# Automated Vehicles as a Game Changer for Sustainable Mobility

Guy Fournier, Adrian Boos, Dimitri Konstantas, Danielle Attias

► To cite this version:

Guy Fournier, Adrian Boos, Dimitri Konstantas, Danielle Attias (Dir.). Automated Vehicles as a Game Changer for Sustainable Mobility. Springer Nature Switzerland, pp.XXVIII, 509, 2024, Contributions to Management Science, 978-3-031-61680-8. 10.1007/978-3-031-61681-5 hal-04651664

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Distributed under a Creative Commons Attribution 4.0 International License
Contributions to Management Science

Guy Fournier

Adrian Boos

Dimitri Konstantas

Danielle Attias *Editors*

Automated
Vehicles as a
Game Changer
for Sustainable
Mobility

Learnings and Solutions

OPEN ACCESS

<figure><img src="image_2.png" /></figure>

Springer
Contributions to Management Science
The series *Contributions to Management Science* contains research publications in all fields of business and management science. These publications are primarily monographs and multiple author works containing new research results, and also feature selected conference-based publications are also considered. The focus of the series lies in presenting the development of latest theoretical and empirical research across different viewpoints.

This book series is indexed in Scopus.
Guy Fournier • Adrian Boos • Dimitri Konstantas •
Danielle Attias
Editors

Automated Vehicles
as a Game Changer
for Sustainable Mobility

Learnings and Solutions

<figure><img src="image_3.png" /></figure>

Springer
Editors

Guy Fournier ID
Pforzheim University
Pforzheim, Germany

Adrian Boos
Pforzheim University
Pforzheim, Germany

Dimitri Konstantas
Geneva School of Economics
and Management
University of Geneva
Geneva, Switzerland

Danielle Attias
University of Paris-Saclay
Gif-sur-Yvette, France

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ISSN 1431-1941

ISSN 2197-716X (electronic)

Contributions to Management Science

ISBN 978-3-031-61680-8

ISBN 978-3-031-61681-5 (eBook)

https://doi.org/10.1007/978-3-031-61681-5

European Union Horizon 2020 research and innovation programme grant agreement 769033 - AVENUE project

© The Editor(s) (if applicable) and The Author(s) 2024. This book is an open access publication.

**Open Access** This book is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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If disposing of this product, please recycle the paper.
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Own design, Poster with more information can be found at the following link: AVENUE

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# Foreword

Dear Reader,

In discussions on how we can steer the future direction of our planet in the right way, mobility soon takes a central spot. Today, mobility generates approximately one third of all urban emissions, an impact that will only grow as millions more people move to cities, increasing passenger demand by 79% by 2050.

The desired outcome of this discussion is clear: we need to encourage a shift from the private car towards more sustainable, higher occupancy modes such as public transport. To make this shift, the latter must provide a convenient, reliable, and inclusive alternative.

At UITP (the International Association of Public Transport), we believe that automation can be a key solution here. Automated mobility, autonomous vehicles, self-driving shuttles: in their many forms, they can hugely enrich the mobility mix, providing a kind of flexibility that has the power to fill gaps in terms of times (late at night), location (rural areas), and people's needs.

But, taking an innovative spin on a famous quote, we can strongly argue that alike happiness, automation is best when shared. Only when deployed as shared vehicles that are integrated into an effective public transport network, automated vehicles (AVs) can be a real solution to create healthier and more competitive and sustainable cities.

In order to be a credible alternative to (automated) car ownership, the different sustainable modes need to be coordinated, planned, and delivered in an integrated way not only from a physical perspective (coordinated network planning, stations, urban planning, and algorithmic optimisation of automated fleets) but also from an information perspective whereby services are integrated into a passenger-centric MaaS system. Here, the question of data also remains important: there is a need for a huge collection of data, as well as the regulatory framework to utilise it safely and cooperatively.

The question is thus not (anymore) the technology, but how to involve all stakeholders in the best way and how to create business models and services that work and make passengers want to use AVs. Public transport authorities and operators are
experts in organising urban mobility solutions: we should allow them to lead the transition and take the lead in the coordination of tomorrow's mobility.

