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Traffic Safety Sensitivity Analysis of Parameters Used for Connected and Autonomous Vehicle Calibration

Author

Listed:
  • Tasneem Miqdady

    (TRYSE Research Group, ETSI Caminos, Canales y Puertos, University of Granada, Campus de Fuentenueva, s/n, 18071 Granada, Spain)

  • Rocío de Oña

    (TRYSE Research Group, ETSI Caminos, Canales y Puertos, University of Granada, Campus de Fuentenueva, s/n, 18071 Granada, Spain)

  • Juan de Oña

    (TRYSE Research Group, ETSI Caminos, Canales y Puertos, University of Granada, Campus de Fuentenueva, s/n, 18071 Granada, Spain)

Abstract

Recently, the number of traffic safety studies involving connected and autonomous vehicles (CAVs) has been increasing. Due to the lack of information regarding the real behaviour of CAVs in mixed traffic flow, traffic simulation platforms are used to provide a reasonable approach for testing various scenarios and fleets. It is necessary to analyse how traffic safety is affected when key parameter assumptions are changed. The current study conducts a sensitivity analysis to identify the parameters used in CAV calibration that have the highest influence on traffic safety. Using a microsimulation-based surrogate safety assessment model approach (SSAM), traffic conflicts were identified, and a ceteris paribus analysis was conducted to measure the effect of gradually changing each parameter on the number of conflicts. Afterwards, a two-at-a-time sensitivity analysis was performed to explore the influence of simultaneously varying two parameters. The results revealed that reaction time, clearance, maximum acceleration, normal deceleration, and the sensitivity factor are key parameters. Studying these parameters two at a time revealed that low maximum acceleration, when combined with other parameters, consistently resulted in the highest number of conflicts, while combinations with short reaction time always yielded the best traffic safety results. This investigation broadens the understanding of CAV behaviour for future implementation for both manufacturers and researchers.

Suggested Citation

  • Tasneem Miqdady & Rocío de Oña & Juan de Oña, 2023. "Traffic Safety Sensitivity Analysis of Parameters Used for Connected and Autonomous Vehicle Calibration," Sustainability, MDPI, vol. 15(13), pages 1-21, June.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:13:p:9990-:d:1177798
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    References listed on IDEAS

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    1. Ye, Lanhang & Yamamoto, Toshiyuki, 2018. "Modeling connected and autonomous vehicles in heterogeneous traffic flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 269-277.
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