Autonomous Vehicles E-Book

Tomasz Krysinski

• Herausgeber: John Wiley & Sons
• Kategorie: Fachliteratur
• Serie: ISTE Invoiced
• Sprache: Englisch

Seitenzahl: 234

Veröffentlichungsjahr: 2026

Beschreibung

The development of autonomous vehicles represents a major technological breakthrough, revolutionizing mobility through the integration of advanced technologies at the intersection of artificial intelligence (AI), mechatronics and control sciences. This heralds a new era of disruptive innovation for the automotive and aerospace industries.

Autonomous Vehicles offers an in-depth, structured analysis of the scientific and technical challenges associated with autonomy, while also addressing the industrial, societal, legal and safety issues specific to the automotive and aerospace sectors. This book presents the key functions of automated driving and piloting, sensor technologies and their role in environmental perception, as well as data processing and exploitation strategies based on conventional algorithmic approaches and techniques derived from AI.

This detailed book offers concrete examples from industrial use cases, offering a rigorous and up-to-date overview of a rapidly changing field, grounded in close collaboration between academia and industry.

Leseprobe

Table of Contents

Cover

Table of Contents

Title Page

Copyright Page

Foreword

Preface

Introduction

I.1. Autonomy towards improved safety

I.2. Societal and economic aspects

I.3. Improving the environmental impact

I.4. Acceptance and ethics aspects

I.5. Legal aspect

1 Vehicle Architecture

1.1. Generalities and levels of autonomy

1.2. Evolution of features associated with autonomy

1.3. Vehicle architecture and control chain

1.4. Vehicle architecture review

2 Features and Autonomy

2.1. Simple or comfort control features

2.2. Complex features specific to a phase of use

2.3. Complex traffic and security features

3 Sensors and Technologies

3.1. Introduction

3.2. Sensor review and comparison

4 Data Mining and Fusion

4.1. Introduction to the concept of data fusion

4.2. DTMO: detection and tracking of moving objects

4.3. SLAM: mapping and localization

Conclusion

References

Index

Other titles from iSTE in Systems and Industrial Engineering – Robotics

End User License Agreement

List of Tables

Chapter 1

Table 1.1.

Classification of failure criticalities

Chapter 3

Table 3.1. Advantages and disadvantages of sensors of a magneto-inertia...

Table 3.2.

Comparison of sensor performance

List of Illustrations

Introduction

Figure I.1. The three fundamental pillars of land or air vehicle autono...

Figure I.2(A). Number of people killed in light vehicle accidents over ...

Figure I.2(B). Number of people killed in accidents involving heavy goo...

Figure I.3. Evolution of the accident rate on commercial flights 2015–2...

Figure I.4. Distribution of fatal road accidents in France in 2018 (sou...

Figure I.5. Human factors in commercial air transport and automobile ac...

Figure I.6. Distribution in % of road transport modes in Île-de-France ...

Figure I.7.

Comparison of costs according to vehicle use.

Figure I.8.

Platooning technique for trucks (source: Jacob, JTR 2017).

...

Figure I.9.

Formation flying (Fello’Fly project, Airbus).

Chapter 1

Figure 1.1.

Scale of autonomy levels according to the SAE organization

...

Figure 1.2. Autonomy levels for aeronautical systems for the drone-type...

Figure 1.3.

Technologies associated with vehicle autonomy

Figure 1.4. Chronological evolution of technologies towards an autonomo...

Figure 1.5.

Functional integration diagram of vehicle autonomy

Figure 1.6.

Functional integration diagram of aircraft autonomy

Figure 1.7.

Mechanical, hydromechanical or electrical flight controls

Figure 1.8.

Architectures of electric actuators of servo drives

Figure 1.9.

Integration of servo controls on aircraft (source: Airbus)

...

Figure 1.10. Fatigue curve of metallic materials or Wöhler curve or S–N...

Figure 1.11.

Stromeyer model (“fatigue curve”)

Figure 1.12. Example of stress spectrum: distinction between LCF and HC...

Figure 1.13. Example of the variation of effort over time for a maneuve...

Figure 1.14.

Example of stress variation over time for a maneuver

Figure 1.15.

Haigh diagram

Figure 1.16.

Failure rate

Figure 1.17. Schematic diagram of the impact of redundancy on reliabili...

