Safety Force Field (SFF) vehicle software is designed specifically for collision avoidance. It acts as an independent supervisor on the actions of the vehicle’s primary planning and control system, which could be either human-driven or autonomous. Specifically, SFF performs real-time double-checks of the controls that were chosen by the primary system. If SFF deems the controls to be unsafe, it will veto and correct the primary system’s decision.
SFF is provably safe, in the sense that, if all road participants comply with SFF and the perception and vehicle controls are within expected design margins, then it can be mathematically proven that no collisions can occur.
SFF leverages perception data from various sensor types to compute a physics-based forward simulation of all perceived objects in surrounding traffic. SFF forward-computes them executing a Safety Procedure, which is a trajectory that would safely bring each object to a stop. For example, one safety procedure could be defined by braking-only, while another could be defined by steering to align with the direction of traffic and then braking.
Each object traces out a trajectory, or more formally, a volume in space-time that it would physically occupy during the execution of a safety procedure — we call this the vehicle’s Claimed Set. Overlap between claimed sets of different objects physically means there is risk they will occupy the same space at the same time in the future, i.e. collide. As soon as any claimed set overlap happens, SFF mandates that these objects take action to mitigate the situation, and computes the best real-time control commands for each object.
To decide what control command is “best” for each object, SFF leverages a mathematical function called safety potential that is a numerical measure of how safe a given situation is. SFF performs a perturbation analysis on claimed set overlaps between objects to see which control actions would help avoid the collision, and how much better they would be compared to the baseline safety procedure.