Comparing and validating models of driver steering behaviour in collision avoidance and vehicle stabilisation
Journal article, 2014

A number of driver models were fitted to a large data set of human truck driving, from a simulated near-crash, low-friction scenario, yielding two main insights: steering to avoid a collision was best described as an open-loop manoeuvre of predetermined duration, but with situation-adapted amplitude, and subsequent vehicle stabilisation could to a large extent be accounted for by a simple yaw rate nulling control law. These two phenomena, which could be hypothesised to generalise to passenger car driving, were found to determine the ability of four driver models adopted from the literature to fit the human data. Based on the obtained results, it is argued that the concept of internal vehicle models may be less valuable when modelling driver behaviour in non-routine situations such as near-crashes, where behaviour may be better described as direct responses to salient perceptual cues. Some methodological issues in comparing and validating driver models are also discussed.

steering

driving experience

low friction

driver models

collision avoidance

electronic stability control

Author

Gustav M Markkula

Chalmers, Applied Mechanics, Vehicle Engineering and Autonomous Systems

Ola Benderius

Chalmers, Applied Mechanics, Vehicle Engineering and Autonomous Systems

Mattias Wahde

Chalmers, Applied Mechanics, Vehicle Engineering and Autonomous Systems

Vehicle System Dynamics

0042-3114 (ISSN)

Vol. 52 12 1658-1680

Areas of Advance

Transport

Subject Categories

Vehicle Engineering

DOI

10.1080/00423114.2014.954589

More information

Created

10/7/2017