Links between subjective assessments and objective metrics for steering, and evaluation of driver ratings

Abstract

During the development of new vehicles, finding correlation links between subjective assessments (SA) and objective metrics (OM) is an important part of the vehicle evaluation process. Studying different correlation links is important in that the knowledge gained can be used at the front end of development, during testing and when creating new systems. Both SA from expert drivers using a rating scale of 1–10 and OM from different tests measured by a steering robot were collected using standard testing protocols at an automotive manufacturer. The driver ratings were evaluated and the correlations were analysed using regression analysis and neural networks through a case study approach. Links were identified and were compared with related research.