Autonomous and Connected Vehicles E-Book

Dominique Paret

• Herausgeber: John Wiley & Sons
• Kategorie: Wissenschaft und neue Technologien
• Sprache: Englisch

Seitenzahl: 707

Veröffentlichungsjahr: 2022

Beschreibung

AUTONOMOUS AND CONNECTED VEHICLES Discover the latest developments in autonomous vehicles and what the future holds for this exciting technology In Autonomous and Connected Vehicles, networking experts Dominique Paret and Hassina Rebaine deliver a robust exploration of the major technological changes taking place in the field, and describe the different levels of autonomy possible with current technologies and the legal and regulatory contexts in which new autonomous vehicles will circulate. The book also includes discussions of the sensors, including infrared, ultrasound, cameras, lidar, and radar, used by modern autonomous vehicles. Readers will enjoy the intuitive descriptions of Advanced Driver Assistance Systems (ADAS), network architectures (CAN-FD, FlexRay, and Backbone Ethernet), and software that power current and future autonomous vehicles. The authors also discuss how ADAS can be fused with data flowing over newer and faster network architectures and artificial intelligence to create greater levels of autonomy. The book also includes: * A thorough introduction to the buzz and hype surrounding autonomous and connected vehicles, including a brief history of the autonomous vehicle * Comprehensive explorations of common issues affecting autonomous and connected vehicles, including regulatory guidelines, legislation, relevant norms and standards, and insurance issues * Practical discussions of autonomous vehicle sensors, from DAS to ADAS and HADAS, and VA L3 to L5 * In-depth examinations of networks and architecture, including discussions of data fusion, artificial intelligence, and hardware architecture in vehicles Perfect for graduate and undergraduate students in programs dealing with the intersection of wireless communication technologies and vehicles, Autonomous and Connected Vehicles is also a must-read reference for industry professionals and researchers seeking a one-stop reference for the latest developments in vehicle communications technology.

Leseprobe

Autonomous and Connected Vehicles

Network Architectures from Legacy Networks to Automotive Ethernet

Dominique Paret and Hassina Rebaine

Translated by

Benjamin A. Engel

This edition first published 2022

© 2022 John Wiley & Sons Ltd

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The right of Dominique Paret and Hassina Rebaine to be identified as the authors of this work has been asserted in accordance with law.

Originally published in France as: Véhicules autonomes et connectés. Technologies, architectures et réseaux : du multiplex à l’Ethernet By

Dominique PARET & Hassina REBAINE © Dunod 2019, Malakoff

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Library of Congress Cataloging-in-Publication Data

Names: Paret, Dominique, author. | Rebaine, Hassina, author. | Engel, Benjamin A., translator.Title: Autonomous and connected vehicles : network architectures from legacy networks to automotive ethernet / Dominique Paret and Hassina Rebaine; translated by Benjamin A. Engel. Other titles: Véhicules autonomes et connectés. English Description: Hoboken, NJ : Wiley, 2022. | Translation of: Véhicules autonomes et connectés : techniques, technologies, architectures et réseaux : du multiplex à l’ethernet automobile | Includes bibliographical references and index. Identifiers: LCCN 2021033078 (print) | LCCN 2021033079 (ebook) | ISBN 9781119816126 (hardback) | ISBN 9781119816317 (pdf) | ISBN 9781119816133 (epub) | ISBN 9781119816140 (ebook) Subjects: LCSH: Automated vehicles. | Driver assistance systems. | Intelligent transportation systems. | Local area networks (Computer networks) Classification: LCC TL152.8 .P3713 2022 (print) | LCC TL152.8 (ebook) | DDC 629.2--dc23 LC record available at https://lccn.loc.gov/2021033078LC ebook record available at https://lccn.loc.gov/2021033079

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Contents

Cover

Title page

Copyright

Foreword

Acknowledgments

About the Authors

Preface

Introduction

1 The Buzz about Autonomous and Connected Vehicles

2 Aspects Relating to Autonomous and Connected Vehicles

3 DAS, ADAS, HADAS, and AVs – L3, L4, L5!

4 Networks and Architecture

5 Ethernet and Automobiles

6 Simulations, Applications, and Software Architectures for Automobiles

Index

End User License Agreement

List of Illustrations

Chapter 1

Figure 1.1 Example of links and connections in a connected vehicle.

Figure 1.2 Example of functions that help make a vehicle autonomous.

Figure 1.3 Other examples.

Figure 1.4 NHTSA vehicle autonomy scale

Figure 1.5 Levels of vehicle autonomy according to OICA-SAE.

Figure 1.6 Levels of vehicle autonomy according to OICA-SAE.

Figure 1.7 A level-0 “autonomous” car

Figure 1.8 Google Car.

Figure 1.9 Examples of level-3 vehicles: the Renault Espace (left) and Peugeot 508 First Edition (right).

Figure 1.10 A typical example of a level-5 vehicle (the NAVYA shuttle).

Figure 1.11 Concordance between OICA-SAE levels and eyes/hands/mind on and off.

Figure 1.12 Overview of levels of vehicle autonomy.

Chapter 2

Figure 2.1 Convention on Road Traffic (Vienna, 8 November 1968 – consolidated version).

Figure 2.2 Example of an autonomous COMP: As explained in Ch 1 where no...

Figure 2.3 Projected schedule for “autonomous vehicles” expertise in France.

Figure 2.4 What would the vehicle’s AI choose?

Figure 2.5 Simplified, illustrative example of a security target.

Figure 2.6 Example of the numerous attack points at which a connected vehicle is vulnerable.

Figure 2.7 Example of a smart biometric and behavioral seat (source: Faurecia).

Figure 2.8 (a) Renault Symbioz, (b) and (c) Peugeot e-Legend Concept. Source: Renault and Peugeot.66

Figure 2.9 Example of the battery in a Tesla Model S.

Figure 2.10 Example of a charging station at a highway rest stop.

Figure 2.11 Examples of equipment on the UTAC CERAM tracks...

Figure 2.12 Projected schedule for the development Projected schedule for the development

Chapter 3

Figure 3.1 Examples of “types of vision” that an autonomous vehicle must have.

Figure 3.2 Examples of “angles of view” that an autonomous vehicle must have.

Figure 3.3 Bayer color filter array.

Figure 3.4 Examples of processing to combat glare.

Figure 3.5 ON Semiconductor’s AS0140/42 CMOS imaging circuits.

Figure 3.6 NIT MC1003-PGC.

Figure 3.7 Example of Valéo’s smart camera.

Figure 3.8 Valéo’s blind spot radar.

Figure 3.9 Operational principle behind a lidar.

Figure 3.10 General diagram of a lidar system and the principle on which its measurements are based.

