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As the pedestrian’s rapid progress, pedestrian safety has recently assumed greater importance in the research population activities. To assess road user interactions at an unsignalized junctions with heterogeneous traffic complexity, innovative trajectory-based data was used and to make urban intersections safer for road users, the proposed severity levels will be used to test and evaluate numerous infrastructures and control upgrades. Study authors suggests an advanced pattern-based technique to characterize pedestrian-vehicle interactions based on road user behaviors. Surrogate safety measures (SSM) can be estimated more accurately with this study than with the regular grid-based analysis. In order to evaluate SSM (Speed, Time to Collision (TTC), Gap Time of the pedestrian and vehicle interactions) at an unsignalized crossing, Safe Distance and Stopping sight distance with trajectory data are to be estimated. Support Vector Machine (SVM) is used to classify severity grades based on specified indicators generated at an unsignalized junction in India. From the analysis, Severity at the intersection found as 8.12, 8.91sec respectively, Average gap time, stopping sight distance also calculated. Plots between Time to Collision and Gap Time for pedestrian passing first (PPF), vehicle passing first (VPF) are compared by developing a linear regression model and R2=0.684, 0.656 developed with some independent parameters respectively. Concluded that TTC for PPF is higher than VPF and by considering all the evaluated values this research had improved the methods for analysing and improving the safety of uncontrolled intersections.

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