ArticlePloS one2026
Research on a driving risk model for urban tunnel.
Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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0 citing papers in PubMed.
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
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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