Abstract
Road accident statistics highlight the importance of the number of fatalities and injuries. For example, 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 predefi ned 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 defi ne 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.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
More From: International Journal of Safety and Security Engineering
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.