Figure 1.18.

Modular duplex or triplex redundancy. Example: sensors

Figure 1.19. Example of the installation of the three ADIRU units seen ...

Figure 1.20.

Architecture of the autopilot on aircraft (source: Airbus)

Figure 1.21.

Schematic definition of the flight envelope [BRE 01]

Figure 1.22.

Type of law and degradation

Figure 1.23.

Blade pitch control (source: Airbus Helicopters)

Figure 1.24. Schematic diagram of a servo control: single body (source:...

Figure 1.25.

Servo controls: double body

Figure 1.26.

Servo control installation

Figure 1.27.

Helicopter control chain (source: Airbus Helicopters)

Figure 1.28. Classification of flight formulas (source: Airbus Helicopt...

Figure 1.29. Comparison of actuators and trajectory DDL (source: Airbus...

Figure 1.30.

Different flight formulas and their actuators [CHA 23]

Figure 1.31.

Example of failure of two rotors out of six

Figure 1.32.

Comparison of the complexity of VTOL formulas

Figure 1.33.

Electrohydraulic power steering

1

Figure 1.34.

Electric power steering (DAE, EPS or EPAS)

2

Chapter 2

Figure 2.1.

ASR assistance system (see: https://www.forum-audi.com)

Figure 2.2.

ESP system on vehicle: example of oversteer

Figure 2.3.

Line tracking system

Figure 2.4.

ABS brake assist system

Figure 2.5.

Helicopter control chain with or without SEMA

Figure 2.6. Associated mechanical flight control architecture to an aut...

Figure 2.7. Fly-by-wire flight control architecture and autopilot (AFCS...

Figure 2.8. Control stick with AFCS disengagement button (D) (Automatic...

Figure 2.9.

Aircraft braking distance and runway threshold

Figure 2.10.

A320 braking system

Figure 2.11.

Effectiveness of the aircraft anti-skid system (ABS)

Figure 2.12. ILS system integration for trajectory control during landi...

Figure 2.13.

ILS or instrument landing aid system

Figure 2.14.

Using the localizer and glide path antennas

Figure 2.15. Processing of the received signal for demodulation and exp...

Figure 2.16.

Indicators seen by the pilot in the cabin

Figure 2.17. Distribution of accidents by flight and by phase in 2001–2...

Figure 2.18.

Diversity of landing zones for an aircraft

Figure 2.19.

Variety of landing zones for a helicopter

Figure 2.20. Various projects for landing or takeoff assistance (source...

Figure 2.21. Experimentation of the EAGLE platform on H225 (source: Air...

Figure 2.22. Automatic control diagram for landing on a ship’s deck...

Figure 2.23.

Project VSR700: autonomous drone from Airbus Helicopters

Figure 2.24. Schematic diagram of landing and taxiing assistance (sourc...

Figure 2.25. Comparison of pollutant emissions according to technologie...

Figure 2.26.

Energy losses of a single truck

Figure 2.27.

Road platoon communication: the use of LiDAR

Figure 2.28.

Truck convoy safety

Figure 2.29.

Examples of disruptions that can affect performance

Figure 2.30.

Trucks in convoy

Figure 2.31. Urban land traffic management: connected vehicles (author:...

Figure 2.32.

Communication architecture of connected vehicles

Figure 2.33.

Use of marginal vortices for V-shaped formations

Figure 2.34.

Principle of convoy flight formation

Figure 2.35. Urban air traffic management: connected aircraft (author: ...

Figure 2.36. Example of the need for power line detection for a helicop...

Chapter 3

Figure 3.1.

Functional description of an autonomous vehicle

Figure 3.2.

Installation of sensors on autonomous land or air vehicles

...

Figure 3.3.

Accelerometer and gyroscope: MEMS technology

Figure 3.4.

Schematic of an inertial/GNSS navigation system

Figure 3.5.

Diagram of the structure of an inertial unit [JAR 19]

Figure 3.6. Diagram of the GPS system and redundancy of satellite measu...

Figure 3.7.

Electromagnetic spectrum and environmental sensors

Figure 3.8.

Steps of information processing by a VIS camera

Figure 3.9.

Defining the focal length of a camera

Figure 3.10.

Shallow and large depths of field

Figure 3.11.

Impact of aperture on the depth of field

Figure 3.12.