Research & innovation projects like AVENUE are key to address such questions and to be able to maximise the benefits of automation for our society. UITP is proud to be involved in various EU projects on CCAM, including as Coordinator in SHOW (SHared automation Operating models for Worldwide adoption). Also in ULTIMO, which will build on the learnings of SHOW and AVENUE, UITP is proud to work together with CCAM colleagues to look at AV deployment that considers all elements in a cross-sector business environment and truly wants to unlock the integration of AVs into cities.

This AVENUE book shows the results of a unique collaboration and provides invaluable knowledge on how to ensure automated mobility is deployed as real solution for some of today's greatest challenges. We are confident it will inspire many.

Head of 3rd Party funded projects and the CCAM
Colleagues, UITP,
the International Association of Public Transport
Brussels, Belgium

Umberto Guida
# Foreword

Dear Reader

Digitalisation is having a far-reaching impact on us and our lives—also in the way we get around. We cannot say conclusively today what this will look like in 50 or even 100 years’ time. What is certain is that even in a hundred years’ time, a society’s prosperity, welfare, health, education, and culture will still be directly linked to the wide availability of sustainable, safe, and reliable transport. Automated vehicles are likely to play a major role in that respect. They can make more efficient use of existing roads, improve traffic flow, and significantly increase road safety—an opportunity that we, as specialist authorities and road traffic agencies, must not pass up if we want to make our roads fit for the future.

That is why the Federal Roads Office (FEDRO)<fnref n="1" /> has made smart mobility and automated and connected transport a focal point of its official activities. In 2015, an automated vehicle travelled on public roads in Switzerland for the first time as part of a pilot scheme. In the meantime, 16 pilot schemes have been conducted throughout Switzerland. This also included the operation of three on-demand shuttle buses in Geneva. As part of this pilot project, authorised and supervised by FEDRO, an automated bus operated by the Geneva transport authority (transports publics genevois, tpg) carried passengers on the semi-public roads of a hospital campus. The routes were not predetermined, but were orientated to the needs of the customers. Similar pilot applications were run in three other cities (Lyon, Copenhagen, and Luxembourg).

These four pilot applications were part of the major EU-funded AVENUE project, in which FEDRO was represented on the Advisory Board. In FEDRO’s view, the project has been positive. AVENUE has shown how teams from different cultures across Europe can work together to successfully find solutions in a highly complex and innovative field such as automated mobility. Mutual exchange, a willingness to learn, and cooperation between the private and public sectors are essential. FEDRO’s participation on the advisory board contributed to this

<footnote n="1">¹Switzerland’s federal authority responsible for road infrastructure and private road transport.</footnote>
constructive cooperation. At the same time, it has gained valuable experience in the field of automated transport. This meant that both sides were able to benefit from FEDRO's involvement in the major AVENUE project.

Today's pilot applications will form an integral part of tomorrow's transport solutions. By 2050, around a third of all vehicles on the roads could be (partially) automated. As one of our studies also shows, driverless shuttles, buses, and trains could cover up to 70% of our transport needs. Traditional motorised private and public transport would lose their dominance. The boundaries between these forms of transport will shift towards 'public individual transport' or 'individual public transport' services. These forms of transport will be characterised by their efficiency: automated vehicles can be on the move continuously, making one journey after another. In future, it will be almost inconceivable for vehicles to stand stationary for more than 90% of the time as they do today.

Switzerland has taken an important step towards smarter mobility: The revision of the Road Traffic Act and the Ordinance on Automated Transport demonstrate a clear commitment to automated transport on the part of the Swiss parliament and government. The potential of conditional and highly automated vehicles (SAE automation levels 3 and 4) will be deployed on Swiss roads as early as 2025.

In addition to the political process, it will be important that we as a society prepare ourselves for the 'automation' megatrend. As specialised authorities, we can ensure that the new technologies are supported in terms of legislation and infrastructure, as the potential in terms of efficiency, costs, safety, and availability is simply too promising to ignore. But there must be broad social acceptance. Projects like AVENUE can play an important part by literally taking users on a journey and incorporating their experiences into improving the technology.

I am confident that this approach will be successful. And I look forward to seeing the upcoming changes in mobility lead us towards greater safety, improved compatibility, and availability at lower costs.