Figure 3.11 Example of elements in a spinning lidar (source: Velodyne).

Figure 3.12 Example of scanning by a Velodyne Lidar 101.

Figure 3.13 Standard Lidar and Puck VLS 128 models (source: Evan Ackerman/IEEE Spectrum – Velodyne Lidar).

Figure 3.14 Example of an image from a Velodyne VLS-128 lidar (source: Velodyne Lidar).

Figure 3.15 360° coverage using multiple lidars.

Figure 3.16 Parameters to be taken into account when evaluating a lidar system.

Figure 3.17 Examples of the “solid-state” lidars made by LeddarTech.

Figure 3.18 Bundles of lidar beams (source: leddartech.com).

Figure 3.19 Beam distribution in the LeddarVu lidars from Leddar Tech.

Figure 3.20 Example of a combination of lidars for an autonomous vehicle (source: Leddar Tech).

Figure 3.21 Example of a “solid-state” lidar made by Velodyne.

Figure 3.22 Example of the integration of the ibeo ScaLa lidar sensor from Valéo.

Figure 3.23 Separation of light in a prism.

Figure 3.24 Baraja’s concept of lidar using fiber-optical connections.

Figure 3.25 Example of an image captured by a lidar on the roof of a Google Car.

Figure 3.26 Comparison of performances (source: Denso International).

Figure 3.27 Another comparison of performances (source: Denso International).

Figure 3.28 Characteristics of different sensors.

Figure 3.29 Comparison of performances of the different systems (source: INSA Rouen)....

Figure 3.30 All solutions that can be chosen for an autonomous vehicle.

Figure 3.31 Examples of physical placements of the different sensors in a vehicle.

Figure 3.32 Earliest implementations of sensors in experimental vehicles....

Figure 3.33 Examples of esthetically pleasing ways of integrating sensors.

Figure 3.34 The hidden part of the iceberg of electronics managing the sensors...

Figure 3.35 2018, a demonstrator vehicle kitted out by Valéo.

Figure 3.36 TESLA 3S with “autopilot”.

Figure 3.37 ADAS with cameras and radars for driving assistance systems.

Figure 3.38 Blind spot monitor.

Figure 3.39 Aquaplaning detection ADAS (source: Continental).

Figure 3.40 Electronic-tire information system (source: Continental).

Figure 3.41 Parking assistance ADAS.

Figure 3.42 All solutions that can be chosen for an autonomous vehicle.

Figure 3.43 Summary of datarates for different sensors

Figure 3.44 Examples of physical placements of the different sensors in a vehicle.

Figure 3.45 Earliest implementations of sensors in experimental vehicles....

Figure 3.46 Examples of esthetically pleasing ways of integrating sensors.

Figure 3.47 The hidden part of the iceberg of electronics managing the sensors...

Figure 3.48 2018, a demonstrator vehicle kitted out by Valéo

Figure 3.49 TESLA 3S with “autopilot”.

Figure 3.50 ADAS with cameras and radars for driving assistance systems.

Figure 3.51 Blind spot monitor.

Figure 3.52 Aquaplaning detection ADAS (

source

: Continental).

Figure 3.53 Electronic-tire information system (

source

: Continental).

Figure 3.54 Parking assistance ADAS.

Chapter 4

Figure 4.1 Snapshot of an example of communication network architecture.

Figure 4.2 Symbioz: Renault’s concept car.

Figure 4.3 Example of V2X communications around a connected vehicle.

Figure 4.4 Example of V2X and P2X communication (source: 5GAA).

Figure 4.5 Specific example of V2V communications.

Figure 4.6 The two modes of operation of C-V2X communications.

Figure 4.7 Technical requirements relating to 5G-NR-V2X.

Figure 4.8 Examples of possible applications using 5G NR-based V2X.

Figure 4.9 Overview of how to fuse data from numerous sources.

Figure 4.10 Example: block diagram of the S32V234 from NXP.

Figure 4.11 Example: block diagram of the TEF 810X from NXP.

Figure 4.12 Example: block diagram of the S32R27 from NXP.

Figure 4.13 Complete overview of the envisaged solution.

Figure 4.14 Example of the sequence of steps in data fusion.

Figure 4.15 Example of the visual output from data fusion.

Figure 4.16 NVIDIA DRIVE Orin™ SoC (system-on-a-chip),...

Figure 4.17 Example of the Tesla/Samsung automobile AI unit.

Figure 4.18 Photo of one of the two main integrated circuits of the AI.

Figure 4.19 Photos of the heat dissipators needed for the integrated circuits.

Figure 4.20 Example of all the cables needed for a vehicle to work.

Figure 4.21 Example of how the cables are laid out in a vehicle.

Figure 4.22 Bus topology.

Figure 4.23 Ring topology.

Figure 4.24 Star topology.

Figure 4.25 Point-to-point switched star topology.

Figure 4.26 Overall topology of a vehicle from around 2010.

Figure 4.27 Overall topology of a vehicle from around 2015.

Figure 4.28 A heterogeneous network, as formerly existed.

Figure 4.29 Generic example of Ethernet-based network architecture.

Figure 4.30 Concrete example of Ethernet-based network architecture.

Figure 4.31 Evolution of the content of the different layers in the OSI model between 2010 and 2020.

Figure 4.32 Evolution of the content of the application layers between 2010 and 2020 (Source: Bosch).

Figure 4.33 Relative positions of the different communication protocols used in the automobile industry.

Figure 4.34 Composition of a SENT message.

Figure 4.35 Sequence of one to six 4-bit nibbles of data.

Figure 4.36 Examples of SENT communications with a 13-bit data frame.

Figure 4.37 Grouping of nibbles conveying pressure and temperature values.

Figure 4.38 Physical layer in SENT.

Figure 4.39 Payload/bus occupation in commonplace applications.

Figure 4.40 General layout of a CAN FD frame.

Figure 4.41 The seven fields in a CAN FD frame.

Figure 4.42 Comparison of SOF fields.

Figure 4.43 Comparison of arbitration fields.

Figure 4.44 Definition of a sample point.

Figure 4.45 Data field.

Figure 4.46 Comparisons of the position of the sample point between the two datarates.

Figure 4.47 Comparison of CAN and CAN FD200.

Figure 4.48 CRC field.

Figure 4.49 CRC delimiter bit.

Figure 4.50 Examples of chronograms for CAN FD frames.

Figure 4.51 Bit deformation.

Figure 4.52 Concrete examples of bit deformation.

Figure 4.53 Position of radiation in relation to the mask (example TJA 1044).

Figure 4.54 Problems of nodes awakening due to the passing of CAN FD frames.

Figure 4.55 No problems of awakening due to the passage of CAN FD frames.

