Abstract

part of a long-term partnership between the World Bank and Brazil, the Federal Government of Brazil sought the World Bank’s assistance to review road safety management capacity in Brazil, building both on past experiences in the country and international best practices. This National Road Safety Management Capacity Review, therefore, was prepared by the World Bank, with the support of the Global Road Safety Facility (GRSF). The primary objective of the review is to evaluate the multi-sectoral capacity of road safety management in Brazil, identifying possible road safety challenges and presenting recommendations to address these challenges. The methodology of the review, in accordance with the guidelines of the World Bank Global Road Safety Facility, focused on examinations of key functional aspects of road safety, including institutions, legislation, financing, information, and capacities at all levels of government and among non-government actors. The review was prepared mainly based on interviews of key road safety stakeholders at the federal, state, and municipal levels, members of parliament, NGOs, and the private sector, in addition to direct inspection of roads and on-road behaviors, and the analysis of published research and reports on road safety. In addition, information and understanding gained from previous reviews of the states of São Paulo, Rio Grande do Sul, and Bahia were also incorporated.

Abstract

Friction plays a key role in causing slipperiness as a low coefficient of friction on the road may result in slippery and hazardous conditions. Analyzing the strong relation between friction and accident risk on winter roads is a difficult task. Many weather forecasting organizations use a variety of standard and bespoke methods to predict the coefficient of friction on roads. This article proposes an approach to predict the extent of slipperiness by building and testing an expert system. It estimates the coefficient of friction on winter roads in the province of Dalarna, Sweden using the prevailing weather conditions as a basis. Weather data from the road weather information system, Sweden (RWIS) was used. The focus of the project was to use the expert system as a part of a major project in VITSA, within the domain of intelligent transport system

Abstract

This article investigates the prospective and limitations in the application of potential intelligent transport system (ITS) functions to reduce accident risks, using a cause‐treatment relationship. The main causes of road accidents are described and appropriate ITS solutions (including advanced driver assistance systems and advanced traveller information systems) are presented as countermeasures. Anticipated impacts are discussed and indicate that several ITS have the potential of improving road safety and addressing specific accident causes. However, attention is required on particular aspects of their implementation as they may trigger adverse effects by imposing behavioural adaptation risks, and overestimation and over‐reliance on system capabilities. Further, user acceptability and strategic implementation issues are paramount to the successful introduction of these systems."br

Abstract

"jats:title"Objective"/jats:title" "jats:p"The emphasis of the study presented in this paper was to identify the attributes of drivers who are prone to cause a motorway crash. It was induced byambitions to enhance the effectiveness of traffic safety campaigns by identifying subgroups of drivers more precisely."/jats:p" "/jats:sec""jats:sec" "jats:title"Method"/jats:title" "jats:p"For this purpose we conducted an accident data analysis of all injury crashes 2012–2014 on Austrian motorways. Since 2012 it is possible for the police to label the “mainly responsible person” for the crash in the Austrian electronic accident recording system. It turned out that the quality of the data had some limitations, which required considerable pre-processing. The analysis by comparing the proportions of “mainly responsible” and “not responsible” drivers was done using descriptive statistics and logistic regression models. The binary characteristic, if a person was, according to the police, mainly responsible for the crash served as response variable. It was regressed on various personal and vehicle characteristics in order to identify their influence on the probability of causing a crash."/jats:p" "/jats:sec""jats:sec" "jats:title"Results/Conclusions"/jats:title" "jats:p"The results yield apparent tendencies, some of which support well-known pattern, e.g., the disproportionally high risk of motorcyclists and - to a lesser extent - young and elderly car drivers to cause an accident. Other results were less expected, e.g., the higher risk of foreign car drivers (compared to Austrian drivers) as well as drivers of light trucks, whereas drivers of heavy trucks revealed a below-average risk of causing a crash. The differences between male and female car drivers were small from young to middle age and fully disappeared in the high age group. There is some evidence that the frequency and experience of driving on a motorway have more influence on the risk of causing a crash than the driver’s gender. From this we conclude that motorway safety campaigns should on the one hand focus on the abovementioned groups of high risk drivers and on the other hand, in terms of car drivers, equally address both male and female drivers."/jats:p" "/jats:sec Document type: Article