Concept for visualizing concealed objects to improve the driver's anticipation

Current advanced driver assistance systems (e.g. Emergency Brake Assistance, Lane Departure Warning, Lane Keeping Assistance and Blind Spot Detection) assist the driver in reacting to time-critical and unstable situations in a proper way. However, the anticipation of situations which are lying in the farer future is currently left primarily to the driver. In this paper, we present visualization concepts for concealed objects in order to support smart deceleration. Smart deceleration requires the anticipation of future traffic condition and the assistance of the driver in performing deceleration phases efficiently. In addition, safety is increased by reduction of potential criticality through the early deceleration phase. We have identified and categorized situations in which a broader anticipation is possible: situations with permanent obstacles, situations with temporarily stopped vehicles and situations with slower driving vehicles. An important issue when presenting information to the driver is the identification of the most suitable perspective. For visualizing the traffic situation in the surroundings of the driver’s car we established a virtual bird-eye perspective (VBEP), showing the traffic scene from a 3D viewpoint that is slightly raised above the driver and rigidly tethered to the car. This VBEP is a powerful concept to draw the driver’s attention to situations in the further future. On the basis of this concept we developed different visualizations and integrated them in the digital instrument cluster between the speedometer and the revolution counter.

[1]  Fabien Moutarde,et al.  Modular Traffic Sign Recognition applied to on-vehicle real-time visual detection of American and European speed limit signs , 2009, ArXiv.

[2]  Hirokazu Kato,et al.  Marker tracking and HMD calibration for a video-based augmented reality conferencing system , 1999, Proceedings 2nd IEEE and ACM International Workshop on Augmented Reality (IWAR'99).

[3]  Andry Rakotonirainy,et al.  Advancement in Advanced Driving Assistance Systems tools: Integrating vehicle dynamics, environmental perception and drivers' behaviours to assess vigilance , 2005 .

[4]  Gudrun Klinker,et al.  Speed Recommendations During Traffic Light Approach : A Comparison of Different Display Concepts , 2008 .

[5]  Paul Milgram,et al.  A Taxonomy of Real and Virtual World Display Integration , 1999 .

[6]  Andry Rakotonirainy,et al.  In-vehicle Technologies, Advanced Driver Assistance Systems and Driver Distraction: Research challenges , 2005 .

[7]  Alexandre Dugarry,et al.  Advanced driver assistance systems information management and presentation , 2004 .

[8]  A. Zelinsky,et al.  Stereo panoramic vision for monitoring vehicle blind-spots , 2004, IEEE Intelligent Vehicles Symposium, 2004.

[9]  L. Andreone,et al.  Developing a near infrared based night vision system , 2004, IEEE Intelligent Vehicles Symposium, 2004.

[10]  J.E. Gayko,et al.  Development, evaluation and introduction of a lane keeping assistance system , 2004, IEEE Intelligent Vehicles Symposium, 2004.

[11]  Dean A. Pomerleau,et al.  Overtaking vehicle detection using implicit optical flow , 1999 .

[12]  Takayuki Watanabe,et al.  Research on a Brake Assist System with a Preview Function , 2001 .

[13]  P. Milgram,et al.  A Taxonomy of Mixed Reality Visual Displays , 1994 .

[14]  Paul Milgram,et al.  Chapter 1 a Taxonomy of Real and Virtual World Display Integration 1.1.1 Augmented Reality , 1999 .

[15]  Dean A. Pomerleau,et al.  Overtaking vehicle detection using implicit optical flow , 1997, Proceedings of Conference on Intelligent Transportation Systems.

[16]  A. Herbin,et al.  Robust on-vehicle real-time visual detection of American and European speed limit signs, with a modular Traffic Signs Recognition system , 2007, 2007 IEEE Intelligent Vehicles Symposium.

[17]  Jerome Douret,et al.  A multi-model lane detector that handles road singularities , 2006, 2006 IEEE Intelligent Transportation Systems Conference.

[18]  Andry Rakotonirainy.  Human-Computer Interactions: Research Challenges for In-vehicle Technology , 2003 .