Multi-Agent Active Collaboration Between Drivers and Assistance Systems

Abstract The term Intelligent Vehicles refers currently to vehicles able to drive autonomously or able to provide pertinent information to the driver for safety, assistance, and comfort. Cognitive cars are intelligent vehicles with additional capabilities like being able to collaborate with the driver in operating conditions. In this chapter, a multi-agent system is used as a “digital butler” that does the interface between the driver and the machine. In order to test this approach, we consider an Advanced Driving Assistance System (ADAS) providing speed warnings when approaching dangerous areas. The system has been tested in an actual case carried out with an experimental vehicle. We report some illustrative collaboration between the driver and the machine.

[1]  Véronique Cherfaoui,et al.  Object-level fusion and confidence management in a multi-sensor pedestrian tracking system , 2008 .

[2]  Jean-Paul A. Barthès OMAS - a flexible multi-agent environment for CSCWD , 2011, Future Gener. Comput. Syst..

[3]  Dipti Srinivasan,et al.  Multi-Agent System in Urban Traffic Signal Control , 2010, IEEE Computational Intelligence Magazine.

[4]  Ho Gi Jung,et al.  A New Approach to Urban Pedestrian Detection for Automatic Braking , 2009, IEEE Transactions on Intelligent Transportation Systems.

[5]  Peter Stone,et al.  Multiagent interactions in urban driving , 2008 .

[6]  Nicolas Smith,et al.  Architectures of Map-Supported ADAS , 2011, 2011 IEEE Intelligent Vehicles Symposium (IV).

[7]  Véronique Berge-Cherfaoui,et al.  A system for driver behavioral indicators processing and archiving , 2006, 2006 IEEE Intelligent Transportation Systems Conference.

[8]  Klaus Henning,et al.  The "cognitive car": A roadmap for research issues in the automotive sector , 2006, Annu. Rev. Control..

[9]  Christian Ress,et al.  ELECTRONIC HORIZON - SUPPORTING ADAS APPLICATIONS WITH PREDICTIVE MAP DATA , 2006 .

[10]  M. Shawky,et al.  A distributed framework for real-time in-vehicle applications , 2005, Proceedings. 2005 IEEE Intelligent Transportation Systems, 2005..

[11]  Domitile Lourdeaux,et al.  Modelling Autonomous Virtual Agent Behaviours in a Virtual Environment for Risk , 2008, Int. J. Virtual Real..

[12]  Marie-Pierre Bruyas,et al.  Ergonomic guidelines for the design of pictorial information , 1998 .

[13]  Jean-Michel Hoc,et al.  Respective demands of task and function allocation on human-machine co-operation design: A psychological approach , 2002, Connect. Sci..

[14]  M. Althoff,et al.  Online Verification of Cognitive Car Decisions , 2007, 2007 IEEE Intelligent Vehicles Symposium.

[15]  Mohan M. Trivedi,et al.  Head Pose Estimation and Augmented Reality Tracking: An Integrated System and Evaluation for Monitoring Driver Awareness , 2010, IEEE Transactions on Intelligent Transportation Systems.

[16]  Satoshi Nakamura,et al.  Robust speech recognition in car environments , 1998, Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181).