Interactive gaze and finger controlled HUD for cars

Modern infotainment systems in automobiles facilitate driving at the cost of secondary tasks in addition to the primary task of driving. These secondary tasks have considerable chance to distract a driver from his primary driving task, thereby reducing safety or increasing cognitive workload. This paper presents an intelligent interactive head up display (HUD) on the windscreen of the driver that does not require them to take eyes off from road while undertaking secondary tasks like playing music, operating vent controls, watching navigation map and so on. The interactive HUD allows interaction in the form of pointing and selection just like traditional graphical user interfaces, however tracking operators’ eye gaze or finger movements. Additionally, the system can also estimate drivers’ cognitive load and distraction level. User studies show the system improves driving performance in terms of mean deviation from lane in an ISO 26022 lane changing task compared to touchscreen system and participants can undertake ISO 9241 pointing tasks in less than 2 s on average inside a Toyota Etios car.

[1]  Pradipta Biswas.  Exploring the Use of Eye Gaze Controlled Interfaces in Automotive Environments , 2016, SpringerBriefs in Computer Science.

[2]  Carl Jörgen Normark,et al.  Design and Evaluation of a Touch-Based Personalizable In-Vehicle User Interface , 2015, Int. J. Hum. Comput. Interact..

[3]  Christof Lutteroth,et al.  Gaze vs. Mouse: A Fast and Accurate Gaze-Only Click Alternative , 2015, UIST.

[4]  Shumin Zhai,et al.  The metropolis keyboard - an exploration of quantitative techniques for virtual keyboard design , 2000, UIST '00.

[5]  Pradipta Biswas,et al.  A new interaction technique involving eye gaze tracker and scanning system , 2013, ETSA '13.

[6]  Pradipta Biswas,et al.  Estimating Pilots’ Cognitive Load From Ocular Parameters Through Simulation and In-Flight Studies , 2019, Journal of eye movement research.

[7]  Angela Castronovo,et al.  Generating a Personalized UI for the Car: A User-Adaptive Rendering Architecture , 2013, UMAP.

[8]  Wonil Hwang,et al.  Haptic Seat Interfaces for Driver Information and Warning Systems , 2011, Int. J. Hum. Comput. Interact..

[9]  Yun Fu,et al.  hMouse: Head Tracking Driven Virtual Computer Mouse , 2007, 2007 IEEE Workshop on Applications of Computer Vision (WACV '07).

[10]  Luis Figueiredo,et al.  Hands-free interaction with a computer and other technologies , 2009, Universal Access in the Information Society.

[11]  Per Ola Kristensson,et al.  Subtle gaze-dependent techniques for visualising display changes in multi-display environments , 2013, IUI '13.

[12]  Bruce N. Walker,et al.  A Multimodal Air Gesture Interface for In Vehicle Menu Navigation , 2014, AutomotiveUI.

[13]  Justin S. Graving,et al.  Human Factors Design Guidance for Level 2 and Level 3 Automated Driving Concepts , 2018 .

[14]  Min Chen,et al.  Glyph-based Visualization: Foundations, Design Guidelines, Techniques and Applications , 2013, Eurographics.

[15]  Gerhard Rigoll,et al.  Gaze-based interaction on multiple displays in an automotive environment , 2011, 2011 IEEE International Conference on Systems, Man, and Cybernetics.

[16]  Patrick Langdon,et al.  Multimodal Intelligent Eye-Gaze Tracking System , 2015, Int. J. Hum. Comput. Interact..

[17]  Mark Ashdown,et al.  Combining head tracking and mouse input for a GUI on multiple monitors , 2005, CHI Extended Abstracts.

[18]  Mohan M. Trivedi,et al.  Hand Gesture Recognition in Real Time for Automotive Interfaces: A Multimodal Vision-Based Approach and Evaluations , 2014, IEEE Transactions on Intelligent Transportation Systems.

[19]  Gowdham Prabhakar,et al.  Detecting drivers’ cognitive load from saccadic intrusion , 2018 .

[20]  LOW-COST NON-IMAGING EYE TRACKER SYSTEM FOR COMPUTER CONTROL REFERENCE TO PRIORAPPLICATIONS , 2017 .

[21]  Hans-Werner Gellersen,et al.  Gaze and Touch Interaction on Tablets , 2016, UIST.

[22]  Sandra P Marshall,et al.  Identifying cognitive state from eye metrics. , 2007, Aviation, space, and environmental medicine.

[23]  Kyungdoh Kim,et al.  Utilization of Visual Information Perception Characteristics to Improve Classification Accuracy of Driver’s Visual Search Intention for Intelligent Vehicle , 2015, Int. J. Hum. Comput. Interact..

[24]  Yanxia Zhang,et al.  SideWays: a gaze interface for spontaneous interaction with situated displays , 2013, CHI.

[25]  Thorsten O. Zander,et al.  Combining Eye Gaze Input With a Brain–Computer Interface for Touchless Human–Computer Interaction , 2010, Int. J. Hum. Comput. Interact..

[26]  Ronald R. Mourant,et al.  Luminance Specifications for Automobile Instrument Panels , 1976, Human factors.

[27]  Albrecht Schmidt,et al.  Making use of drivers' glances onto the screen for explicit gaze-based interaction , 2010, AutomotiveUI.

[28]  Johannes Schöning,et al.  Combining Direct and Indirect Touch Input for Interactive Workspaces using Gaze Input , 2015, SUI.

[29]  Johannes Schöning,et al.  Combining Direct and Indirect Touch Input for Interactive Desktop Workspaces using Gaze Input , 2015 .