Director of the Federal Roads Office (FEDRO)
Ittigen, Switzerland

Jürg Röthlisberger

Federal Roads Office (FEDRO) & Advisory
Board Member AVENUE
Ittigen, Switzerland

Benno Nager
# Foreword

## The Five Ts: Transparency, Trust, Teamwork, Try, and Transform

### We Need a Climate for Change

People and the ecosystems we life in, in this Digital Age, have great capabilities to improve and sustain the quality of life for all, if we interact and team up. As we face and urgently need to deal with many societal challenges, we need a climate for change.

Societal challenges and related Sustainable Development Goals are a challenging problem set. There is no one solution. There is no one group with the answer. There is no one technical fixture. This is all about boots on the ground, roll up our sleeves, start walking, and work together. This is not about the talk. This is all about walking the talk and achieving outcomes. Transformation and other continuous change is a team sport.

Mobility is one of our main societal challenges locally and globally. Whether it is about getting persons of any demography and in any phase of life, safely, securely, timely, comfortably and affordably while preserving human integrity, or otherwise. Mobility is an integral part of almost every aspect in life. It intertwines with many other societal challenges. So addressing the mobility challenges will also support, co-address, and improve those other societal challenges, whether local, regional, national, or global.

However, thinking that we can address this big societal challenge and other intertwined challenges by doing more of the same and with that we will get a different outcome is a low probability success strategy. We have got to get out of our comfort zones. We have to be willing to try new, alternative approaches to provide these essential services to the public, while improving and sustaining the quality of life and planet.
Horizon 2020 Project AVENUE

With Horizon 2020 Project AVENUE, an essential and great start has been made to do
exactly that: trying new alternatives. For once, these included (A) finding the optimal
balance between EV and AV in order to provide useful, affordable, viable, and sus-
tainable multi- and inter-modal services to the public—in a people-centric manner,
(B) pivoting from fixed stop to on demand—but still—public transportation, while
(C) getting the right stakeholders onboard, comfortable, confident, and courageous
enough to actively support the mission, and while (D) aiming to create multi-layered
yet integrated data sharing ecosystems in this Digital Age for multiple stakeholders,
including the traveller, the public transport operator, the platform provider and its sup-
ply chain ecosystems, as well as first responders, relevant authorities, other stakehold-
ers, and last but not least: citizens, businesses, and society at large.

The latter—data, information, and knowledge sharing—is essential to unlock data,
create transparency, and spur innovation in an accountable manner, and to support the
AVENUE mission including to build, achieve, and sustain the appropriate levels of
trust that are necessary to be truly able to trigger the envisioned symbiotic transforma-
tion of future-proof mobility, green, digital, and societal transition. Step by step.

*Europe Fit for the Digital Decade*

I want Europe to strive for more by grasping the opportunities from the digital age within safe and ethical boundaries. When advocating its mission called ‘A Europe Fit for the Digital Age’, the Commission well-phrased the importance of the symbiosis between opportunities, challenges, risks, and ethics. Obviously, that should generally be nothing new to anyone. However, connecting, inter-connecting and even hyper-connecting, and creating new physical, cyber-physical and digital ecosystems and other combinatoric possibilities and innovations to empower people and organisations, public and private, and guide Europe’s green and digital transformations requires each of us to get out of our comfort zone, rethink, team up, and most of all, to act and try.

In line with the EU Fit for the Digital Age mission, together with the member
states the Commission has developed and started to deliver on the so-called Path to
the Digital Decade 2030. It consists of various strategies, common objectives and
targets, where mobility is one of the main essential components thereof to support
the necessary transformations. Said targets are to be met by 2030.

The Five Ts: Transparency, Trust, Teamwork, Try,
and Transform

In the above paragraphs you have already been able to identify the Five Ts. One
needs to be willing to meet the right levels of transparency, as transparency leads to
trust. Trust can be seen as the equation of consistency through time, where
teamwork and the willingness to try, fail, pivot, and try again will be the strategy with the highest probability of success.

Project AVENUE has basically taken these Five Ts in, also by demonstrating that the challenges at hand can be converted with our combined creativity and determination to transform. Meanwhile, obviously many new challenges, big and small have arisen during the project. This, as one will only see and is able to identify and address the true challenges if one starts walking, teams up, tries, and pivots while focusing on transformative outcomes—not on efforts. It is good to see and know that this project has already been succeeded by new collaborations, and namely the Horizon Europe project ULTIMO.

This publication gives you a rich amount and variety of valuable insights and oversights, lessons learned and good practices for you to consider, further, improve, and optimise. It is a great example of the willingness to share and provide transparency.