Impact of focal length on the field of view

Figure 3.13.

Photoelectric effect and photosensitive cell technology

Figure 3.14.

Network of cells or photosites forming the sensor

Figure 3.15.

Defining the resolution of a vision sensor

Figure 3.16.

Discretization and digitization of a black-and-white image

Figure 3.17.

Illustration of the Bayer filter

Figure 3.18. Comparison of images with a traffic light depending on the...

Figure 3.19.

Stereoscopic vision of nonsynchronous cameras [ELB 18]

Figure 3.20.

Uses of cameras for vehicle driver assistance

Figure 3.21.

360° camera vision system (source: Airbus)

Figure 3.22. Detection of the center of the landing zone (red dot) (sou...

Figure 3.23. Installation of cameras on rotary wings: EAGLE (source: Ai...

Figure 3.24. Example of the image seen in the cockpit for pilot assista...

Figure 3.25.

Visible and infrared spectra used by cameras

Figure 3.26. Comparison of VIS (visible) image and SWIR image in low-li...

Figure 3.27. Comparison with the presence of fog in the VIS (visible) (...

Figure 3.28. Evolution of optical density due to fog according to the w...

Figure 3.29. Evolution of optical density/absorbance of white and black...

Figure 3.30. Evolution of reflectivity contrast for SWIR camera dependi...

Figure 3.31. Comparison of thermal camera and SWIR facing a window (sou...

Figure 3.32.

Emission of acoustic waves for SONAR

Figure 3.33.

How ultrasonic sensors work

Figure 3.34.

Ultrasonic sensors on cars

Chapter 4

Figure 4.1.

Diagram of data mining and fusion

Figure 4.2.

General concept of data fusion

Figure 4.3. Information fusion types based on the link between informat...

Figure 4.4.

Low-level fusion method between a LiDAR and VIS camera

Figure 4.5. Intermediate-level fusion method between a LiDAR and VIS ca...

Figure 4.6.

Synthesis of low, medium and high fusion level methods

Figure 4.7.

Principle of sensor calibration before data fusion

Figure 4.8.

Bayesian data fusion

Figure 4.9.

Schematization of the Kalman filter

Figure 4.10.

Continuous-time extended Kalman filter (EKF) [DEV 93]

Figure 4.11.

Examples of error risks when reading signs

Figure 4.12.

Classification of signs as neural networks

Figure 4.13. Different types of learning for obstacle detection in auto...

Figure 4.14.

Obstacle collision avoidance system (OCAS)

Figure 4.15. Implementation of LiDAR on the RSAS system (source: Airbus...

Figure 4.16.

RSAS system interface (source: Airbus Helicopters)

Figure 4.17. Evolution of the sound alarm for the obstacle detection sy...

Figure 4.18. Static evaluation of a 360° obstacle detection dummy anten...

Figure 4.19. Detection of a large cell phone transmission antenna and a...

Figure 4.20. Hovering near a building: RSAS (source: Airbus Helicopters...

Figure 4.21. Hovering near trees or hedges: RSAS (source: Airbus Helico...

Figure 4.22. Helicopter hovering in a quarry. Comparison of the RSAS im...

Figure 4.23. Principle of calibration, intrinsic and extrinsic paramete...

Figure 4.24. Conversion of spatial coordinates in pixels on the image [...

Figure 4.25.

Spatial coordinate conversion process

Figure 4.26.

LiDAR sensor and camera targets

Figure 4.27. Camera and LiDAR implementation for improvement in pilot v...

Figure 4.28. Combination of two visualization methods SVS and EFVS: CVS...

Figure 4.29. Trajectory displayed by the VERTEX system (source: Airbus ...

Figure 4.30.

Principle of the aircraft avoidance system TCAS

Figure 4.31. Implementation of the camera system: EAGLE Project (source...

Figure 4.32.

Coordinate system

Figure 4.33. Angular positions of the device and definition of the traj...

Figure 4.34.

Schematization of interactions for landing assistance

Guide

Cover Page

Table of Contents

Title Page

Copyright Page

Foreword

Preface

Introduction

Begin Reading

References

Index

Other titles from iSTE in Systems and Industrial Engineering – Robotics

Wiley End User License Agreement

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Autonomous Vehicles

Aerospace and Automotive Applications

Tomasz Krysinski

François Malburet

First published 2026 in Great Britain and the United States by ISTE Ltd and John Wiley & Sons, Inc.

