Head tracking based glance area estimation for driver behaviour modelling during lane change execution

This paper describes a method to analyse driver behaviour before lane change manoeuvres to detect the lane change intent before the actual manoeuvre itself is initiated. Recent research shows that driver's visual behaviour is an essential indicator to estimate intent to change lane. To create stochastic models for this process, it is necessary to detect which areas are frequently taken into focus by the driver (like looking towards the front window and side mirrors, for example). In a laboratory setting these regions could directly be measured using eye tracking methods. When focusing on solutions which can be integrated into cars under realistic settings, common eye tracking methods fail. More stable solutions are head tracking systems, mostly based on mono or stereo cameras. In this article an approach is presented for estimating the drivers glance areas from head tracking data.

[1]  Matthias J. Henning.  Preparation for lane change manoeuvres: Behavioural indicators and underlying cognitive processes , 2009 .

[2]  Peter Norvig,et al.  Artificial Intelligence: A Modern Approach , 1995 .

[3]  Klaus C. J. Dietmayer,et al.  Driver intention inference with vehicle onboard sensors , 2009, 2009 IEEE International Conference on Vehicular Electronics and Safety (ICVES).

[4]  L. Stark,et al.  Types of gaze movement: Variable interactions of eye and head movements , 1982, Experimental Neurology.

[5]  Mohan M. Trivedi,et al.  On the Roles of Eye Gaze and Head Dynamics in Predicting Driver's Intent to Change Lanes , 2009, IEEE Transactions on Intelligent Transportation Systems.

[6]  Gunnar Blohm,et al.  Differential influence of attention on gaze and head movements. , 2009, Journal of neurophysiology.

[7]  Shigeo Abe DrEng.  Pattern Classification , 2001, Springer London.

[8]  David G. Stork,et al.  Pattern Classification , 1973 .

[9]  M. Trivedi,et al.  Head and eye gaze dynamics during visual attention shifts in complex environments. , 2012, Journal of vision.

[10]  Colin Bauer,et al.  A driver specific maneuver prediction model based on fuzzy logic , 2012 .

[11]  Alex Pentland,et al.  Graphical models for driver behavior recognition in a SmartCar , 2000, Proceedings of the IEEE Intelligent Vehicles Symposium 2000 (Cat. No.00TH8511).

[12]  Firas Lethaus,et al.  Do eye movements reflect driving manoeuvres , 2006 .

[13]  Mohan M. Trivedi,et al.  Lane Change Intent Analysis Using Robust Operators and Sparse Bayesian Learning , 2005, IEEE Transactions on Intelligent Transportation Systems.

[14]  Firas Lethaus,et al.  Using Pattern Recognition to Predict Driver Intent , 2011, ICANNGA.

[15]  Mohan M. Trivedi,et al.  On-road prediction of driver's intent with multimodal sensory cues , 2011, IEEE Pervasive Computing.