Citation

Pickering SG, Brace CJ. Proc. Inst. Mech. Eng. Pt. D J. Automobile Eng. 2007; 221(4): 429-441.

Copyright

(Copyright © 2007, Institution of Mechanical Engineers, Publisher SAGE Publishing)

DOI

10.1243/09544070JAUTO347

PMID

unavailable

Abstract

This paper describes automated data-processing and manoeuvre detection techniques developed as part of a suite of tools used for the prediction of longitudinal vehicle driveability. The core task is to identify events of interest in recorded objective driveability time-series data and generate metrics describing these manoeuvres, which can then be correlated with subjective evaluations provided by the vehicle test drivers. The objective events of particular interest are the start of transients and gear-shift events. As a necessary precursor to the generation of the objective metrics, procedures were designed to check data integrity and to automatically replace data that were found to be faulty, ensuring that as few data points and as little testing time were wasted as is possible.
Of 741 tests analysed (average of 12 drivers for each of five vehicles), only 11 per cent of tests needed further manual attention following the automated processing. Of these, 64 per cent proved to be irrecoverable owing to data problems and were rejected. The processing and generation of metrics take approximately 1 s per set of test data, producing a time saving of approximately 95 per cent. This makes it possible to perform real-time processing and metric generation as part of a continuous testing scheme or real-time evaluation.

Language: en