How to define a safety tolerance zone for speed? Insights from the i-DREAMS project

Several factors of driver state negatively impact road safety, such as distraction (in-vehicle or external), fatigue and drowsiness, health issues and extreme emotions. The aim of the current study is to define a Safety Tolerance Zone (STZ) for speed, and integrate crash prediction and risk assessment. A naturalistic driving experiment was conducted and data from a representative sample (N=20 drivers) was utilized. Explanatory variables of risk and the most reliable indicators were assessed. A feature importance algorithm extracted from Extreme Gradient Boosting (XGBoost) was used to evaluate the significance of variables on forecasting STZ. Additionally, a Neural Network model was implemented for real-time data prediction. Results indicated a strong relationship between the STZ level for speed and the independent variables of headway, distance travelled and medium harsh braking events.

• Record URL:
  • https://doi.org/10.1016/j.trpro.2023.11.422
• Record URL:
  • http://www.sciencedirect.com/science/article/pii/S2352146523007196
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/23521465
• Supplemental Notes:
  • © 2023 The Author(s). Published by Elsevier B.V. Abstract reprinted with permission of Elsevier.
• Authors:
  • Michelaraki, Eva
  • Kallidoni, Marianthi
  • Katrakazas, Christos
  • Brijs, Tom
  • Yannis, George
• Conference:
  • Transport Research Arena Conference (TRA Lisbon 2022)
  • Location: Lisbon , Portugal
  • Date: 2022-11-14 to 2022-11-17
• Publication Date: 2023

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: pp 415-422
• Serial:
  • Transportation Research Procedia
  • Volume: 72
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 2352-1465
  • Serial URL: http://www.sciencedirect.com/science/journal/23521465/
• Publication flags:

  Open Access (libre)

Subject/Index Terms

• TRT Terms: Crash risk forecasting; Driver performance; Predictive models; Risk assessment; Speeding; Traffic safety
• Subject Areas: Highways; Safety and Human Factors;

Filing Info

• Accession Number: 01906207
• Record Type: Publication
• Files: TRIS
• Created Date: Jan 29 2024 9:16AM