A Fuzzy logic, risk-based autonomous vehicle control approach and its impacts on road transportation safety

Abstract

Autonomous Vehicles (AV) are expected to bring significant advantages in safety and efficiency to the Roadway Transport Systems (RTS). However, AVs will be incorporated into RTS only if their benefit outweigh safety risks and, thus, it is mandatory assuring that they will be safe during their operation. In our previous work published on IEEE Transaction on ITS, we proposed the Autonomous Automotive Cyber Physical Systems (A2CPS) Engine, a conceptual framework for the AV Supervision and Control Systems (SCS). Supported by a consolidated, international normative risk management process and by a proven-in-use SCS architecture adopted in other transport modes, we advocated this run-time, vehicle-centric risk management concept could minimize the safety risks related to the AV operation. In this paper, the engine concept is implemented using Fuzzy Logic and embedded in an computerbased AV model. Its capability in managing safety risks related to the AV operation, including the impacts of AV behavior over the RTS safety, is assessed using a simulation-based safety analysis approach. As a result, we observe this AV is able to identify potential collision conditions, estimating and assessing its level of risk during runtime execution and mitigating the associated risks by speed reduction or stopping the AV. Concluding, the engine concept has potential to manage the safety risks related to the operation of an AV in RTS scenarios in an innovative, cost-effective and safe way.