Validation of Simulated Safety Indicators with Traffic Crash Data

Borja Alonso, Vittorio Astarita, Luigi Dell’Olio, Vincenzo Pasquale Giofrè, Giuseppe Guido, Marcella Marino, William Sommario and Alessandro Vitale
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Borja Alonso: Department of Transport and Project and Process Technology, University of Cantabria, Avda. De Los Castros, 44, 39005 Santander, Spain
Vittorio Astarita: Department of Transport and Project and Process Technology, University of Cantabria, Avda. De Los Castros, 44, 39005 Santander, Spain
Luigi Dell’Olio: Department of Transport and Project and Process Technology, University of Cantabria, Avda. De Los Castros, 44, 39005 Santander, Spain
Vincenzo Pasquale Giofrè: Department of Civil Engineering, University of Calabria, 87036 Arcavacata, Italy
Giuseppe Guido: Department of Civil Engineering, University of Calabria, 87036 Arcavacata, Italy
Marcella Marino: Department of Civil Engineering, University of Calabria, 87036 Arcavacata, Italy
William Sommario: Department of Civil Engineering, University of Calabria, 87036 Arcavacata, Italy
Alessandro Vitale: Department of Civil Engineering, University of Calabria, 87036 Arcavacata, Italy

Sustainability, 2020, vol. 12, issue 3, 1-22

Abstract: The purpose of this document is to validate a new methodology useful for the estimation of road accidents resulting from possible driver distractions. This was possible through a statistical comparison made between real accident data between 2016 and 2018 in the city of Santander (Spain) and simulated data resulting from the application of the methodology on two areas of study. The methodology allows us to evaluate possible collisions starting from the knowledge of vehicular trajectories extrapolated from microsimulation. Studies show that there are good correlations between the real data and the simulated data. The results obtained show that the proposed methodology can be considered reliable and, therefore, it could be of fundamental importance for designers, since it would simplify the choice between different possible intervention scenarios, determining which is the least risky in terms of road safety.

Keywords: crash data; safety estimation; microsimulation; drivers’ distraction; road safety; traffic safety indicators; road safety performances (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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