Apart from any fair dealing for the purposes of research or private study, or criticism or review, as permitted under the Copyright, Designs and Patents Act 1988, this publication may only be reproduced, stored or transmitted, in any form or by any means, with the prior permission in writing of the publishers, or in the case of reprographic reproduction in accordance with the terms and licenses issued by the CLA. Enquiries concerning reproduction outside these terms should be sent to the publishers at the undermentioned address:

ISTE Ltd 27-37 St George’s Road London SW19 4EU UKwww.iste.co.uk

John Wiley & Sons, Inc.111 River StreetHoboken, NJ 07030USAwww.wiley.com

© ISTE Ltd 2026The rights of Tomasz Krysinski and François Malburet to be identified as the authors of this work have been asserted by them in accordance with the Copyright, Designs and Patents Act 1988.

Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s), contributor(s) or editor(s) and do not necessarily reflect the views of ISTE Group.

Library of Congress Control Number: 2025949404

British Library Cataloguing-in-Publication DataA CIP record for this book is available from the British LibraryISBN 978-1-83669-030-6

The manufacturer’s authorized representative according to the EU General Product Safety Regulation is Wiley-VCH GmbH, Boschstr. 12, 69469 Weinheim, Germany, e-mail: Product_[email protected].

Foreword

Currently, the aeronautical and automotive industries are focused on developing environmentally friendly means of transport and autonomous mobility solutions, without a pilot or driver.

These two industries have been constantly evolving since the modern aviation and modern automobile era. These developments are reflected in the technical improvement of products, the evolution of services or better control of less energy-intensive industrial processes.

Some radical or disruptive technological advances can transform the industrial world and society very quickly within a short period of time, and are characterized as technological revolutions. These advances create new markets or new services.

The invention of the commercial airplane is an example of the first radical revolution in aeronautics.

In 1896, Lord Kelvin reportedly wrote, “heavier-than-air flying machines are impossible”, when he was asked to join the Aero Club. In December 1903, the Wright brothers made the first flight of a powered and controlled aircraft, becoming the first to fly a “heavier-than-air” system.

After a period of improved aircraft performance, where flights were intended for adventurers or individuals who considered the activity a game, it was the first commercial flight that triggered the first revolution in the aviation industry. In 1914, the American entrepreneur P.E. Fansler opened the first regular airline in Florida, between St. Petersburg and Tampa, charging a ticket to the sole passenger of his seaplane. This is the first example where technology found its market in aeronautics.

The car industry experienced its first revolution when Henry Ford developed a simple, robust, inexpensive and mass-produced automobile. This was made possible by the introduction of an assembly line work, which then made it possible to produce 4,000 Ford Model Ts per day.

The Ford Model T was successful because it was accessible to everyone and had a strong reputation as a solid and reliable car. It was able to implement innovative technologies such as the use of vanadium steel for the chassis or gearbox, simple and effective leaf spring suspensions, or an original semi-automatic transmission with two forward gears and a reverse gear controlled by three pedals and a lever, the accelerator being a lever.

Later, due to the two world wars, aviation underwent significant development for military purposes. Nevertheless, a number of entrepreneurs created companies for new commercial operations: first passenger lines or mail transport.

Thus, in France, Latécoère founded the Société des Lignes Latécoère in 1919 for a postal service to Senegal, via Spain and Morocco. Louis Charles Breguet founded the Compagnie des Messageries Aériens. In 1919, the oldest airline in the world, KLM, was also created, which is still in existence. The first aeronautical industrial revolution thus launched commercial civil aviation.

A second revolution in aeronautics corresponds to the transition to modern aviation characterized by the development of turboprop and then jet airliners, replacing post-war aircraft models equipped with piston engines. The first jet airliner, which entered service in 1952, can be attributed to De Havilland. Technological revolution in the field of engines, structural design and flight controls significantly improved flight safety, which allowed aviation to become a means of mass transport.

Similarly, for helicopters, the first aircraft powered by a 260 horsepower Turbomeca “Artouste” gas turbine was on April 18, 1951. In 1957, Sikorsky tested its first turbine helicopter. This would become the standard for helicopter engines. This revolution, introducing the turbine to helicopters, was a very significant gap in the payload capacity of rotary wings.