Figure 4.56 Example of a circuit implementing multiple types of security – TJA115x from NXP.

Figure 4.57 LLC frame format as specified in CiA 610-.

Figure 4.58 CAN XL MAC frame fields.

Figure 4.59 Example of CAN XL COMP: This is a new fig

Figure 4.60 CRC field, ACK field, and EOF field.

Figure 4.61 Signal symmetry and the nominal sample point.

Figure 4.62 ADS and DAS.

Figure 4.63 CAN SIC and SIC XL Line driver – TJA146x from NXP.

Figure 4.64 Examples with Classic CAN and CAN SIC TJA1146.

Figure 4.65 Bridging the gap between CAN FD and Ethernet.

Figure 4.66 Convergences in IVN standards by application.

Figure 4.67 General structure of the FlexRay communication cycle.

Figure 4.68 Static and dynamic segments, arranged as COMP: This was 4.65 in art File

Figure 4.69 Example of division of time slots between different applications.

Figure 4.70 Daisy chain topology.

Figure 4.71 MOST communication frame format COMP: This was 4.70 in Art file

Figure 4.72 Physical layer of LVDS in point-to-point COMP: This was 4.72 in Art file

Figure 4.73 CAN SIC and SIC XL Line driver – TJA146x from NXP.

Figure 4.74 Examples with Classic CAN and CAN SIC TJA1146.

Figure 4.75 Possible protocol/line driver combinations.

Figure 4.76 Bridging the gap between CAN FD and Ethernet.

Figure 4.77 Convergences in IVN standards by application.

Figure 4.78 Application fields for CAN, CAN FD, FlexRay, CAN XL, and Ethernet.

Figure 4.79 Conclusions on transmission speed at 10 Mbit/s in the automotive field.

Figure 4.80 General structure of the FlexRay communication cycle.

Figure 4.81 Static and dynamic segments, arranged as chosen by the designer.

Figure 4.82 Example of division of time slots between different applications.

Figure 4.83 Example of datarates of AV signals in a vehicle.

Figure 4.84 Daisy chain topology.

Figure 4.85 MOST communication frame format .

Figure 4.86 Physical layer of LVDS in point-to-point mode.

Figure 4.87 Overview of the main specifications for the different protocols...

Chapter 5

Figure 5.1 Typical format of an Ethernet frame.

Figure 5.2 Ethernet frame header.

Figure 5.3 Ethernet frame packet.

Figure 5.4 Extended frame details.

Figure 5.5 Example of frame filling.

Figure 5.6 Comparison between switched full-duplex and shared Ethernet.

Figure 5.7 Example of application in an automobile.

Figure 5.8 Layers and sublayers in the OSI model.

Figure 5.9 Successive layers of encapsulation before a message is sent.

Figure 5.10 The multiple sublayers of the PHY layer of Ethernet.

Figure 5.11 Conventional configuration of 10 or 100BASE-TX PHY.

Figure 5.12 Conventional configuration of 1000BASE-T PHY.

Figure 5.13 Conventional topology of 1000BASE-T PHY.

Figure 5.14 Example of 3-bit symbol mapping.

Figure 5.15 Conventional configuration of 1000BASE-TX PHY.

Figure 5.16 Summary of 1 Gbit/s solutions.

Figure 5.17 Main Ethernet variants used in the industrial world.

Figure 5.18 Example of an RF spectral mask.

Figure 5.19 Overview of bitrates needed in automobile applications.

Figure 5.20 Comparison between an LVDS cable (left) and an unshielded twisted pair (right).

Figure 5.21 Diagram of a twisted pair.

Figure 5.22 Category 5 with three types of cables, having four twisted pairs.

Figure 5.23 Technical features in UTP.

Figure 5.24 Detailed documentary example of definitions of terms.

Figure 5.25 Coding technique with four distinct electrical levels.

Figure 5.26 Examples of coding (example 1 on the left and example 3 on the right;...

Figure 5.27 Examples of coding – details.

Figure 5.28 Transcoding table.

Figure 5.29 Use of MLT-3 line coding (source: Microchip).

Figure 5.30 NRZI coding.

Figure 5.31 3B to 2T look-up table.

Figure 5.32 4B to 3T look-up table.

Figure 5.33 Principle of PAM.

Figure 5.34 Variants of PAM encoding in Ethernet technology.

Figure 5.35 Principle of MLT-3 coding.

Figure 5.36 Example of MLT-3 encoding.

Figure 5.37 Examples of NRZI/MLT3 and 8B/9N/PAM-5 encoding.

Figure 5.38 Examples of signals in 100BASE-TX Ethernet (readings taken on a LeCroy oscilloscope).

Figure 5.39 Eye pattern for a 20 m unshielded twisted pair at ambient temperature ...

Figure 5.40 Examples of physical layers for 100 Mbit/s applications.

Figure 5.41 Physical layer in BroadR-Reach.

Figure 5.42 Overview of encoding in BroadR-Reach.

Figure 5.43 General shape of BroadR-Reach signal.

Figure 5.44 Overview of the BroadR-Reach solution.

Figure 5.45 Example of a complete BroadR-Reach channel.

Figure 5.46 Details of how the BroadR-Reach path works.

Figure 5.47 Differences between 100Base-T and BroadR-Reach.

Figure 5.48 Physical layer 100BASE-T1 (source: OPEN Alliance).

Figure 5.49 Physical layer of 1 Gbit/s Ethernet.

Figure 5.50 Examples of applications implemented by VW and Marvell.

Figure 5.51 Summary of 1 Gbit/s Ethernet solutions for automobiles.

Figure 5.52 IEEE to BroadR-Reach migration.

Figure 5.53 Main differences between the 100 Mbit/s and 1000 Mbit/s Ethernet variants.

Figure 5.54 Field of use of 10 Mbit/s Ethernet.

Figure 5.55 Summary of Ethernet standards used in automobiles.

Figure 5.56 Overview of the BCM89810 transceiver.

Figure 5.57 1 Gbit/s Ethernet secure switch – Marvell, 88Q5050.

Figure 5.58 IEEE 100BASE-T1 Ethernet transceivers – NXP, TJA110x.

Figure 5.59 Five-port Ethernet switch compatible with IEEE 802.3 – NXP, SJA1105.

Figure 5.60 Example of applications.

Figure 5.61 The 3-bit PRIO fields in the header tag of an 802.1Q VLAN frame.

Figure 5.62 Example of a scheduler in IEEE 802.1Qbv.

Figure 5.63 Problems due to late sending of frames.

Figure 5.64 Implementation of guard bands.

Figure 5.65 Example of frame pre-emption.

Figure 5.66 Possible fulfillment of layers 1 to 7 of the OSI model with TSN standards.

