How Kodiak uses AI and probabilistic risk assessment to measure autonomous trucking safety

Autonomous truck makers are developing tools to rigorously measure whether their AI-powered vehicles are safe enough to operate. One approach uses Probabilistic Risk Assessment, a methodology borrowed from aerospace and nuclear industries that breaks down scenarios into exposure frequency, collision likelihood, and collision severity to calculate expected collision rates, even for rare events that real-world testing alone cannot capture. A second tool called BreakPoint uses AI to systematically search for edge cases that could cause collisions or unsafe behavior, with findings feeding back into the risk assessment models. Together, these approaches aim to move beyond claims of safety toward quantifiable, mathematically rigorous proof that autonomous systems can handle real-world driving scenarios.