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Peer-reviewedCC BY 4.0PLOS One

Research on a driving risk model for urban tunnel

  • Song Fang1
  • Wenting Lu2
  • Baoliang Wang
  • Ting Yang
  1. 1Jiangsu Vocational College of Electronics and Information, Huaian, China
  2. 2Jiangsu Provincial Department of Industry and Information Technology, Nanjing, China
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Abstract

This research introduces a novel driving risk assessment framework for urban tunnel environments, founded upon the physical principles of field theory. The framework conceptualizes three distinct but interacting fields: the kinetic energy field, behavioral field, and potential energy field. The study subsequently elucidates the evolutionary dynamics of the driving risk field, which is precipitated by the presence of neighboring vehicles, individual driving behavior patterns, and alterations in the roadway environment. A comprehensive driving risk field model for urban tunnels was constructed, and the variation patterns of the driving risk field forces acting on vehicles were examined. The results indicate the magnitude of the driving risk field force is inversely proportional to inter-vehicle spacing and the distance to the tunnel sidewall, while directly proportional to the relative speed between vehicles and the longitudinal slope gradient. Under identical conditions, the driving risk field force acting on vehicles at tunnel entrances and exits is greater than inside the tunnel, and the influence of speed on the risk field force exceeds that of distance. The proposed model effectively describes the variation trends of driving risks during vehicle travel in urban tunnels, and the outcomes of this research contribute to laying a theoretical groundwork for optimizing the planning, design, and management protocols of urban tunnels.

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Cite

BibTeXRIS
BibTeX
@article{fang2026research,
  title = {{Research on a driving risk model for urban tunnel}},
  author = {Song Fang and Wenting Lu and Baoliang Wang and Ting Yang},
  journal = {PLOS One},
  year = {2026},
  month = oct,
  doi = {10.1371/journal.pone.0345766},
  url = {https://doi.org/10.1371/journal.pone.0345766},
  note = {CC BY 4.0},
}
RIS
TY  - JOUR
TI  - Research on a driving risk model for urban tunnel
AU  - Song Fang
AU  - Wenting Lu
AU  - Baoliang Wang
AU  - Ting Yang
PY  - 2026
DA  - 2026/10/09
JO  - PLOS One
DO  - 10.1371/journal.pone.0345766
UR  - https://doi.org/10.1371/journal.pone.0345766
AB  - This research introduces a novel driving risk assessment framework for urban tunnel environments, founded upon the physical principles of field theory. The framework conceptualizes three distinct but interacting fields: the kinetic energy field, behavioral field, and potential energy field. The study subsequently elucidates the evolutionary dynamics of the driving risk field, which is precipitated by the presence of neighboring vehicles, individual driving behavior patterns, and alterations in the roadway environment. A comprehensive driving risk field model for urban tunnels was constructed, and the variation patterns of the driving risk field forces acting on vehicles were examined. The results indicate the magnitude of the driving risk field force is inversely proportional to inter-vehicle spacing and the distance to the tunnel sidewall, while directly proportional to the relative speed between vehicles and the longitudinal slope gradient. Under identical conditions, the driving risk field force acting on vehicles at tunnel entrances and exits is greater than inside the tunnel, and the influence of speed on the risk field force exceeds that of distance. The proposed model effectively describes the variation trends of driving risks during vehicle travel in urban tunnels, and the outcomes of this research contribute to laying a theoretical groundwork for optimizing the planning, design, and management protocols of urban tunnels.
SN  - 1932-6203
ER  -