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Promet - Traffic&Transportation journal

Accelerating Discoveries in Traffic Science

Accelerating Discoveries in Traffic Science

PUBLISHED
02.12.2022
LICENSE
Copyright (c) 2024 Xiaoxia Xiong, Yu He, Xiang Gao, Yeling Zhao

A Multi-Level Risk Framework for Driving Safety Assessment Based on Vehicle Trajectory

Authors:

Xiaoxia Xiong
Jiangsu University

Yu He
Jiangsu University

Xiang Gao
Jiangsu University

Yeling Zhao
Jiangsu University

Keywords:traffic safety, multi-level risk, safety indictor, SEM, vehicle trajectory

Abstract

Few existing research studies have explored the re-lationship of road section level, local area level and ve-hicle level risks within the highway traffic safety system, which can be important to the formation of an effective risk event prediction. This paper proposes a framework of multi-level risks described by a set of carefully select-ed or designed indicators. The interrelationship among these latent multi-level risks and their observable indica-tors are explored based on vehicle trajectory data using the structural equation model (SEM). The results show that there exists significant positive correlation between the latent risk constructs that each have adequate con-vergent validity, and it is difficult to completely separate the local traffic level risk from both the road section level risk and vehicle level risk. The local and road level in-dicators are also found to be of more importance when risk prediction time gets earlier based on feature impor-tance scoring of the LightGBM. The proposed conceptual multi-level indicator based latent risk framework gener-ally fits with the observed results and emphasises the im-portance of including multi-level indicators for risk event prediction in the future.

References

  1. World Health Organization. Road Traffic Injuries. 2021. http://www.who.int/mediacentre/factsheets/fs358/en/.

    Shunying Z, et al. Review of research on traffic conflict techniques. China Journal of Highway and Transport. 2020;33(2): 15-33.

    Wang X, et al. Effect of daily car-following behaviors on urban roadway rear-end crashes and near-crashes: A naturalistic driving study. Accident Analysis and Prevention. 2022;164(November 2021): 106502. doi: 10.1016/j.aap.2021.106502.

    Chen S, et al. Risky driving behavior recognition based on vehicle trajectory. International Journal of Environmental Research and Public Health. 2021;18(23). doi: 10.3390/ijerph182312373.

    Bastos JT, et al. Naturalistic driving study in Brazil: An analysis of mobile phone use behavior while driving. International Journal of Environmental Research and Public Health. 2020;17(17): 1-14. doi: 10.3390/ijerph17176412.

    Mahmud SMS et al. Application of proximal surrogate indicators for safety evaluation: A review of rec

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How to Cite
Xiong, X. (et al.) 2022. A Multi-Level Risk Framework for Driving Safety Assessment Based on Vehicle Trajectory. Traffic&Transportation Journal. 34, 6 (Dec. 2022), 959-973. DOI: https://doi.org/10.7307/ptt.v34i6.4154.

SPECIAL ISSUE IS OUT

Guest Editor: Eleonora Papadimitriou, PhD

Editors: Marko Matulin, PhD, Dario Babić, PhD, Marko Ševrović, PhD


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