Figure 5.67 List of main standards for real-time and deterministic Ethernet, divided by subject.

Figure 5.68 List of standards.

Chapter 6

Figure 6.1 Example of a simulation image.

Figure 6.2 Implementation of the data acquisition structure.

Figure 6.3 Example of a BrickPC.

Figure 6.4 CANape – an example of a data acquisition tool.

Figure 6.5 Example of calibration.

Figure 6.6 Example of an interface (VX1000).

Figure 6.7 Data-logging hardware.

Figure 6.8 Data logging system.

Figure 6.9 Use of a high-datarate video interface.

Figure 6.10 Installation and recording of ECUs.

Figure 6.11 Synchronization of recordings.

Figure 6.12 Data acquisition module.

Figure 6.13 Overview of the whole data storage and transport system.

Figure 6.14 From point-to-point to multiplexed networks.

Figure 6.15 Architecture between 2010 and 2015.

Figure 6.16 ECU gateway approach.

Figure 6.17 Cluster gateway approach.

Figure 6.18 Central gateway architecture.

Figure 6.19 Software architecture.

Figure 6.20 Examples of frames in the FlexRay protocol.

Figure 6.21 Backbone architecture.

Figure 6.22 The AUTOSAR standard.

Figure 6.23 Signal mapping.

Figure 6.24 Encapsulation of PDUs.

Figure 6.25 PDU frame.

Figure 6.26 Signal routing mode.

Figure 6.27 Static PDU mapping.

Figure 6.28 L-PDUs and I-PDUs.

Figure 6.29 PDU header.

Figure 6.30 Container PDU and PDU gateway.

Figure 6.31 PDU transmission triggers.

Figure 6.32 Receipt of useful information.

Figure 6.33 Emerging applications.

Figure 6.34 Position of Ethernet applications in the near COMP: Is 36 in Art File

Figure 6.35 Casting modes.

Figure 6.36 Reduction of data stream for a receiver COMP: Is 38 in Art File and add arrow

Figure 6.37 Static architecture “before”.

Figure 6.38 Dynamic architecture “after”.

Figure 6.39 “Backbone” architecture.

Figure 6.40 “Backbone” architecture.

Figure 6.41 Evolution of AUTOSAR for Ethernet.

Figure 6.42 Adaptation of the OSI model to the needs of modern automobiles.

Figure 6.43 Adaptation from socket orientation to PDU COMP: New fig not in Art File

Figure 6.44 Socket adaptor.

Figure 6.45 XCP.

Figure 6.46 XCP on Ethernet.

Figure 6.47 Various modes of measurement COMP: Is 6.46 in Art File

Figure 6.48 ASAM database – A2L.

Figure 6.49 XCP on CAN frame.

Figure 6.50 DoIP gateway.

Figure 6.51 Logical addresses in DoIP.

Figure 6.52 DoIP on Ethernet.

Figure 6.53 Process of identification in DoIP.

Figure 6.54 Activation of DoIP gateway.

Figure 6.55 DoIP frame.

Figure 6.56 Loading and encapsulation of the DoIP message.

Figure 6.57 Examples of AVB networks.

Figure 6.58 Position of AVB/TSN in the OSI model.

Figure 6.59 The earliest version of an AVB node.

Figure 6.60 Exchange between a “talker” and a “listener”,...

Figure 6.61 Clock offset in relation to the grandmaster.

Figure 6.62 Sound and video synchronization.

Figure 6.63 Checking resource availability and stream reservation.

Figure 6.64 Scheduling of feeds with differing levels of priority.

Figure 6.65 FQTSS and category-based scheduling of streams.

Figure 6.66 Format of a VLAN frame.

Figure 6.67 Detailed view of a VLAN frame.

Figure 6.68 Header of AVTP packet.

Figure 6.69 SOME/IP over Ethernet.

Figure 6.70 Synchronous and asynchronous service exchanges.

Figure 6.71 AUTOSAR PDU and PDU header.

Figure 6.72 The SOME/IP IP header.

Figure 6.73 SOME/IP frame serialization.

Figure 6.74 Detailed view of serialization.

Figure 6.75 Messages between the client/server and the group.

Figure 6.76 Multiple options for deployment of a service.

Figure 6.77 Phases of operation of the service discovery protocol.

Figure 6.78 Example of a PDU in SOME IP SD.

Figure 6.79 IGMP on Ethernet.

Figure 6.80 Multicast IP and MAC addresses.

Figure 6.81 AUTOSAR: adaptive platform (AP) and classic platform (CP).

Figure 6.82 Middleware: standard service-management platform.

Figure 6.83 The two fundamental parts of SOA: the execution layer and the connected layer.

Figure 6.84 V-shaped cycle.

Figure 6.85 Example of VECTOR’s platform.

Figure 6.86 Initial architecture of VECTOR’s CANoe.

Figure 6.87 IL of protocols.

Figure 6.88 Protocol-dependent architecture.

Figure 6.89 Protocol-independent architecture.

Figure 6.90 Individual TCP/IP stack.

Figure 6.91 Simulation of a missing Ethernet node.

Figure 6.92 Configuration and transmission of IP packets.

Figure 6.93 Example of a script.

Figure 6.94 Middleware between the application layer and the data link layer.

Figure 6.95 Service-oriented data model.

Figure 6.96 Fundamental principle behind SOA.

Figure 6.97 Service interface and service model.

Figure 6.98 Importation of service interfaces.

Figure 6.99 CO configuration interface.

Figure 6.100 Links between COs and different network protocols.

Figure 6.101 Communication between COs depending on protocol.

Figure 6.102 Abstract transmission for virtual prototyping.

Figure 6.103 Binding between COs via SOME/IP.

Figure 6.104 Examples of other technologies.

Figure 6.105 Examples of future applications.

Figure 6.106 Example of a service-oriented HMI.

Figure 6.107 Trace window for SOME/IP.

Figure 6.108 Trace window for DoIP .

Figure 6.109 API for AVB.

Figure 6.110 Examples of simulation of AVB/TSN Talkers and Listeners.

Figure 6.111 Network communication interfaces.

Figure 6.112 Configurable interfaces for simulation, measurement, eavesdropping, and recording.

Figure 6.113 Bypassing latency due to the tool.

Figure 6.114 The ecosystem with which a vehicle communicates.

Figure 6.115 RF communication interface.

Figure 6.116 Environment simulation solution for Car2x/V2X applications.

Figure 6.117 Example of a whole application.

Figure 6.118 ASN.1 transfer syntax, facilitating communication between two applications.

Figure 6.119 BTP packet header with protocol and payload.

Figure 6.120 Example of simulation with CANoe.

Figure 6.121 Example of simulation with CANoe.

