A Framework for Analysing Driver Interactions with Semi-Autonomous Vehicles
This addresses safety issues for drivers and operators in sectors like mining, logistics, and defense, but it is incremental as it builds on existing modeling and analysis techniques.
The paper tackles the problem of ensuring safety in semi-autonomous vehicles by proposing a framework that combines empirical human behavior models with environment and system models, and uses model checking to analyze interactions for desired safety properties, demonstrated through a case study involving driver fatigue.
Semi-autonomous vehicles are increasingly serving critical functions in various settings from mining to logistics to defence. A key characteristic of such systems is the presence of the human (drivers) in the control loop. To ensure safety, both the driver needs to be aware of the autonomous aspects of the vehicle and the automated features of the vehicle built to enable safer control. In this paper we propose a framework to combine empirical models describing human behaviour with the environment and system models. We then analyse, via model checking, interaction between the models for desired safety properties. The aim is to analyse the design for safe vehicle-driver interaction. We demonstrate the applicability of our approach using a case study involving semi-autonomous vehicles where the driver fatigue are factors critical to a safe journey.