersection and to estimate the safety status under the various security optimization strategies. The experimental results verified the effectiveness of the SICP model, indicating that the proposed model is effective in evaluating the safety level of existing or prebuilt signalized intersections.http://dx.doi.org/10.1155/2022/8233424 |
| spellingShingle | Yingying Ma Zihao Zhang Jiabin Wu Conflict Probability Prediction and Safety Assessment of Straight-Left Traffic Flow at Signalized Intersections Journal of Advanced Transportation |
| title | Conflict Probability Prediction and Safety Assessment of Straight-Left Traffic Flow at Signalized Intersections |
| title_full | Conflict Probability Prediction and Safety Assessment of Straight-Left Traffic Flow at Signalized Intersections |
| title_fullStr | Conflict Probability Prediction and Safety Assessment of Straight-Left Traffic Flow at Signalized Intersections |
| title_full_unstemmed | Conflict Probability Prediction and Safety Assessment of Straight-Left Traffic Flow at Signalized Intersections |
| title_short | Conflict Probability Prediction and Safety Assessment of Straight-Left Traffic Flow at Signalized Intersections |
| title_sort | conflict probability prediction and safety assessment of straight left traffic flow at signalized intersections |
| url | http://dx.doi.org/10.1155/2022/8233424 |
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