Guide

Cover

Title page

Copyright

Table of Contents

Foreword

Acknowledgments

About the Authors

Preface

Begin Reading

Index

End User License Agreement

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Foreword

To begin with, I wish to thank Dominique Paret and Hassina Rebaine for their initiative in writing this excellent book about the technologies needed for the autonomous vehicles of the future. The technical literature on the subject is scant as yet, but we are seeing numerous new developments, almost on a daily basis.

France will have to take up a position in relation to these technologies by 2030, which represents an extraordinary opportunity, because the automotive industry is currently undergoing a period of immense and intense change. Vehicles will be (partially) autonomous, connected, electrified, shared, etc. The ways in which they are used are also evolving, and the new forms of transport are expanding the range of what is possible. In addition, users are hungry for new experiences, as a result of the shifting of their way of life and their environment.

Every day, new technologies and associated skills are emerging, to understand, develop and implement these experiences. the traditional engineering Sciences of the twentieth and early twenty-first centuries will also become human sciences, and the engineers of tomorrow will/will have to be designers, marketers, psychologists, lawyers, philosophers, etc.

The usual terminology is also evolving. Amongst other shifts, “comfort” is becoming “wellbeing;” “ergonomics” is giving way to “human–machine interface;” “onboard electronics” are being replaced by “sensors, big data, and algorithms;” the regulation is expanding to apply to personal data; and automation is becoming a matter of ethics.

The training of engineers is no exception to this rapidly changing context. There are profound changes happening in all areas: new schools, new directions, the combination of schools; school/university; the size of promotions; dual-honors courses; international collaboration; apprenticeships; project-based coursework; spin-offs; digital engineering; and new technologies. However, this is not yet enough. The industry must provide its technicians and engineers with the requisite expertise, and work with them to build the academic world, its content, its courses, internships, conferences, projects, professorships, and so on. Today, it is universally accepted that the vehicles of the future will draw heavily on the concept of artificial intelligence, but in actual fact, such AI must first be based on the expanded intelligence of the engineers who designed it.

With that in mind, this extremely thorough book addresses readers wishing to understand the complexity of autonomous vehicles (for all applications), their use in various applications (whether connected or not), and those who design these systems.

To my mind, the most special thing about this work is that it sets out the positions of the fundamental aspects of automotive engineering – functional, software and hardware aspects of the technological building blocks – describing the architectures, examining the different protocols that are used, making designers aware of the regulations and norms in force, discussing the processing of sensitive data and finally, talking about safety and end-to-end cybersecurity. Other points are highlighted in the discussion of the numerous elements in the overall design chain of secure autonomous and connected vehicles, and the technical/economic implementation of these systems in the real world.

Dominique and Hassina have, for many years, been internationally recognized experts in technologies for automobile architectures and networks, both “multiplexed” (LIN, CAN, CAN FD, FlexRay, etc.) and “point-to-point switched” (100 Mbit/s, 1 Gbit/s and multi-Gbit/s Ethernet) in relation to the protocols, physical layers, software and tool development. The highly technical nature of the topics addressed in this book attests to the caliber of their expertise.

I sincerely hope, and firmly expect, that this book will help construct the skills necessary for the development of autonomous vehicles!

Philippe Aumont

Vice-President, SIA – Société des Ingénieurs de l’Automobile

Acknowledgments

As usual, there are many people to whom thanks are due for their kindness, their willingness to listen, their remarks, and their constructive comments. They all know who they are, and to all, we say a heartfelt “Thank you!”

Now we offer thanks to a few, more specific, friends and colleagues, for lengthy informal discussions that have contributed to this book:

In the automotive and industrial worlds: Jean-Philippe Dehaene and his team (Vector France), Karim El Attachi (Stellantis – formerly PSA + Fiat), Robert Chen (Faurecia), Denis Bugnot, and Muriel Partouche (NXP);

at the SIA: Philippe Aumont.

We also wish to thank three members and friends of the panel of experts “GDPR – Associates,” co-founded by Dominique Paret and Pierre Crégo, for their continuous support:

Maître Gaëlle Kermorgant – a barrister at the Paris Bar – and Isabelle Pottier – a barrister with Alain Bensoussan-Lexis – for their valuable assistance and involvement in relation to the legalities surrounding present and future automobiles, and Personal Data;

Mr. Jean-Paul Huon, the CEO of Z#bre, and the co-author of Secured Connected Objects (which was published in both French and English by ISTE).

Finally, we warmly thank Ms. Sandra Grayson at John Wiley, for her tenacity and patience throughout this project; our long-time translator, Ben Engel, for the consistently high quality of his work; and numerous other friends who, each in their own way, have brought us good times and joy.

Dominique Paret – Hassina Rebaine

Meudon, 9 May 2021

About the Authors

The two authors of this book have, for many years, been working together on hardware and software for onboard systems, protocols, structures, and architectures of communication networks in the automotive and aeronautical fields, and all variants thereof.

Dominique Paret

Dominique Paret is an electronics engineer (who qualified at the Breguet-ESIEE school of engineering) and the holder of a Master of Advanced Studies (DEA) in physics from the UPMC, Paris VI. For many years, prior to his recent retirement, he was a technical expert and provided technical support in the fields of Contactless/RF technology (contactless chip cards, RFID, NFC, Geoloc, Zigbee, BT, BLE, UWB, UNB, IEEE 804-xxx, etc.), automobile technologies, and multiplexed networks with a major international group producing electronic components (Philips–NXP). He was also a member of and delegate to AFNOR, the ISO, BNA, and the CEN in relation to these domains. In parallel to this career, he taught at some 15 engineering schools, both in his native France and abroad.

Dominique Paret is the founder and CEO of the consultancy and technical expertise company dp-Consulting, which he ran for 12 years, and the co-founder of GDPR Associates. He has also authored over 35 technical books, published in French (by Dunod), English (ISTE – John Wiley), Spanish (Paraninfo), Korean, and Chinese.

In short, nobody’s perfect, but technology can be!

Hassina Rebaine

A general engineer in electronics who graduated from the Algiers National Polytechnic College, Hassina Rebaine holds a doctorate in electronics on VLSI CAD systems and a DEA in information processing from the INSTN, UPMC, Paris.

Specializing, initially, in the design of simulation tools at SAT (Société Anonyme des Télécommunications) for VLSI ASICs, she then shifted her focus to the design of FPGAs/ASICs written in VHDL, for Verilog (Europe Technologies).

Today, Hassina is Training Manager at Vector, with respect to solutions for automobile onboard systems. Her areas of interest include tools to validate the use of the communication protocols CAN, LIN, FlexRay, and Ethernet. She also teaches at a range of engineering schools and universities.

