Kodiak Uses Probabilistic Risk Assessment and AI Tool to Measure Autonomous Truck Safety
Kodiak Robotics has developed a Probabilistic Risk Assessment (PRA) methodology and an AI tool called BreakPoint to quantify and reduce safety risks for its autonomous trucks.
minutes
tens of thousands
What Happened
Kodiak's Probabilistic Risk Assessment (PRA) estimates the expected rate of collisions for the Kodiak Driver by decomposing scenarios into exposure, collision likelihood, and severity. It uses Bayesian probability theory to characterize uncertainty and updates as new data is collected, providing a quantitatively rigorous safety case.
BreakPoint is Kodiak's in-house AI validation tool that adversarially injects errors into the autonomy system to discover unknown failure modes. It searches for edge cases in simulation that could lead to collisions, surfacing vulnerabilities in minutes that would otherwise require tens of thousands of real-world miles to encounter.
Together, PRA and BreakPoint form a closed-loop system: BreakPoint finds failure modes and estimates their likelihood, PRA incorporates and prioritizes them, and the results guide engineering efforts. This cycle continuously shrinks the space of unknown hazardous scenarios, enabling scalable deployment of safe driverless trucks.
Why this matters
This approach allows Kodiak to autonomously discover rare failure modes and measure safety with mathematical rigor, addressing a key challenge in deploying driverless vehicles on public roads.
Terms in This Story
- PRA
- Probabilistic Risk Assessment: a methodology that quantifies risk using probability theory.
- BreakPoint
- A proprietary AI tool developed by Kodiak that adversarially searches for failure modes in autonomous driving systems.
- SOTIF
- Safety of the Intended Functionality (ISO 21448): a standard addressing hazards caused by systems performing correctly but encountering unexpected conditions.
- ODD
- Operational Design Domain: the specific conditions under which an autonomous system is designed to operate.
Summarised from the linked release; details can be imperfect — always verify against the original source.