This chapter describes a modeling effort to define accident prediction models for first-class main roads outside built-up areas in Hungary using variables that are available and believed to exert an influence on safety performance. Models are proposed using the Generalized Linear Modeling (GLM) approach assuming a negative binomial error structure. The chapter also overviews design characteristics and accident statistics of two-lane rural first-class main roads. Five variables are used to predict accident frequencies, Annual Average Daily Traffic (AADT), posted speed, curve, roadway width and shoulder width. Traffic volume is used as an exposure to accidents and the length of the homogenous sections. Safety Performance Functions (SPFs) have been widely used in the traffic safety field for analyzing how the safety performance of road facilities is related to various road characteristics. The chapter reviews literature to demonstrate problems associated with conventional regression techniques used for accident prediction.

This paper explores how vehicle speeds are related to equitable, environmental, and economic sustainability of urban areas. This relationship is manifested primarily through associations between vehicle speeds and road crash casualties, severity of pedestrian crashes, generation of harmful emissions, and relative desirability of neighboring land. Reported research findings describing these associations are presented and discussed. Reported experiences with implementing various methods of influencing vehicle speeds, including automated enforcement, self-explaining roads, and in-vehicle systems, are presented and discussed. To support increased sustainability of urban areas, the following steps are recommended: (a) speed limits should be set to limit casualty risk and not to accommodate driver choices, (b) roadways in developed areas should be designed with 10-ft lanes and on-street parking and sidewalks, and (c) vehicle speeds in downtown and residential areas should be kept below 25 mph (preferably 20 mph). The paper also identifies gaps in knowledge about speed and sustainability.

The objective of this paper was to model the evolution of road safety as a function of motorization level. The authors completed a country-level as well as a time-dependent analysis focusing on countries for which data were available for a long period of time (1965 to 2009). For the statistical analysis, a function describing road safety trends (decline, turning, improvement) was proposed. Two coefficients in the model were estimated for each country and for each year, and their change over time is discussed. The results showed that the shape of the curve changed over time. In some countries, the decrease in the mortality rate became slower over time; however, a greater potential to improve road safety existed in other countries. Possible reasons for the general positive trends in road safety are the continuous improvement in engineering solutions (better infrastructure, safer cars) as well as road users who are better trained and skilled because of education and experience. In addition to the factors mentioned previously, the increased speed by which safety-related information and knowledge are disseminated contributes to the decrease in the differences in safety levels among countries.