Advanced Proactive Road Safety Management Techniques

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There is a pressing need for improved methods of road safety analysis to reduce the frequency and severity of road crashes. Most of current research on road safety focuses on the statistical techniques to model crashes and evaluate safety countermeasures. Less attention has been devoted to improve our understanding of crash causes and road user behavior. This is unfortunate, given the lack of complete understanding of the complex interaction of crash factors, how safety measures work and how they affect road user behavior. A major contribution of this research will be the development of novel methods that advance this understanding. This proposal focuses on three issues: i) evaluating surrogate safety measures and validating their relationship with crashes; ii) developing evasive action-based conflict indicators that incorporate elements of road user behavior and iii) developing a calibration framework for enhancing the use of micro-simulation models in safety analysis by increasing the correlation between simulated and field conflicts. The research attempts to contribute to traffic safety research in several ways. It tests and validates the use of traffic conflicts as surrogate safety measures and confirms their relationship with crashes. The development of a Bayesian framework for combining information from crash records and conflict data in a Bayesian framework is a new contribution to safety research. As well, the development of new evasive-action based traffic conflict indicators should provide the traffic conflict techniques with the ability to better measure conflict severity in high-mix, less-organized traffic environments. The research also proposes a new quantitative methodology for the integration of various measures of traffic conflicts (time proximity and behavior based) into a single safety index. Various conflict indicators are hypothesized to be of different and sometimes of independent nature. Ultimately, important road safety treatment decisions must be taken based on a singular inference on the underlying level of safety. Finally, the research will advance the use of micro-simulation models in road safety analysis by introducing a calibration process to maximize the correlation between simulated and field-measured conflicts. Calibrated model parameter values for various conflict types, traffic environments and location types will be determined.