@article{ref1,
title="How to define a safety tolerance zone for speed? Insights from the i-DREAMS project",
journal="Transportation research procedia",
year="2023",
author="Michelaraki, Eva and Kallidoni, Marianthi and Katrakazas, Christos and Brijs, Tom and Yannis, George",
volume="72",
number="",
pages="415-422",
abstract="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. <br><br>RESULTS indicated a strong relationship between the STZ level for speed and the independent variables of headway, distance travelled and medium harsh braking events.<p /> <p>Language: en</p>",
language="en",
issn="2352-1465",
doi="10.1016/j.trpro.2023.11.422",
url="http://dx.doi.org/10.1016/j.trpro.2023.11.422"
}