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Article

Investigating Influence Factors on Traffic Safety Based on a Hybrid Approach: Taking Pedestrians as an Example

Transport Planning and Research Institute, Ministry of Transport, Beijing 100028, China
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Author to whom correspondence should be addressed.
Sensors 2024, 24(23), 7720; https://doi.org/10.3390/s24237720
Submission received: 15 October 2024 / Revised: 25 November 2024 / Accepted: 26 November 2024 / Published: 3 December 2024

Abstract

Road traffic safety is an essential component of public safety and a globally significant issue. Pedestrians, as crucial participants in traffic activities, have always been a primary focus with regard to traffic safety. In the context of the rapid advancement of intelligent transportation systems (ITS), it is crucial to explore effective strategies for preventing pedestrian fatalities in pedestrian–vehicle crashes. This paper aims to investigate the factors that influence pedestrian injury severity based on pedestrian-involved crash data collected from several sensor-based sources. To achieve this, a hybrid approach of a random parameters logit model and random forest based on the SHAP method is proposed. Specifically, the random parameters logit model is utilized to uncover significant factors and the random variability of parameters, while the random forest based on SHAP is employed to identify important influencing factors and feature contributions. The results indicate that the hybrid approach can not only verify itself but also complement more conclusions. Eight significant influencing factors were identified, with seven of the factors identified as important by the random forest analysis. However, it was found that the factors “Workday or not” (Not), “Signal control mode” (No signal and Other security facilities), and “Road safety attribute” (Normal Road) are not considered significant. It is important to note that focusing solely on either significant or important factors may lead to overlooking certain conclusions. The proposed strategies for ITS have the potential to significantly improve pedestrian safety levels.
Keywords: pedestrian traffic safety; intelligent transportation systems; sensor-based data; pedestrian–vehicle crashes; hybrid approach pedestrian traffic safety; intelligent transportation systems; sensor-based data; pedestrian–vehicle crashes; hybrid approach

Share and Cite

MDPI and ACS Style

Li, Y.; Shi, Y.; Xiong, H.; Jian, F.; Yu, X.; Sun, S.; Meng, Y. Investigating Influence Factors on Traffic Safety Based on a Hybrid Approach: Taking Pedestrians as an Example. Sensors 2024, 24, 7720. https://doi.org/10.3390/s24237720

AMA Style

Li Y, Shi Y, Xiong H, Jian F, Yu X, Sun S, Meng Y. Investigating Influence Factors on Traffic Safety Based on a Hybrid Approach: Taking Pedestrians as an Example. Sensors. 2024; 24(23):7720. https://doi.org/10.3390/s24237720

Chicago/Turabian Style

Li, Yue, Yuanyuan Shi, Huiyuan Xiong, Feng Jian, Xinxin Yu, Shuo Sun, and Yunlong Meng. 2024. "Investigating Influence Factors on Traffic Safety Based on a Hybrid Approach: Taking Pedestrians as an Example" Sensors 24, no. 23: 7720. https://doi.org/10.3390/s24237720

APA Style

Li, Y., Shi, Y., Xiong, H., Jian, F., Yu, X., Sun, S., & Meng, Y. (2024). Investigating Influence Factors on Traffic Safety Based on a Hybrid Approach: Taking Pedestrians as an Example. Sensors, 24(23), 7720. https://doi.org/10.3390/s24237720

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