No abstract

The global fleet of powered two-wheelers (PTWs) is constantly increasing. In many countries, motorcycles, scooters and mopeds play a significant role in mobility, particularly in many of the world's large cities. As such, PTWs are becoming an important component of the transport system. However, they represent an important challenge for road safety. PTW riders are at far more risk than car drivers per kilometre ridden in terms of fatalities and severe injuries entailing long-term disability. Moreover, they have not benefited from safety improvements at the same pace as car occupants over recent decades. Addressing the issue of PTW safety is thus an essential contribution to the success of the United Nations' Decade of Action for Road Safety, which aims at halving the expected number of road deaths worldwide by 2020. This report reviews recent trends in powered two-wheeler crashes, the factors contributing to these crashes and their severity. It describes a set of countermeasures targeting user behaviours, the use of protective equipment, the vehicles and the infrastructure. Finally, it discusses motorcycle safety strategies in the context of a safe system

The objective of this paper is the analysis of road safety management in European countries and the identification of "good practice". A road safety management investigation model was created, based on several "good practice" criteria. Road safety management systems have been thoroughly investigated in 14 European countries on 2010, by means of interviews with both governmental representatives and independent experts, who filled in an extensive questionnaire. A reliable and accurate picture ("profile") was created for each country, allowing country comparisons. Then, statistical methods were used to make rankings of countries, and analyse the relationship between road safety management and road safety performance. The results of the analyses suggest that it is not possible to identify one single "good practice". Nevertheless, there were several elements that emerged as "good practice" criteria. On the basis of the results, recommendations are proposed at national and European level.

Abstract

The road traffic safety situation is severe worldwide and exploring driving behavior is a research hotspot since it is the main factor causing road accidents. However, there are few studies investigating how to evaluate real-time traffic safety of driving behavior and the number of driving behavior safety levels has not yet been thoroughly explored. This paper aims to propose a framework of real-time driving behavior safety level classification and evaluation, which was validated by a case study of driving simulation experiments. The proposed methodology focuses on determining the optimal aggregation time interval, finding the optimal number of safety levels for driving behavior, classifying the safety levels, and evaluating the driving safety levels in real time. An improved cross-validation mean square error model based on driver behavior vectors was proposed to determine the optimal aggregation time interval, which was found to be 1s. Three clustering techniques were applied, i.e., k-means clustering, hierarchical clustering and model-based clustering. The optimal number of clusters was found to be three. Support vector machines, decision trees and naï ve Bayes classifiers were then developed as classification models. The accuracy of the combination of kmeans clustering and decision trees proved to be the best with three clusters.