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14 February 2024 Risk assessment, prediction, and factor analysis for lanes at urban intersection
Yongjie Wang, Yueying Xu, Qiong Li, Chenhui Li
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Proceedings Volume 13018, International Conference on Smart Transportation and City Engineering (STCE 2023); 130183N (2024) https://doi.org/10.1117/12.3024086
Event: International Conference on Smart Transportation and City Engineering (STCE 2023), 2023, Chongqing, China
Abstract
To determine the risk levels of urban signal-controlled intersection lanes, we propose two comprehensive risk assessment sets that incorporate time proximity, spatial proximity, and velocity-based indicators. Using actual trajectory data of intersection users, we analyse the interactions between three common vulnerable road users and motor vehicles. Bayesian inference algorithm is employed to evaluate lane risk levels. Additionally, XGBoost, random algorithm, and SVM algorithm with a Gaussian kernel are utilized to predict intersection lane risk. The importance and correlation of risk factors are explored using SHAP value theory. Results indicate that while extremely dangerous collisions are less likely due to signal control, moderate risk remains prevalent. The XGBoost model outperforms the other methods with an accuracy rate of 91.51% and precision rate of 94.17%. Among the analysed interaction risk factors, the speed and acceleration of road users have the greatest impact on lane risk levels. In low traffic flow conditions, higher speeds of motorcycles and cars increase collision risks. Lanes three and four exhibit higher probabilities of hazardous interactions between pedestrians and cars, resulting in more severe pedestrian injuries. Additionally, motorcycles at lower speeds are more prone to risky interactions with pedestrians.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
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Yongjie Wang, Yueying Xu, Qiong Li, and Chenhui Li "Risk assessment, prediction, and factor analysis for lanes at urban intersection", Proc. SPIE 13018, International Conference on Smart Transportation and City Engineering (STCE 2023), 130183N (14 February 2024); https://doi.org/10.1117/12.3024086
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KEYWORDS
Risk assessment
Roads
Factor analysis
Bayesian inference
Safety
Injuries
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