Preface

Having had a long career as the technical support officer in the semiconductor industry, at Philips Semiconductors/NXP, I had the good fortune to play a direct and active role in the birth, design, development, standardization committees such as the ISO, BNA, Consortium, etc., of the protocols CAN (with Bosch), LIN (with Motorola), FlexRay (with BMW and Freescale), CAN FD and CAN XL (with Bosch – CiA), and Ethernet BroadR-Reach (with BroadCom). In addition, as I have always had a passion for conveying knowledge, at the same time, I trained both professionals and students (final-year engineering students) – hundreds of people, in all – in “Embedded Systems and Networks” and “IVNs – In-Vehicle Networks.” In parallel, I have published dozens of books over my career, including several in collaboration with Hassina Rebaine, the Technical Support Officer at Vector.

Why this book?

Over recent years, we have published (with Dunod and John Wiley) numerous highly technical books on “CAN,” “FlexRay and its applications,” and “Multiplexed networks for embedded systems.” The latter book notably described the imminent advent, in the industry, of CAN FD and CAN XL, the tsunamis of future ADASs, and the underpinnings of the earliest applications of Ethernet in vehicles that are beginning to have small glimpses of pseudo-autonomy. Since then, we have trawled the market for a book of a sensible level, clear, simple, accurate, and easily accessible, regarding the foundations, the why and the how, and other factors in communication network architectures for autonomous vehicles (such networks are the very “backbone” of a vehicle). Truth to tell, we found there was a gap in the market for such a book – what we found were either overly simplistic books or highly specialized works and university theses focusing on a particular facet of the discipline. With the exception of the few articles, books, journals, etc., cited in the bibliography, the area appears to be a gaping hole. However, over a period of three years, we attended a great many generic (and expensive) high-level conferences (equally expensive), marketing symposia spanning a range of domains and subjects on autonomous vehicles, transport, etc. When we sought to really get into the nitty gritty (true hardware and software architectures, true datarates, true problems – in summary, the daily concerns of automakers, OEMs, SMEs, startups, etc.), we found a similar lack of coverage. In addition, having spent a (very) long time in the field, we realized there was a lack of technical support on the basis of their definitions and applications in the world of intelligent and/or autonomous vehicles. Finding this academic state extremely unsatisfactory, following numerous discussions with a number of colleagues and friends, we decided to once more screw up our courage to the sticking place, mining this domain, and, in the hope of filling some small part of the void, opted to write this essentially technical book designed around this specific facet of “autonomous (or nearly autonomous) vehicles,” whose release to the general public is now highly foreseeable – imminent, even.

How this book is constructed, and how to approach it

We have carefully reconstructed and reshuffled this book many times over, to ensure it is coherent and readable, and that readers can easily orientate themselves. The end result is that these pages are divided into five major parts.

Part One clearly defines the parameters of the discussion and outlines the vast subject with which we are dealing, including integral parts of the technology and aspects that are tangentially connected to it. This part offers:

A

general introduction

to the world of autonomous vehicles, including the precise definitions of the different

levels of autonomy

and connections/connectivity of an automobile, the terminology used and the likely future trends (

Chapter 1

);

A description and a detailed breakdown of the numerous aspects, contexts, constraints, and problems (regulatory, legal, normative, moral, ethical, etc.) that weigh upon the design of the autonomous vehicles expected to enter into circulation between 2022 and 2035. At first glance, these matters may seem ancillary, but must be considered in relation to the technology, whatever the autonomous vehicle project (

Chapter 2

).

Part Two is more technical. It is divided into two main parts, illustrated with numerous examples of applications. It includes:

A detailed technical review of the extremely numerous sensors that are directly or indirectly related to a vehicle’s autonomous properties (infrared, sonar, cameras, radar, lidar, inertial navigation systems, etc.) (

Chapter 3

);

A detailed technical review of many possible ADASs (Advanced Driver Assistance Systems) and, in particular, of the data fusion in these systems. We examine the integration of AI (artificial intelligence) in the system to make decisions compatible with the desired level of autonomy. The discussion touches on problems relating to mobility, comfort, and security of data transport (

Chapter 3

).

We then move on to Part Three, which is technical and technological, and relates to:

The different possible architectures (hardware and software) used for implementing the different networks in the various zones of the vehicle – power train, chassis, comfort, infotainment, ADAS, etc., – to serve the needs of autonomous and/or connected vehicles, in terms of operational safety and cybersecurity (

Chapter 4

);

The increasing power of these networks, reflecting the datarates needed for the automation functions. There is also a detailed discussion of the CAN FD, CAN XL, and FlexRay protocols.

Part Four, which is highly technical and technological, describes the possibilities of Ethernet in the industrial world, the features specific to the automobile market, and the new “backbone” structures in “switched” Ethernet networks at 100 Mbit/s, 1 Gbit/s, and several Gbit/s, peculiar to automobiles (Chapter 5).

Finally, Part Five gives a detailed description of the software and tools needed, which are becoming increasingly important during the simulation, development, testing, calibration, etc., of all the devices in the future “autonomous supercomputers on wheels” (Chapter 6).

Target audience

This book is intended for all those who are curious about this new (or nearly new) and vast domain, encapsulating multiple physical, technological, technical, industrial, and marketing aspects. Of course, it is also written for students, professionals in the discipline, and new arrivals to it.

Technical level

Readers need not have a specific level of technical knowledge in order to follow the discussion. The book is intended to be universally accessible, but, throughout, the aim is to satisfy readers’ curiosity and provide technical knowledge up to a high level fairly quickly.

Teaching style

As both of us have, for many years, been teaching and training experts in this field, the language used, and the tone, are deliberately accessible and agreeable, without compromising on precision. To provide a complete view of the field, many examples of industrial applications are presented. In addition, running through this book is an unerring desire to impart knowledge, because, to our minds, there is little point writing for oneself. For the curious and intrepid, we have included numerous summary tables, secrets, and anecdotes throughout the text. Simply put, this book is for you, for the pleasure of understanding, learning, and enjoying. We remain “Autonomously Yours!”

N.B

Of course, this book has certain points in common with our earlier publications, which are either identical or similar. That being the case, there will inevitably be a certain amount of repetition. This, we feel, is a price worth paying in order for this book to present a contiguous picture of this novel discipline. We therefore ask our faithful readers to bear with us.

To recap, Ethernet was designed in 1975, I2C in 1979, D2B (the forebear of MOST) around 1981, CAN in 1983, etc., so all of these technologies have been maturing for around 40 years. They represent the vintage in our profession!

