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WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control

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A mathematical model for predicting lane changes using the steering wheel angle.

Kim Schmidt¹, Matthias Beggiato², Karl Heinz Hoffmann¹

¹Institut für Physik, Technische Universität Chemnitz, D-09107, Germany.

Journal of Safety Research

|June 11, 2014

Summary

Early detection of driver intention, like steering wheel angle changes, can improve advanced driver assistance systems (ADAS). This helps predict lane changes, reducing false alarms and increasing driver acceptance.

Keywords:

Driving simulator Lane change Mathematical model Prediction Steering wheel angle

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Area of Science:

Human-Computer Interaction
Automotive Engineering
Road Safety

Background:

Driver acceptance is crucial for advanced driver assistance systems (ADAS) effectiveness.
Early detection of driver intention can enable selective system activation and reduce false alarms.

Purpose of the Study:

To explore early predictors of lane changes.
To identify measurable parameters indicating a driver's intention to change lanes.

Main Methods:

A driving simulator study analyzed 3111 lane changes from 51 participants.
Investigated driver behavior preceding lane changes, including secondary task disengagement and steering input.

Main Results:

Drivers disengaged from secondary tasks approximately 7 seconds before lane crossing.
A mean steering wheel angle of 2.5° was observed as drivers moved toward the lane.
Steering wheel angle shows promise as an early, measurable predictor of lane change maneuvers.

Conclusions:

A mathematical model of steering wheel angle is proposed for predicting lane changes.
This predictor can form the basis of a new ADAS to recognize driver intention.
Improved intention recognition can lead to more effective system activation/deactivation, reducing nuisance alarms and enhancing ADAS acceptance.