During the same period, the automobile industry underwent similar transformations concerning safety through the development of passive or active technologies such as anti-lock braking systems (ABS), driver and passenger safety devices such as airbags, or advanced driver assistance systems (ADAS).

This second aeronautical revolution saw the development of aircraft manufacturers such as Boeing (1916), Sud-Aviation in France (1957), the Marcel Dassault aircraft company (1945), as well as numerous airlines such as KLM created in 1919, Air France in 1933 and American Airlines in 1930, which understood the need to develop different commercial civil lines. Thus, there was a significant increase in the number of flights and the quality of the service offered.

The third technological revolution is often associated with the introduction of new electronic and computer technologies. The first onboard electronic systems date back to the 1950s for automobiles, but it was in the 1970s that the first real onboard computer appeared in production cars (in 1978, in the Cadillac “Seville” model). This was made possible thanks to the use of integrated circuits and the development of microprocessors. The first computers on aircraft were mainly used for navigation; the use of computers for monitoring aircraft mechanisms and engines was introduced later.

In 1984, the Airbus A320 became the first commercial aircraft with fully digital controls. Boeing, more recently, introduced fly-by-wire controls, starting with the 777. Today, every aspect of an airplane, helicopter or car is controlled by a computer system.

The fourth transportation revolution is linked to the development of an environmentally friendly and autonomous vehicle. The first part was addressed in the book, Énergie et motorisation automobile et aéronautique (Energy and Motorization of Automotive and Aeronautics) by Tomasz Krysinski and François Malburet. The authors offered a detailed comparison of the energy and technical challenges in the automotive and aeronautics transport sector.

The second part was proposed by authors Tomasz Krysinski and François Malburet in their second book. They presented the recent development of autonomous vehicles as well as their impacts on ecological, economic and societal aspects. This new revolution is made possible by the development of new sensor technologies, computer capabilities and the arrival of artificial intelligence.

This is the beginning of the story.

Bruno EVENCEO Airbus Helicopters

Preface

The aeronautics and automobile industries are embarking on a historic revolution in their vehicles thanks to the arrival of new converging technologies in the field of vision sensors (LiDAR and camera), the explosion in the capabilities of computers – particularly in the field of large-scale data processing – and complex algorithm systems, machine learning and the arrival of artificial intelligence (AI).

These converging technologies make it possible to have increasingly autonomous and connected rolling and flying vehicles by offering driving or piloting aids to move toward autonomous driving or flight, without a driver or pilot, and having onboard communication systems that allow communication with the environment, making the vehicle safer.

In this book, the authors analyze the arrival of these technologies from different aspects: environmental, societal and economic. They draw up an initial assessment and propose their perspectives for the future of autonomous transport.

In aeronautics, there are already some applications of autonomous passenger flights operating in limited areas or with limited functions, such as autonomous landing. These are prototypes in development. Fully autonomous flight still requires many technological breakthroughs; there is still a long way to go.

For the automotive sector, advanced driver assistance systems (ADAS) are widely used in series production. Some countries, such as China and the United States, have regulated and authorized the testing of fully autonomous vehicles on roads in real-life conditions. Since September 2022, cars that have these features can drive autonomously in the presence of a driver in certain specific driving situations on European roads: during phases on the highway, in a parking lot or even in the middle of traffic jams. It is too early to envisage large-scale fully autonomous vehicles on the roads in the short term.

In this context and based on their professional experience and culture, the authors decided to write this book on autonomous vehicles in application to flying or rolling vehicles, making the link between science and technology in an industrial context.

This book is intended for engineering students, those in mechanics disciplines, young engineers joining companies in the automobile or aeronautics sector, and people wishing to have a more comprehensive vision of the proposed topic.

A large number of books have been written on the subject of autonomous vehicles [CAO 22; FOS 17; IBA 12; NON 10; YU 18], each in its own specific industrial field. The authors wanted to write a book that would put the automotive and aeronautics industries into perspective, whose needs converge on certain points, and diverge on others. Although the technical solutions at times may be similar, they can also be very different. The authors’ objective was to present all of the technological building blocks involved in the development of autonomous vehicles, such as the description of the vehicle architecture including the control chain, the driving or piloting functionalities, the sensor technology and the data processing.