Introduction

Warning

This book is not intended to be an encyclopedia on autonomous and/or connected vehicles. Its sole purpose is to explain the types, choices, operation, properties, and architectures of the networks that can be used in autonomous vehicles, depending on a great many external parameters. Thus, one part of the book (the earlier chapters, essentially) details these parameters, with the aim of quantifying their technical implications in concrete terms – for example, in terms of the choice of network topology, datarate, latency, level of security, performance, compliance with norms, standards and regulations, etc.

In this book, various worlds collide – mainly, the world of automobiles, its connected domains, and numerous entities in the worlds of electronics, mechanics, and communication. All of these disciplines have their own specific sets of vocabulary, their own ways of being and acting, design methods, marketing techniques, and commercial approaches, which are generally very different – and this is perfectly normal.

Often, the thinking in electronics can be viewed as linear and Cartesian, taking one step at a time in logical succession. However, in the automotive world, it becomes much more serpentine and interlinked with other factors, because everything reacts to (and influences) everything else, and often we need to view the product that the end client wants as a contiguous whole, rather than a collection of subsets.

Before we begin…

Before setting out on this long journey, let us make two specific points.

On the subject of autonomous and connected vehicles, the Internet offers hundreds of articles (some better than others), presenting some complex and marvellous theories, all sorts of varied and vast future markets, fabulous forms of encryption, etc. As we are not fond of unproductive redundancy, we have focused solely on subjects about which there are not as many articles – i.e. the down-to-earth, day-to-day of this domain, offering a concrete and technical discussion of the vast range of applications and designs. The aim, in so doing, is to guide readers, to overlook nothing, and to avoid the pitfalls that may be encountered in the process of designing and implementing secure, autonomous, and connected vehicles. It is all very well to talk about such things, giving speeches and lectures and demonstrations (as we have seen and heard many times). However, to concretely and physically realize a connected solution for commercial purposes, and to sell it in large quantities at a sensible and reasonable price, is far better. Otherwise, it would be as well to do nothing, and forego the unnecessary fuss. This book describes the procedures that must be observed to avoid the usual pitfalls in a project, and facilitate the transition from the virtual to the real and concrete world. Thus, we propose an approach based on due consideration of the technical, financial, ergonomic, etc. standards, rather than on false promises.

On this subject, in late 2018, Bernard Favre, an expert at Inria and the former Head of Research at Volvo-Renault Trucks and of the LUTB Transport and Systems industrial research program, wrote the following. “Autonomous vehicles are a highly complex technology, in which it is probably harder to bring artificial intelligence to bear than in any other application. In no other sector is the technology faced with such a diverse range of situations. At present, we are in the full throes of innovation “in the lab.” As yet, there is no real proven market …. The number of tests that automakers require in order to validate an autonomous vehicle’s performances is soaring. They include physical experiments in real conditions, and digital simulations. … Having a certain amount of experience of the disparity between what automakers’ projections and announcements say about when new technologies will be available, and when they actually become available for commercialization (for various reasons: maturity, regulations, market acceptability, cost, real performance, etc.), I fear that autonomous vehicles will be no different to what I have seen time and time again in my career”. He concludes by projection that “autonomous cars will be operating on private circuits by 2025. In relation to autonomous vehicles on public/open roads, it is likely to be 2040. …”

This is a view which we, the authors, have long shared.

This, then, is the explicit aim of this book, which should therefore remain on your coffee tables as a reference until 2035 at least – and that should be enough!

1 The Buzz about Autonomous and Connected Vehicles

This book begins with a two-part chapter, directly connected to the technical wizardry that must be implemented in vehicles in general and, by extension, in autonomous and/or connected vehicles.

By way of a general introduction, this first part offers a brief overview of the vocabulary used in the field. This will help to avoid the common confusions arising on the ground, and offer clarity about the various terms used under the umbrella of autonomous vehicles.

The second describes the vast world of vehicles, the surrounding topics, the media buzz, coverage in the ordinary and specialized press, and the concrete reality of defining, designing, manufacturing, fine-tuning and industrially producing a product, and, in particular, successfully selling it at market.

In 2021:

There are already over a billion automobiles in the world (source:

Comité des constructeurs français d’automobiles

[CCFA – French Automaker Committee]);

In 2016, in Paris, drivers spent more than 65 hours stuck in traffic jams. The situation in Moscow was worse still (91 hours) and in Los Angeles (104 hours) (source: INRIX research, 2016);

Each year, worldwide, 1.3 million people die in traffic accidents (source: WHO);

Every year, globally, 2.6 million deaths are caused by air pollution, which is partly linked to automotive traffic;

In 2030, it is projected that 2.3 million people will die as a result of a road traffic accident (source: WHO);

By 2050, according to predictions, 70% of the world population will live in urban areas (source: WHO).

In addition, the world population is continually increasing, leading to:

Increased traffic;

Congestion in city centers;

Soaring CO

2

emissions;

The upsurge in road accidents.

In the short and medium terms, all these subjects raise the question of urbi et orbi (in cities and out of them) transport in the future. In addition, in the early twenty-first century, the automotive industry is experiencing major technological changes, and as mentioned in the Foreword, in time, vehicles will come to be (partially) autonomous, connected, often electric, shared, etc. Their uses will evolve, and new forms of mobility, technologies, and skills will extend the range of possibilities.

As stated previously, this technical book is merely a single stone in the understanding of the vast edifice that is autonomous and connected vehicles. We have therefore restricted our field of study to a specific part of that edifice.

1.1 The reasons behind this book and its limitations

Autonomous and/or connected vehicles represent an enormous and highly complex subject, including a great many concepts that must be understood. Thus, we shall begin by briefly presenting the fields we have decided to cover in this book. Note that, while we have chosen to focus on the technical and technological aspects only, each of the subjects has its own accompanying philosophy and technical consequences.

1.1.1 Architectures

In a vehicle, there are a wide range of architectures, which clash, overlap, coexist, etc. We shall examine various architectures here. For example:

Functional architecture

, which governs the overall organization of all the system functions in a vehicle. Here, functional architecture is discussed only briefly;

Network architecture

, which governs the way in which protocols and communications between the functions and ECUs (computers) in the vehicle are chosen and structured. This will be the main focus of the book, as we move progressively from multiplexed network systems to automotive Ethernet architectures;

Hardware architecture

, whose purpose is to structure and define the choices of ECUs, the types of electronics, sensors, actuators, etc. We shall also discuss these in some depth, as they are directly involved in the different types of data that need to be transmitted;

Software architecture

, which controls the structure and management of the different software modules in a vehicle. At the end of the book, we shall examine the software architectures that are dedicated to networking;

Organic architecture

, which is in charge of the implementation of the different functions in the vehicle’s electrical and electronic components;

Topological architecture

, which manages the physical arrangement of the different systems and components within a vehicle. The topological architecture is of crucial importance in estimating and minimizing network lengths, which are closely connected to the achievable datarates;

Cabling architecture

, which governs the way in which the networks and cabling harnesses are physically divided and implemented in the vehicle, their performances, diameters, weight, and so on.

