Measurement and modelling of driver learning of steering control during successive obstacle avoidance manoeuvres
Year: 2024
Type: article
Abstract: Understanding of driver behaviour can provide invaluable insight for the design of vehicles and driver assistance systems. Most existing human driver models do not incorporate driver learning or the effect of a driver's confidence in their predictions of future states, both of which affect human-generated control actions. In this paper, human driver steering control is assessed based on experimental data, then a driver model is proposed which captures driver learning and is capable of reproducing a wide range of human control styles by the selection of appropriate parameters. The driver model learns an internal model of the vehicle dynamics from experience, using a Gaussian Process, then selects control actions via Model Predictive Control. The results verify the model's capacity to capture the learning drivers achieve over time and to replicate various observed cautious and adventurous behaviours.
Source: Apollo (University of Cambridge)
DOI: 10.17863/cam.114444
Authors: Fieldhouse, Harry, Keen, Steven, Cole, David
Language: English
Subfield: Automotive Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
Award: G8210905733
OpenAlex ID: W6943910943
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