Worldwide, more than 1.25 million people die annually in road traffic accidents and between 20 and 50 million more are injured. By 2030, highway-related crashes are projected to be the 5th leading cause of death in the world. Road accidents have a number of contributing factors, including roadway conditions, vehicle conditions, and factors related to the road users. While some of these factors have been studied extensively by researchers very few focused on quantifying the relationship between accidents frequency and pavement quality. Before 1990s, due to the lack of pavement data collection technology, it was very difficult to carry out state-wide scale studies relating pavement quality and road safety. However, in the past decades, there has been a huge growth and awareness in the importance of road safety as a public health issue, leading to a significant increase of research in the topic. Researchers started to study other contributing factors to accidents occurrence such as the pavements quality. Moreover, with the development of high-speed friction measurement tools, agencies can now include friction into network level Pavement Management Systems (PMSs). Therefore, incorporating safety concerns is one of the urgent needs of PMSs, not only in order to optimize the management of the resources but also, and above all, towards the reduction of road fatalities. Despite the fact that there is limited research on the topic, important results were already achieved proving that there is a correlation between the frequency of traffic accidents and variables, which state the condition of the pavement such as friction, macrotexture and microtexture. This article aims to present a short review of the existing literature in Accident Frequency Prediction Models and Modelling Techniques already used or that can be used in PMSs. Moreover, the most interesting Accident Frequency Prediction Models for inclusion in PMSs will be tested with real data provided by a Portuguese Road Agency. The final part of the paper contains the conclusions and presents how these models can be incorporated in PMSs.

road, accident prediction model, traffic, pavement quality, friction, macrotexture.