And with that it also makes available a valuable amount of trust principles and components that can help you, your organisation, and your stakeholders to join forces to addressing the societal challenge of mobility, and the many intertwined challenges—and opportunities. On the latter, I am certain that if one is able to convert those challenges into such opportunities, any person in any part of the mobility market in any place on this planet can benefit from it.

I welcome you to enjoy reading this publication, use its valuable content, and join an ever-increasing community that is determined to foster the climate for change and focus on making the difference, for the short, mid, and long term, whether local, regional, global, or otherwise.

Director Arthur's Legal, Strategies & Systems
& Advisory Board Member AVENUE
Amsterdam, The Netherlands

Arthur van der Wees
Acknowledgements

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This project has received funding from the
European Union's Horizon 2020 research and
innovation program under grant agreement No. 769033.

The research work developed in this book received funding from the European Union's Horizon 2020 research and innovation program under grant agreement No. 769033, for the AVENUE project (Autonomous Vehicle to Evolve to a New Urban Experience).

We would like to express our sincere thanks to all the authors and related institutions who contributed to this book. Participating in this adventure required considerable effort, commitment, and flexibility, as many of our authors generously shared their knowledge and insights at all hours of the day and throughout the week. Their willingness to stay involved and contribute even after the project was completed is something to be praised and we are very grateful for. We are especially thankful for their enthusiasm to explore and illuminate the potential of automated vehicles for the common good. Your contributions have been invaluable for the team and we greatly appreciate the time, expertise and dedication you have brought to this project. Thank you for being an integral part of this journey and helping to create a thoughtful and informative discourse on such an important topic. Your input for the book will surely be a starting point for further meaningful discussions.

Acknowledgment for support in artwork, layout, and typesetting:

Nicole van den Boom, Antonia Bucksch, Charly Beye, Sally Krüger, and Niklas Liebhauser

**Disclaimer** Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or CINEA. Neither the European Union nor the granting authority can be held responsible for them.
# About This Book

This book deals with the possibilities of a new, more sustainable form of integrated mobility on the basis of the Horizon 2020 Project AVENUE-Autonomous Vehicles to Evolve to a New Urban Experience. AVENUE designed and carried out full-scale demonstrations of urban transport automation by deploying fleets of automated minibuses in low to medium demand areas of four European demonstrator cities (Geneva, Lyon, Copenhagen, and Luxembourg) and two replicator cities (Esch-sur-Alzette in Luxembourg and Sion in Switzerland). The AVENUE vision for future public transport in urban and suburban areas is that automated vehicles will ensure safe, rapid, economic, sustainable, and personalised transport of passengers. AVENUE introduces disruptive public transportation paradigms based on on-demand, door-to-door services, aiming to set up a new model of public transportation, by revisiting the offered public transportation services, and aiming to suppress prescheduled fixed bus itineraries. In Part I, the book explains how automated vehicles were implemented on the different sites and which progress were achieved on the vehicles, the vehicle safety, in-vehicle services, cybersecurity and on the requirements for Persons with Reduced Mobility. The economic, environmental, and social impact of the implementation of automated vehicles for companies, citizens, and cities is assessed in Part II. One aim of this book is finally to demonstrate that automated vehicles integrated in a MaaS (Mobility-as-a-Service)/ITS (Intelligent Transport System) can become a game changer towards sustainable mobility and a fair share of the created values between the stakeholders. The transport system could become more efficient, flexible, resilient, and citizen centric avoiding thus a coercive transformation policy.
# Contents

