TY - JOUR
T1 - Modeling driver steering behavior in restricted-preview boundary-avoidance tasks
AU - van der El, Kasper
AU - Pool, Daan M.
AU - van Paassen, Marinus M.
AU - Mulder, Max
PY - 2023
Y1 - 2023
N2 - In the design of human-like steering support systems, driver models are essential for matching the supporting automation's behavior to that of the human driver. However, current driver models are very limited in capturing the driver's adaptation to key task variables such as road width and visibility (i.e., 'preview' of the road ahead). This paper uses a recently proposed, novel control-theoretical model for centerline tracking to investigate driver steering in lane-keeping tasks with restricted and unrestricted preview, in an attempt to substantially extend this model's validity. Using data from a tailored driving simulator experiment, three driver control loops (feedforward, heading and position feedback) are separately quantified using system identification techniques. The results show that when preview is restricted, drivers use all of the remaining preview to anticipate the curves of the road ahead, and are no longer able to 'smooth' tight curves in the road trajectory (i.e., corner cutting). When sufficient preview and lane width are available, the time to line crossing increases, and steering behavior is less aggressive and more intermittent, or more 'satisficing'. The novel driver steering model captures these adaptations very well (over 95% of the steering actions) and can thereby be instrumental in realizing human-like steering automation and support systems.
AB - In the design of human-like steering support systems, driver models are essential for matching the supporting automation's behavior to that of the human driver. However, current driver models are very limited in capturing the driver's adaptation to key task variables such as road width and visibility (i.e., 'preview' of the road ahead). This paper uses a recently proposed, novel control-theoretical model for centerline tracking to investigate driver steering in lane-keeping tasks with restricted and unrestricted preview, in an attempt to substantially extend this model's validity. Using data from a tailored driving simulator experiment, three driver control loops (feedforward, heading and position feedback) are separately quantified using system identification techniques. The results show that when preview is restricted, drivers use all of the remaining preview to anticipate the curves of the road ahead, and are no longer able to 'smooth' tight curves in the road trajectory (i.e., corner cutting). When sufficient preview and lane width are available, the time to line crossing increases, and steering behavior is less aggressive and more intermittent, or more 'satisficing'. The novel driver steering model captures these adaptations very well (over 95% of the steering actions) and can thereby be instrumental in realizing human-like steering automation and support systems.
KW - Driver behavior
KW - Driver modeling
KW - Preview
KW - Reduced visibility
KW - Steering
UR - http://www.scopus.com/inward/record.url?scp=85150018323&partnerID=8YFLogxK
U2 - 10.1016/j.trf.2023.02.017
DO - 10.1016/j.trf.2023.02.017
M3 - Article
AN - SCOPUS:85150018323
SN - 1369-8478
VL - 94
SP - 362
EP - 378
JO - Transportation Research Part F: Traffic Psychology and Behaviour
JF - Transportation Research Part F: Traffic Psychology and Behaviour
ER -