This thesis presents the results of a research project which sought to find links between driver subjective ratings and objective measures of vehicle handling. The
experimental data used in this project has been made available from a previous research project. The experimental data was collected using a prototype vehicle which was used in 16 different configurations. Objective data was collected based around the ISO defined steady state, step input, and frequency response tests. Subjective
assessments were collected from eight trained test drivers using a numerical rating scale to a questionnaire covering various aspects of vehicle handling.
Analysis of the subjective assessments has been done to identify any shortcomings that may affect any subsequent analysis.
From the literature review, an approach that claims to relate four simple objective metrics to subjective measures of vehicle handling has been developed in two new ways. Firstly, the proposal was tested [1] with the large amount of subjective data available to see if good levels of correlation could be found between the proposed metrics and driver subjective ratings to specific handling questions. Secondly, the method was extended to include further simple metrics to try and improve links between the subjective and objective data [2].
Non-linear relationships in the correlation of subjective vs. objective data have been investigated for the first time [3] using non-linear genetic algorithms, which, in
addition have not previously been used to correlate driver subjective ratings with objective measures that describe vehicle handling.
From the results, it has been possible to specify ranges of preferred values of objective metrics in order to produce a subjectively satisfying vehicle.
Finally, the work discusses how the results obtained can be used by engineers to aid the vehicle design and development process.