Investigating and Modeling the Effects of Speed in Lane Keeping on Winding Roads

Abstract

Accurate models of driver steering behavior are essential with ever-growing automation in road vehicles. In this project, the effects of driving speed on steering behavior on winding roads are investigated and modeled. Data were collected in a human-in-the-loop curve driving experiment with fifteen participants, who were asked to drive at five different constant speeds between 30 and 70 km/h and at variable speed, using gas and brake pedals. This experiment was performed in the fixed-base simulator of the Human-Machine Laboratory at the Faculty of Aerospace Engineering. The collected data show that drivers do not use a constant portion in time or distance of the road ahead at different speeds. Instead, they put their visual aim point at an approximately constant time away, while they filter a constant distance after this. Moreover, drivers’ response time delays, lead time-constants, and position-to-heading feedback gains decrease with increasing driving speed. In a next step, a speed-dependent linear-parameter-varying (LPV) model was constructed to describe variable speed steering behavior. For some participants and parts of the trajectory, measured steering wheel deflections are modeled more accurately by this model than linear-time-invariant (LTI) estimates. However, simpler LTI models on average explain the measured variable speed steering better. Overall, this research clearly shows that drivers adapt their steering behavior to driving speed and how key steering behavior parameters are adjusted with speed. Modeling this adaptation for realistic driving, however, is challenging due to the still unknown dynamics between speed and parameter adaptation.