<table><tr><td>1</td><td>Introduction</td><td>1</td></tr><tr><td></td><td></td><td>Guy Fournier, Adrian Boos, Dimitri Konstantas, and Danielle Attias</td></tr><tr><td>Part I</td><td colspan="2">The AVENUE Project: Implementing Automated Minibuses for “Door-to-Door” and “On-Demand” Passenger Transportation in Geneva, Lyon, Luxembourg and Copenhagen</td></tr><tr><td>2</td><td>AVENUE Site Demonstrators: Geneva, Lyon, Luxembourg, and Copenhagen</td><td>15</td></tr><tr><td></td><td></td><td>Jeroen A. Beukers, Quentin Zuttre, Georges Hilbert, Daniel Kaeding, Albert Hoffmann, Christian Zinckernagel, Nanna May Felhaus, Nicole van den Boom, Adrian Boos, and Dimitri Konstantas</td></tr><tr><td>3</td><td>Automated Minibuses: State of the Art and Improvements Through AVENUE</td><td>71</td></tr><tr><td></td><td></td><td>Pierre Chehwan</td></tr><tr><td>4</td><td>Safety, Security and Service Quality for Automated Minibuses: State of the Art, Technical Requirements and Data Privacy in Case of Incident</td><td>113</td></tr><tr><td></td><td></td><td>Philippe Chrétien, Antonios Lalas, Konstantinos Votis, and Dimitrios Tzovaras</td></tr><tr><td>5</td><td>In-Vehicle Services to Improve the User Experience and Security when Traveling with Automated Minibuses</td><td>125</td></tr><tr><td></td><td></td><td>Dimitrios Tsiktsiris, Anastasios Vafeiadis, Antonios Lalas, Minas Dasygenis, Konstantinos Votis, Dimitrios Tzovaras, Christian Zinckernagel, and Kevin Salvi</td></tr></table>
<table><tr><td>6</td><td>Cybersecurity and Data Privacy: Stakeholders' Stand on Regulations and Standards</td><td>151</td></tr><tr><td></td><td>Niels A. Nijdam, Meriem Benyahya, and Anastasija Collen</td><td></td></tr><tr><td>7</td><td>Technical Cybersecurity Implementation on Automated Minibuses with Security Information and Event Management (SIEM)</td><td>169</td></tr><tr><td></td><td>Athanasios Papadakis, Antonios Lalas, Sofia Petridou, Konstantinos Votis, and Dimitrios Tzovaras</td><td></td></tr><tr><td>8</td><td>Persons with Reduced Mobility (PRM) Specific Requirements for Passenger Transportation Services</td><td>183</td></tr><tr><td></td><td>Linda Mathé, Markus Dubielzig, and Matthias Lindemann</td><td></td></tr><tr><td>9</td><td>Stakeholder Analysis and AVENUE Strategies</td><td>201</td></tr><tr><td></td><td>Dorien Duffner-Korbee, Eliane Horschutz Nemoto, Ines Jaroudi, Nicole van den Boom, Tobias Viere, Gabriele Naderer, and Guy Fournier</td><td></td></tr></table>

## Part II Impact Assessment of AVENUE

<table><tr><td>10</td><td>Research Approach: Introduction to SUMP and AVENUE Methodology</td><td>237</td></tr><tr><td></td><td>Eliane Horschutz Nemoto, Nicole van den Boom, Michael Thalhofer, and Guy Fournier</td><td></td></tr><tr><td>11</td><td>Technical Impact Assessment: Obstacles and Developments of Automated Minibuses for Public Transport</td><td>247</td></tr><tr><td></td><td>Charly Beye, Christian Zinckernagel, and Guy Fournier</td><td></td></tr><tr><td>12</td><td>Economic Impact Assessment: Local Service Costs of Automated Vehicles for Public Transport</td><td>261</td></tr><tr><td></td><td>Fabio Antonialli, Sylvie Mira-Bonnardel, and Julie Bulteau</td><td></td></tr><tr><td>13</td><td>Environmental Impact Assessment: Automated Minibuses for Public Transport</td><td>279</td></tr><tr><td></td><td>Tobias Viere, Adrian Boos, Nicole van den Boom, Meriem Benyahya, Maher Ben Moussa, and Guy Fournier</td><td></td></tr><tr><td>14</td><td>Environmental Impact Assessment: Externalities of Automated Electric Vehicles for Public Transport</td><td>315</td></tr><tr><td></td><td>Ines Jaroudi, Adrian Boos, Tobias Viere, and Guy Fournier</td><td></td></tr><tr><td>15</td><td>Social Impact Assessment: Changing Mobility Behaviour by Understanding Customer Needs and Attitudes</td><td>361</td></tr><tr><td></td><td>Dorien Duffner-Korbee, Gabriele Naderer, Niklas Liebhauser, and Guy Fournier</td><td></td></tr><tr><td>16</td><td>Governance Impact Assessment, Regulatory Recommendations and Challenges</td><td>393</td></tr><tr><td></td><td>Lionel Binz</td><td></td></tr></table>
<table><tr><td>17 Sustainability Assessment of the Integration of Automated Minibuses in Urban Mobility Systems: Learnings from the AVENUE Project</td><td>413</td></tr><tr><td colspan="2">Eliane Horschutz Nemoto, Ines Jaroudi, Dorien Duffner-Korbee, Tobias Viere, Gabriele Naderer, Adrian Boos, Nicole van den Boom, and Guy Fournier</td></tr></table>