1.1.2 Communication networks

As we shall see, for many years, numerous types of communication network have been installed in vehicles. Each network is specifically suited to particular application typologies.

The majority of this book focuses on analyzing their quality and performance, with a view to making suitable, safe applications, carried in vehicles with high levels of autonomy and connectivity. Until recently, such networks were largely based on “multiplexed” modes of operation, and many are in the process of shifting towards modes of operation oriented around the Ethernet philosophy, tailored for use in automobiles. The main goal of this book is to guide readers through that technological transition.

1.2 Terminology

It may be unusual to begin a book with a terminology section. However, in order to discuss autonomous vehicles, it is necessary to clearly define and describe the different levels of vehicle autonomy, to overcome the many potential misunderstandings, without the generalization and obfuscation that are typical of mainstream media coverage of this subject.

1.2.1 Autonomous and/or connected vehicles

To begin with, readers must appreciate the profound distinction between “autonomous” vehicles and “connected” vehicles. These two terms represent two completely different things, and must, under no circumstances, be confused.

By definition, a (true)

autonomous

vehicle must be capable of traveling unassisted, alone, anywhere and at any time, etc., with no restrictions, without the help or even the presence of a driver.To be absolutely clear, either a vehicle is autonomous or it is not. It cannot be nearly autonomous or semi-autonomous, etc. – that makes no sense.Nevertheless, in order to rate a vehicle’s performances, we can speak of the

levels

of

autonomy

(dictionary: its “capacity to be autonomous”), taking care to clearly indicate the specific domains and references in question;

A connected vehicle is a vehicle that is linked to other systems by means of telecommunication systems, telephones, etc.;

An “autonomous” vehicle is not necessarily “connected,” or vice versa.

On the other hand, frequently, an autonomous vehicle often does need to be connected in order to carry out other functions and other tasks (for example: uploading or downloading information about the road on which the vehicle is traveling, etc.) – this is why confusion so often arises.

Autonomous vehicles

The terms “autonomous” and “autonomous vehicles” are much too broad and too imprecisely defined. Again, to prevent confusion, in this book describing the habits and customs of the automotive profession, focusing on vehicles from those of the past to those of the (perhaps distant) future, we shall use precise levels to define these types of autonomy, specified below.

Connected vehicles

It is all very well to speak of connected vehicles – but connected to what, why, and how? Figure 1.1 illustrates some of the possible links and connections. These will be discussed in greater detail in Chapter 4.

Figure 1.1 Example of links and connections in a connected vehicle.

To complete this brief general introduction, Figure 1.2 illustrates a vehicle solution whose functions facilitate a certain degree of autonomy, and which also has a number of connections.

Figure 1.2 Example of functions that help make a vehicle autonomous.

1.2.2 Terms and vocabulary relating to autonomous driving

The changes taking place in the automotive sector have made their way into the lexicon – there is a range of terminology dedicated to autonomous vehicles.

Terms and definitions

This vocabulary includes terms such as “ADASs” (advanced driver assistance systems), “driverless taxi,” “participatory geo-navigation,” etc. Consider a few other examples:

Pay-how-you-drive (PHYD) insurance

: “a vehicle insurance contract whose premiums are based on the driver’s conduct at the wheel, and the way in which the vehicle is used.” Note that driver behavior and vehicle usage are assessed using data transmitted to the insurance company by onboard sensors;

Dashboard camera

,

dashcam

,

dash camera

,

scene recorder

: “an onboard camera that records the scene in front of the vehicle.” Note that often, only the last few minutes of a recording are actually kept in the memory. These recordings may, for example, be used to document the cirucmstances of an accident;

Autonomous driving or

automated driving

: “a method of automated driving of a vehicle, which does not require input from its users; and, by extension, a system that facilitates this kind of driving;”

Traffic jam assist

,

traffic jam chauffeur

,

traffic jam pilot

: “a system that allows a vehicle to move independently in traffic jams.” The simplest forms of traffic jam autonomous driving systems merely follow the vehicle in front in the same lane (which does represent a certain degree of autonomy); the most complex are also able to change lanes.

Driver alert

,

driver alert system

,

driver monitoring

,

driver monitoring system

: “an onboard system that uses sensors and analyzes the driver’s behavior to detect any reduction in their alertness, and warn them about it.” The most advanced form is an alertness monitoring system:

The sensors used may be cameras, which analyze the driver’s head and eye movements. There are also systems that analyze the rotation of the steering wheel to assess driver alertness;

Attention assist

is a registered trademark, so the term should not be used in any other context.

For information, Figure 1.3 offers a list of equivalent terms:

Figure 1.3 Other examples.

Terms

Driverless cab, autonomous taxi, driverless taxi

Mirroring, screen mirroring

Let us now look at the levels of autonomy.

Autonomy levels

In the automobile industry, the gradual trend towards autonomous driving follows a scaled technological progression, defined by a classification, which itself is established on the basis of multiple autonomy levels. Level 0 corresponds to a 100% manual vehicle, and the highest level (4 or 5, depending on the standards used) corresponds to a fully autonomous vehicle (restricted to specific use cases), which has no need of a driver.

Use cases

Note

At the time of writing (2021), these different autonomy levels correspond only to applications in specific environments and use cases.

The three defined use cases and their specific features are as follows:

For private vehicles:

In a traffic jam, without changing lane;

On the highway, without changing lane;

Autonomous parking.

For industrial vehicles:

Speed regulation by infrastructure;

Platooning;

Garbage trucks;

Agricultural sprayers.

For public transport:

Free service on a private site;

Shuttle bus services on a sheltered site.

Note 

All of these use cases are highly restrictive. Nowhere in these three use cases is “open” circulation of autonomous vehicles mentioned.

We shall now look at the classification of autonomy levels.

NHTSA classification (United States)

In the United States, the Department of Transportation and the National Highway Traffic Safety Administration (NHTSA) have created a five-level vehicle autonomy scale (Figure 1.4).

Figure 1.4  NHTSA vehicle autonomy scale.

NHTSA classification

Autonomy level

Functionality

Level 4

Fully autonomous driving

Level 3

Limited autonomous driving

Level 2

Automation of combined functions

Level 1

Automation of certain functions

Level 0

No automation

Let us briefly recap the definitions of these levels.

Level 0 – no automation

“The driver has total control, at all times, of the vehicle’s main functions (engine, accelerator, steering, brakes).”

Level 1 – automation of certain functions

“The automation systems, which apply only to certain vehicle functions, merely assist the driver, who retains overall control.”