S.B. Kolekar
12 records found
1
Authored
Quantifying drivers’ perceived risk is important in the design and evaluation of the behaviour of automated vehicles (AVs) and in predicting takeovers by the driver. A ‘Driver's Risk Field’ (DRF) function has been previously shown to be able to predict manual driving behaviour ...
Driver's risk field
A step towards a unified driver model
Gibson and Crooks (1938) argued that a ‘field of safe travel’ could qualitatively explain drivers' steering behavior on straights, curved roads, and while avoiding obstacles. This study aims to quantitatively explain driver behavior while avoiding obstacles on a straight road, ...
Current driving behaviour models are designed for specific scenarios, such as curve driving, obstacle avoidance, car-following, or overtaking. However, humans can drive in diverse scenarios. Can we find an underlying principle from which driving behaviour in different scenario ...
How road narrowing impacts the trade-off between two adaptation strategies
Reducing speed and increasing neuromuscular stiffness
When drivers encounter a road narrowing two potential adaptation strategies come into play that may increase safety margins: decreasing speed and increasing neuromuscular stiffness of the arms. These two adaption strategies have so far been studied in isolation. We expect that ...
The purpose of this study is to develop and validate a human-like steering model that can capture, not only the mean, but also the intradriver variability (IDV) of steering behavior, in both routine and emergency scenarios. The IDV model proposed in this study is based on the ...
A human-like steering model
Sensitive to uncertainty in the environment
The interaction between a human driver and an automated driving system may improve when the automation is designed in such a way that it behaves in a human-like manner. This paper introduces a human-like steering model, in which the driver adapts to the risk due to uncertainty ...