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May 7, 2026International Journal of Computational Intelligence and Applications0 citations

Research on Key Technology of Vehicle-to-Infrastructure Cooperation Test and Evaluation under Extreme Cold Condition

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SLShuangshuang LiuZLZhipeng LiuLWLu Wang

Key Points

  • This research aims to define working conditions for vehicle-to-infrastructure cooperation in extreme cold environments and establish a robust early-warning model.
  • Developed three types of road surfaces: ice slab, compacting snow, and melted snow.
  • Established an early-warning model based on minimum safety distance for vehicles.
  • Conducted real vehicle verification of 84 test cases in 16 test scenarios in Heihe Autonomous Driving Test field.
  • Successfully defined early-warning parameters tailored for snow and ice conditions.
  • Completed validation with positive feedback from all 84 test cases under varying cold conditions.
  • Provided practical references for future development in vehicle-infrastructure applications in extreme cold environments.

Abstract

In view of the complex snow and ice environment in the high cold region, the existing standard design parameters for vehicle-to-infrastructure cooperation application are not referenced. The working conditions of ice and snow roads are defined, namely three types of road surface, namely ice slab, compacting snow and melted snow. The application message set is delivered through the roadside terminal, and the early-warning model under the minimum safety distance is established to obtain the latest early warning time. Develop test cases and test schemes for vehicle-infrastructure cooperation early-warning application scenarios with characteristics of cold regions and complete real vehicle verification of 84 test cases in 16 test scenarios in Heihe Autonomous Driving Test field, providing practical reference for vehicle-infrastructure cooperation application development in snow and ice environment.

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Cite This Study

Liu et al. (2026) studied this question.

synapsesocial.com/papers/69fc2c4b8b49bacb8b347e4fhttps://doi.org/10.1142/s1469026826410130
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