Diss. Stockholm : Kungliga tekniska högskolan, 2005

In order to achieve sustainable long-term transport infrastructure development, there is a growing need for fast, reliable and effective methods to evaluate and predict the impact of traffic safety measures. Recognising this need, and the need for an active traffic safety approach, this thesis focuses on traffic safety assessment and prediction based on the use of safety indicators that measure the spatial and/or temporal proximity of safety critical events. The main advantage of such measures is that they occur more frequently than accidents, and therefore require relatively short periods of study to establish values that can later be used for comparison, or for accident prediction purposes. There are a number of more generally accepted safety indicators including: Time-to-Accident, Time-to-Collision, and Post-Encroachment Time. These are based on different underlying principles and measurement techniques, including both on-site subjective estimation, and objective photometric measures. A major part of the work presented in this thesis, concerns identifying the potential and limitations of the different safety indicators with regard to their validity and reliability, and practical use for safety assessment and prediction purposes. This is done in conjunction with field studies in the urban and suburban environment, at both signalised and unsignalised intersections. Results from these studies indicate that on-site observation methods provide useful quantitative and qualitative information relatively quickly and efficiently, provided that they are used correctly. On the other hand, the methods based on photometric measurement (video-analysis) proved arduous and time-consuming. Furthermore, there are questions regarding the abilities of the Time-to-Collision and Post-Encroachment Time safety indicators to adequately represent interaction severity, suggesting possible flaws in fundamental concepts related to construct validity. Importantly, results showed that the relationship between safety indicators and traffic accidents is complex and equivocal, where many different factors and processes can impose a significant influence on safety. This makes generalised predictive modelling a particularly difficult task for safety analysts.