ProFusion2 - Sensor Data Fusion for Multiple Active Safety Applications

The Preventive and Active Safety Applications project (PReVENT), contributes to the safety goals of the European Commission (EC). PReVENT addresses the function fields of safe speed and safe following, lateral support, intersection safety and protection of vulnerable road users and collision mitigation in order to cover the field of active safety. The majority of these functions are characterized by using perception strategies based on multi sensor platforms and multi-sensor data fusion. ProFusion as cross-functional activity has the responsibility to streamline the multi sensor data fusion in the functional field activities. This paper presents several aspects of the research work conducted in ProFusion2 (PF2). For the covering abstract see ITRD E134653.

[1]  T. Tatschke,et al.  Detection of Road Users in Fused Sensor Data Streams for Collision Mitigation , 2006 .

[2]  Christian Laugier,et al.  Efficient GPU-based Construction of Occupancy Girds Using several Laser Range-finders , 2006, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[3]  C. Laugier,et al.  Grid based fusion of off-board cameras , 2006, 2006 IEEE Intelligent Vehicles Symposium.

[4]  Gerd Wanielik,et al.  Multi level processing methodology for automotive applications , 2006, 2006 IEEE Intelligent Transportation Systems Conference.

[5]  Alberto Elfes,et al.  Occupancy grids: a probabilistic framework for robot perception and navigation , 1989 .

[6]  Fabio Tango,et al.  In-car machine-human interaction: how the new vehicle technologies which respond to the vehicles needs could match with the user-centered approach and contribute to shape a user-centered design approach , 2004, 2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583).

[7]  Angelos Amditis,et al.  ProFusion2 - Towards a modular, robust and reliable fusion architecture for automotive environment perception , 2006 .

[8]  Olivier Aycard Grid based fusion and tracking , 2006 .

[9]  Manuel Yguel,et al.  Efficient GPU-based Construction of Occupancy Grids Using several Laser Range-finders , 2008 .

[10]  Rudi Lindl,et al.  Three-Level Early Fusion for Road User Detection , 2006 .

[11]  C. Laurgeau,et al.  PUVAME - New French Approach for Vulnerable Road Users Safety , 2006, 2006 IEEE Intelligent Vehicles Symposium.