Developing improved crash prevention approaches through in-depth investigation of motorcycle crash causation patterns.

Despite advancements in road safety, Powered Two-Wheelers (PTWs) remain a vulnerable group with disproportionately high crash rates. This paper presents an in-depth analysis of PTW crashes in six European countries, with a case study of Loss of Control in Curves (LoCC), to address the gap between crash causation and prevention. By examining crash causation factors and their linkage to prevention strategies, the study illustrates various approaches for connecting causes and countermeasures.

In-built network-wide road safety assessment methodologies for rural roads.

Objective: Road traffic crashes are mainly caused by three concurrent factors: infrastructure, vehicle, and human factors. Regarding infrastructure, in recent decades, a series of management tools and procedures called Road Infrastructure Safety Management (RISM) have been proposed. The aim of RISM procedures is to support road authorities in the prevention and mitigation of future road traffic crashes.

Investigation of accidents involving powered two wheelers and bicycles - A European in-depth study.

Introduction: The number of road fatalities have been falling throughout the European Union (EU) over the past 20 years and most Member States have achieved an overall reduction. Research has mainly focused on protecting car occupants, with car occupant fatalities reducing significantly. However, recently there has been a plateauing in fatalities amongst 'Vulnerable Road Users' (VRUs), and in 2016 accidents involving VRUs accounted for nearly half of all EU road deaths.

Smeed's law and expected road fatality reduction: An assessment of the Italian case.

Introduction: Smeed's law defines the functional relationship existing between the fatality rate and the motorization rate.While focusing on the Italian case and based on the Smeed's law, the study assesses the possibility for Italy of reaching the target of halving the number of road fatalities by 2020, in light of the evolving socioeconomic situation.

Method: A Smeed's model has been calibrated based on the recorded Italian data.

Aggregated analysis of in-depth accident causation data.

Data collected from in-depth road accident investigations are very informative and may contain more than 500 accident-related variables for a single investigated case. These data may be used to get a more detailed knowledge on accident and injury causation associated with a specific accident scenario. However, due to their complexity, studies using in-depth data at aggregated levels are not common.

Latent risk and trend models for the evolution of annual fatality numbers in 30 European countries.

In this paper a unified methodology is presented for the modelling of the evolution of road safety in 30 European countries. For each country, annual data of the best available exposure indicator and of the number of fatalities were simultaneously analysed with the bivariate latent risk time series model. This model is based on the assumption that the amount of exposure and the number of fatalities are intrinsically related.