The Field of Safe Motion: Operationalizing Affordances in the Field of Safe Travel Using Reachability Analysis
This work bridges a gap between conceptual driving safety frameworks and computational robotics methods, providing an interpretable tool for assessing driving behavior, but it is an incremental step as it applies existing reachability analysis to a new domain.
The paper introduces the Field of Safe Motion (FSM), a quantitative safety model that operationalizes the conceptual Field of Safe Travel using reachability analysis to determine if a driver maintains a collision-free escape route. The model is demonstrated across various driving scenarios, showing its interpretability and ability to bound uncertainty about road users' future locations.
We present the Field of Safe Motion (FSM), a quantitative safety model for determining whether a driver maintains a collision-free escape route, or "out," at any given moment by accounting for that driver's physical capabilities and the foreseeable actions of other road users. The Field of Safe Travel (FST) provides a framework for representing the types of sensory information and actions available to drivers. However, the FST has remained conceptual in nature since its initial publication almost 90 years ago -- and a concrete computational operationalization is still lacking. At the same time, reachability analysis provides a quantitative basis for assessing the possible actions available to road users, using interpretable kinematic models, but reachability models have so far remained confined largely to the engineering and robotics literature. Bringing these two approaches together provides for an interpretable, quantitative tool for assessing driving behavior across a wide range of driving scenarios. Beyond being interpretable, our approach relies on a relatively small set of basic assumptions that are easy to enumerate and reason about. Furthermore, an interpretable reachability model paired with kinematic assumptions provides a way to bound uncertainty about road users' reasonably foreseeable future locations. We demonstrate the applicability of the FSM to different driving scenarios and discuss the strengths and weaknesses of the model.