This book was written with the aim of transmitting technical culture and know-how in order to support future generations in the development of future solutions. It is the result of a long collaboration between industry and university.

Introduction to autonomy: the Introduction aims to demonstrate and justify the benefits of developing autonomous driving for road and air vehicles. To do this, the authors focus on the three fundamental issues related to the deployment of autonomy: safety, economic and societal benefits, and environmental consequences. The first section provides an overview of road and air transport safety by presenting reports on accidents and their causes in recent years. The second section is a reflection on the economic and societal aspects, highlighting the impact of vehicle development on our lifestyles as well as the proposal of new services. The economic opportunities for the automotive and aeronautical industries as well as for users are discussed. Its acceptance and the ethical and legal aspects are also addressed. Finally, the third section addresses the environmental impact of autonomous vehicles.

Chapter 1, Vehicle Architecture: this chapter summarizes the evolution of the architecture of land and air vehicles. After recalling the levels used by official bodies to classify vehicle autonomy, it is proposed first to describe the historical evolution of the functionalities of automobiles and aircraft through a progressive introduction of innovative technologies. Then, the architecture of the vehicle and its control chain is discussed, describing and comparing the technologies used and highlighting their safety and reliability. Emphasis is placed on the link between the complexity of the control chain and the difficulty of developing vehicle autonomy.

Chapter 2, Features and Autonomy: the aim of this chapter is to present the driving assistance or piloting features that have been introduced, most of which are essential in the development of autonomous vehicles. By distinguishing between land and air vehicles, simple or comfort control features are initially covered: anti-skid, brake assistance, trajectory following or autopilot assistance. Secondly, the more complex functions related to a particular phase of use are described: parking assistance, assistance during taxi, takeoff or landing. Finally, the complex functionalities related to traffic and safety are discussed, involving interactions between vehicles or external elements such as obstacles.

Chapter 3, Sensors and Technologies: this chapter aims to provide an overview of sensor technologies and their potential developments. The first section presents proprioceptive sensors that allow the state of a vehicle to be measured, such as the attitude of a vehicle using inertial measurements or the positioning of the vehicle using the GPS system. The second section describes exteroceptive sensors or external state sensors that allow the detection of the environment external to the land or air vehicle, such as cameras, LiDARs or radars.

Chapter 4, Data Mining and Fusion: vehicle autonomy requires the use of a set of measurements and data. First, the chapter aims to introduce and justify the concept of data fusion and then to describe the different computer processes or algorithms that make information reliable by aggregating data from various sources. The second half of the chapter describes the techniques and methods associated with detection and tracking of moving objects (DTMO) such as sign and pedestrian detection for cars, or cable or pylon detection for aerial vehicles. Vision enhancement devices for airplanes or helicopters are described. The last section of the chapter focuses on simultaneous localization and mapping (SLAM). This describes the use of this type of approach for landing automation through the Airbus Helicopters “EAGLE” project.

The authors would like to thank:

Airbus Helicopters for having authorized them to use, for the purposes of this publication, the knowledge, experience and know-how developed by its employees.

The Airbus Helicopters Research team, who provided support to certain studies carried out, and in particular:

Olivier Honnorat, innovation manager at Airbus Helicopters;

Delphine Allehaux, head of research programs in France;

Johannes Plaum, head of research programs in Germany;

Rainer Heger, head of international cooperation and research activities;

Romain Nevers, active order project manager;

Marc Salesse, executive expert in Flight Control;

Nicolas Diamani, technical director of the VERTEX project, which opened the doors to autonomous helicopter flight.

Ali Yatsou and Rémy Girard, who developed the first obstacle detection system based on LiDAR currently undergoing certification, and for their careful proofreading and relevant advice during the writing of this book.

The management of Arts et Métiers and its development subsidiary, AMVALOR, for their collaboration.

Teachers and students from the Aix-en-Provence Arts et Métiers campus who were able to participate in some of these studies.

These autonomous flight technologies, in addition to innovations and simulations, require in-flight development. We would particularly like to thank Alain Delavet, Carl Ockuer and Setareh Taheri, test flight engineers at Airbus Helicopters, as well as Hervé Jammayrac and Samuel Chartier, test pilots at Airbus Helicopters.

November 2025