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This paper presents a generic analytical framework tailored for surrogatesafety measures (SSMs) that is versatile across various highway geometries,capable of encompassing vehicle dynamics of differing dimensionality andfidelity, and suitable for dynamic, real-world environments. The frameworkincorporates a generic vehicle movement model, accommodating a spectrum ofscenarios with varying degrees of complexity and dimensionality, facilitatingthe prediction of future vehicle trajectories. It establishes a genericmathematical criterion to denote potential collisions, characterized by thespatial overlap between a vehicle and any other entity. A collision risk ispresent if the collision criterion is met at any non-negative time point, withthe minimum threshold representing the remaining time to collision. Theframework's proficiency spans from conventional one-dimensional (1D) SSMs toextended multi-dimensional, high-fidelity SSMs. Its validity is corroboratedthrough simulation experiments that assess the precision of the framework whenlinearization is performed on the vehicle movement model. The outcomes showcaseremarkable accuracy in predicting vehicle trajectories and the time remainingbefore potential collisions occur. The necessity of higher-dimensional andhigher-fidelity SSMs is highlighted through a comparison of conventional 1DSSMs and extended three-dimensional (3D) SSMs. The results showed that using 1DSSMs over 3D SSMs could be off by 300% for non-critical Time-to-Collision (TTC)values and about 20% for critical TTC values (below 1.5 seconds). Furthermore,the framework's practical application is demonstrated through a case study thatactively evaluates all potential conflicts, underscoring its effectiveness indynamic, real-world traffic situations.

Beyond 1D and oversimplified kinematics: A generic analytical framework for surrogate safety measures