Risk Analysis in Road Safety: An Individual Risk Model for Drivers and Pedestrians to Support Decision Planning Processes

Risk Analysis in Road Safety: An Individual Risk Model for Drivers and Pedestrians to Support Decision Planning Processes

F.A. Marcianò A. Vitetta 

Department of Computer Science, Mathematics, Electronics and Transportation, Mediterranea University of Reggio Calabria, Italy

Page: 
265-282
|
DOI: 
https://doi.org/10.2495/SAFE-V1-N3-265-282
Received: 
N/A
| |
Accepted: 
N/A
| | Citation

OPEN ACCESS

Abstract: 

Road accident statistics highlight the importance of the number of fatalities and injuries. For exam-ple, in Italy, 215,405 road accidents occurred in 2009, resulting in 4,237 deaths and 307,258 injured. One aspect of road safety concerns the protection of ‘vulnerable road categories’ like pedestrians and cyclists. The probability of pedestrians being injured if they are involved in a road accident is higher since, unlike motorized users and cyclists, they do not wear any protection. Current hazard levels could be reduced through interventions targeting recognized network critical points (black spots). Planning must be preceded by risk analysis to support the decisional process through quantitative evaluation. For this reason, we present an individual risk model in the case of a road accident. The purpose is to estimate the probability of a pedestrian being involved in a road accident and the probability of being injured under pre-assigned conditions. The model calculates the individual risk of drivers and pedestrians moving in predefined accident scenarios that can be changed according to the analytical purpose. It also allows quantitative evaluation of how each attribute shares in the accident and how the risk level changes with changing attributes. Attributes are quantitative values that define the accident scenario and pedestrian and driver characteristics. In practice, the model could support the decision planning process, allowing both comparison of hazard levels of various hypothetical scenarios and analysis of the weight and elasticity of each attribute characterizing the accident scenario.

Keywords: 

drivers, pedestrians, risk analysis, road accident

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