Reconfigurable HW/SW Architecture of a Real-Time Driver Assistance System

Driver assistance systems significantly increase the driving comfort and can prevent accidents. On the other side, they require high performance and computations need to adopt to the environment to reach their goals. Reconfigurable architectures offer the requested flexibility and performance, if care is taken to partition the tasks in hardware and software parts. Elsewise, real-time requirements can't be fulfilled. In this paper, the implementation and a hardware/software partitioning of a driver assistance system for a reconfigurable architecture are presented. The assistance system detects taillights of ahead moving vehicles in dark environments or in tunnels and visualizes the results. A detailed description of the implementation on a reconfigurable platform is given. Furthermore, the experimental results demonstrate the effectiveness of the approach.

[1]  Jürgen Teich,et al.  The Erlangen Slot Machine: a highly flexible FPGA-based reconfigurable platform , 2005, 13th Annual IEEE Symposium on Field-Programmable Custom Computing Machines (FCCM'05).

[2]  Jason Schlessman,et al.  Hardware/Software Co-Design of an FPGA-based Embedded Tracking System , 2006, 2006 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'06).

[3]  Marco Platzner,et al.  Field Programmable Logic and Application , 2004, Lecture Notes in Computer Science.

[4]  Walter Stechele,et al.  Autovision – A Run-time Reconfigurable MPSoC Architecture for Future Driver Assistance Systems (Autovision – Eine zur Laufzeit rekonfigurierbare MPSoC Architektur für zukünftige Fahrerassistenzsysteme) , 2007, it Inf. Technol..

[5]  S. Wilson,et al.  FPGA implementation of an image segmentation algorithm using logarithmic arithmetic , 2005, 48th Midwest Symposium on Circuits and Systems, 2005..

[6]  Jürgen Teich,et al.  The Erlangen Slot Machine – A Platform for Interdisciplinary Research in Dynamically Reconfigurable Computing (ESM - Eine Hardware-Plattform für interdisziplinäre Forschung im Bereich des dynamischen rekonfigurierbaren Rechnens) , 2007, it Inf. Technol..

[7]  Walter Stechele,et al.  Hardware/software architecture of an algorithm for vision-based real-time vehicle detection in dark environments , 2008, 2008 Design, Automation and Test in Europe.

[8]  Danny Crookes,et al.  An FPGA-Based Image Connected Component Labeller , 2003, FPL.