A discrete-event simulation model for driver performance assessment: application to autonomous vehicle cockpit design optimization

TL;DR

This paper introduces a discrete-event simulation model to evaluate and optimize autonomous vehicle cockpit designs, focusing on driver workload, safety, and situational awareness during early-stage development.

Contribution

It develops a novel simulation tool integrating task analysis for assessing driver performance in autonomous vehicle cockpits.

Findings

Simulation tool effectively evaluates cockpit design options

Improves understanding of driver workload and safety implications

Supports early-stage design optimization

Abstract

The latest advances in the design of vehicles with the adaptive level of automation pose new challenges in the vehicle-driver interaction. Safety requirements underline the need to explore optimal cockpit architectures with regard to driver cognitive and perceptual workload, eyes-off-the-road time and situation awareness. We propose to integrate existing task analysis approaches into system architecture evaluation for the early-stage design optimization. We built the discrete-event simulation tool and applied it within the multi-sensory (sight, sound, touch) cockpit design industrial project.