Quantifying Traffic Conflict Severity Using a Multi-Factor Nonlinear Finite Element Framework: The Role of Vehicle Mass, Impact Geometry, and Occupant-Compartment Proximity

Traffic conflict analysis offers a proactive alternative to crash-based safety assessments by identifying and evaluating near-crash events before they escalate into actual collisions. Previous research established a conflict detection framework capable of identifying critical conflict points, anticipating likely crash types, and defining corresponding crash influence points (CIPs), while demonstrating the value of kinetic energy (KE) as a meaningful indicator of conflict severity. Building on this foundation, the present study introduces a complementary analytical framework which isolates the influence of vehicle mass, arrangement, and geometry in shaping severity outcomes. To control for speed effects, the initial velocity in all simulations was standardized at 35 mph, except for rear-end scenarios in which the lead vehicle was modeled as stationary to reflect realistic pre-impact conditions. This design enabled focused analysis of mass disparity, vehicle positioning within the crash-prone zone (leading versus following), angle of impact (AOI), and CIP location. Sixty-three finite element crash simulations were conducted involving a sedan, minivan, and single-unit truck (SUT) across diverse crash types, including head-on, angle, right-angle, and side-swipe collisions. Severity was evaluated using KE dissipation, deformation proximity to occupant compartments, and detailed examination of crash dynamics. Findings indicate that mass configuration, AOI, and CIP location are decisive in determining severity, with SUT-to-SUT head-on crashes producing the most severe outcomes and non-driver-side side-swipes exhibiting the lowest severity. These insights provide a physics-grounded framework for prioritizing safety countermeasures, enabling decision-makers to target the most critical conflict configurations in high-risk traffic environments.