Automotive Engineering
Graduate Seminar
NOTICE OF SEMINAR PRESENTATION
CANDIDATE: Nathan Sheogobind
DEGREE SOUGHT: MASc
DATE: 6/5/2026
TIME: 11:30am
PLACE: Room 1101 CEI
TITLE: Developing a Model to Integrate Vestibular System Response into Virtual Drivability Evaluations
Abstract
Current drivability characterization methods are limited in two key areas. Firstly, a reliance on subjective evaluation methods is costly and time-intensive, extending the resources needed to develop new automobiles. Secondly, drivability characterizations are limited in their understanding of the human sensory feedback that influences a driver’s perception of drivability, often relying solely on subjective responses from testers. Recently, model-based drivability evaluations have been developed which use mathematical models to map subjective feedback to objective vehicle data, allowing engineers to predict and refine the drivability of a new vehicle early in the development cycle. However, while some methods incorporate psychophysical modelling, the bulk of model-based drivability evaluations do not incorporate human sensory feedback. The vestibular system is one of the key components that informs how humans perceive and control vehicles as it is the internal system by which humans perceive motion. This work aims to develop a framework where vestibular system responses can be estimated for vehicle acceleration and velocity inputs, which is an important step towards incorporating human sensory responses into drivability evaluation models. This framework aims to calculate head movement resulting from longitudinal vehicle accelerations using a linear and nonlinear models, and subsequently use established mathematical models of the vestibular system to estimate the sensory response to longitudinal accelerations. This approach can be integrated into a simulation workflow or be used in conjunction with hardware-in-the-loop test equipment such as chassis dynamometers, thus providing a model-based method that provides insight into human sensory responses to vehicle dynamics.