Automatic Vehicle Guidance:
The Experience of the ARGO Autonomous Vehicle



               

                                The results and the experience of the ARGO project, as well as other similar projects worldwide, are now described in a book, published by World Scientific Co. Publisher: "Automatic Vehicle Guidance: The Experience of The ARGO Autonomous Vehicle", by Alberto Broggi, Massimo Bertozzi, Alessandra Fascioli, and Gianni Conte.


The book cover

It is possible to download the flyer in pdf (174k) or in postscript (990k). In the following, the index of the book is presented.



Preface

Part I: Intelligent Vehicles
  • 1 Introduction
  • 2 Intelligent Vehicles and Machine Vision
    • 2.1 Evolution of Intelligent Transportation Systems
    • 2.2 Requirements of Intelligent Transportation Systems
    • 2.3 Sensing the Environment
    • 2.4 Machine Vision
  • 3 State of the Art
    • 3.1 Road Following
      • 3.1.1 Lane Detection
      • 3.1.2 Obstacle Detection
    • 3.2 Worldwide Projects
      • 3.2.1 Research carried out on the MOB-LAB Vehicle
      • 3.2.2 Research carried out at the Centro Ricerche FIAT
      • 3.2.3 Research carried out at the Universitat der Bundeswehr
      • 3.2.4 Research carried out at Daimler-Benz
      • 3.2.5 Research carried out at the Fraunhofer-Institut fur Informations und Datenverarbeitung
      • 3.2.6 Research carried out at the Laboratoire Central des Ponts-et-Chaussees de Strasbourg
      • 3.2.7 Research carried out at the Defence Evaluation and Research Agency
      • 3.2.8 Research carried out at Carnegie Mellon University
      • 3.2.9 Research carried out at The Ohio State University
      • 3.2.10 Research carried out at the University of Michigan
      • 3.2.11 Research carried out at the Massachusetts Institute of Technology
      • 3.2.12 Research carried out at the Phoang University of Science and Technology

Part II: The ARGO project
  • 4 Algorithms for Image Processing
    • 4.1 Lane Detection: a Model-Based Approach
      • 4.1.1 The multi-resolution approach
      • 4.1.2 The algorithm structure
      • 4.1.3 Performance analysis
      • 4.1.4 Critical analysis and evolution
    • 4.2 Obstacle Detection: a Model-Based Approach
      • 4.2.1 The vehicle detection algorithm
      • 4.2.2 Performance analysis
    • 4.3 The GOLD System
      • 4.3.1 Inverse Perspective Mapping
      • 4.3.2 Inverse Perspective Mapping and stereo vision
      • 4.3.3 Functionalities
      • 4.3.4 An extension of Inverse Perspective Mapping to handle non-flat roads
      • 4.3.5 Discussion
  • 5 Hardware Support for Real-Time Image Processing
    • 5.1 The PAPRICA Architecture
      • 5.1.1 Architectural issues
      • 5.1.2 Hardware system description
    • 5.2 Critical Analysis of the PAPRICA Architecture
      • 5.2.1 Memory organization and processor virtualization
      • 5.2.2 I/O problems
      • 5.2.3 Instruction set
      • 5.2.4 Architectural evolution
    • 5.3 The PAPRICA-3 Architecture
      • 5.3.1 Hardware system description
      • 5.3.2 Obstacle Detection on PAPRICA-3
    • 5.4 The MMX Technology
      • 5.4.1 MMX optimization issues
      • 5.4.2 Obstacle Detection on an MMX-based processor
    • 5.5 Comparison between PAPRICA-3 and MMX Processors
      • 5.5.1 Algorithms implementation
      • 5.5.2 Performance evaluation
      • 5.5.3 Discussion
  • 6 The ARGO Vehicle
    • 6.1 The Data Acquisition System
      • 6.1.1 The vision system
      • 6.1.2 The speed sensor
      • 6.1.3 The user interface
      • 6.1.4 The keyboard
    • 6.2 The Processing System
    • 6.3 The Output System
      • 6.3.1 The acoustical devices
      • 6.3.2 The optical devices
      • 6.3.3 The mechanical devices
    • 6.4 The Control System
    • 6.5 Functionalities
    • 6.6 Other Vehicle Equipments and Emergency Features

Part III: Project Results
  • 7 The MilleMiglia in Automatico Tour
    • 7.1 Description
      • 7.1.1 Dates and schedule
      • 7.1.2 Data logging
      • 7.1.3 Live broadcasting of the event via Internet
  • 8 Performance Analysis
    • 8.1 System Performance
      • 8.1.1 The vision system
      • 8.1.2 The processing system
      • 8.1.3 The visual processing
      • 8.1.4 The control system
      • 8.1.5 The man-machine interface
      • 8.1.6 Environmental conditions
      • 8.1.7 The data transmission system
    • 8.2 Statistical Analysis of the Tour
      • 8.2.1 Detailed analysis of one hour of automatic driving
    • 8.3 Discussion
  • 9 Closing Remarks

Appendices
  • A Morphological Implementation of the DBS Filter
  • B PAPRICA-3 Programming Environment
    • B.1 Low Level Programming Language
    • B.2 High Level Programming Language
    • B.3 Assembly Code Optimization
      • B.3.1 Deterministic optimization
      • B.3.2 Stochastic optimization
      • B.3.3 Parallel implementation of the code optimizer
  • C Global Communications on PAPRICA-3
    • C.1 Concurrent Communications on the ICN
    • C.2 Determining the Sets of Compatible Communications

References

Biographic Notes