Part III Future Vision of AVENUE

<table><tr><td>18 System Innovation in Passenger Transportation with Automated Minibuses in ITS: The Citizen-Centric Approach of AVENUE</td><td>429</td></tr><tr><td colspan="2">Guy Fournier, Michael Thalhofer, Johannes Klarmann, Philippe Chrétien, Dorien Duffner-Korbee, Adrian Boos, Ines Jaroudi, Eliane Horschutz Nemoto, Lionel Binz, Gabriele Naderer, Dimitri Konstantas, and Tobias Viere</td></tr></table>

<table><tr><td>19 Transition Planning Towards a Sustainable Urban Mobility Ecosystem</td><td>475</td></tr><tr><td colspan="2">Michael Thalhofer, Adrian Boos, Eliane Horschutz Nemoto, Dorien Duffner-Korbee, Markus Dubielzig, Christian Zinckernagel, Inès Jaroudi, Dimitri Konstantas, and Guy Fournier</td></tr></table>

<table><tr><td>20 Conclusion</td><td>507</td></tr><tr><td colspan="2">Guy Fournier and Dimitri Konstantas</td></tr></table>
Contributors

**Fabio Antoniali** PPA Business School, Paris, France
École Centrale Lyon, Écully, France

**Danielle Attias** University of Paris-Saclay, Gif-sur-Yvette, France

**Meriem Benyahya** Centre Universitaire d'Informatique, Geneva School of Eco-
nomics and Management, University of Geneva, Carouge, Switzerland

**Jeroen A. Beukers** tpg, Geneva, Switzerland

**Charly Beye** Pforzheim University, Pforzheim, Germany
CentraleSupélec, Université Paris-Saclay, Gif-sur-Yvette, France

**Lionel Binz** Cantonal Transports Office in Geneva (Etat de Genève), Petit-Lancy, Switzerland

**Nicole van den Boom** Pforzheim University, Pforzheim, Germany
CentraleSupélec, LGI, Gif-sur-Yvette, France

**Adrian Boos** Pforzheim University, Pforzheim, Germany

**Julie Bulteau** Université de Versailles Saint-Quentin-en-Yvelines, Versailles, France

**Pierre Chehwan** NAVYA Group, Courbevoie, France
beti - Experts Mobilité Automatisée, Saint-Donat-sur-l'Herbasse, France

**Philippe Chrétien** Centre Européen d'Etudes de Sécurité et d'Analyse des Ris-
ques, CEESAR, Nanterre, France

**Anastasija Collen** Centre Universitaire d'Informatique, Geneva School of Eco-
nomics and Management, University of Geneva, Carouge, Switzerland

**Minas Dasygenis** Department of Electrical and Computer Engineering, University of Western Macedonia, Kozani, Greece

**Markus Dubielzig** Siemens Technology, Accessibility Competence Center, Pader-
born, Germany
**Dorien Duffner-Korbee** Fraunhofer ISI, Karlsruhe, Germany
Pforzheim University, Pforzheim, Germany

**Nanna May Felhaus** Holo, København N, Denmark

**Guy Fournier** Pforzheim University, Pforzheim, Germany
CentraleSupélec, Université Paris-Saclay, Gif-sur-Yvette, France

**Georges Hilbert** SALES-LENTZ (S.L.A. S.A.), Bascharage, Luxembourg

**Albert Hoffmann** SALES-LENTZ (S.L.A. S.A.), Bascharage, Luxembourg

**Ines Jaroudi** Fraunhofer ISI, Karlsruhe, Germany
Pforzheim University, Pforzheim, Germany
CentraleSupélec, LGI, Gif-sur-Yvette, France

**Daniel Kaeding** SALES-LENTZ (S.L.A. S.A.), Bascharage, Luxembourg

**Johannes Klarmann** Pforzheim University, Pforzheim, Germany

**Dimitri Konstantas** Geneva School of Economics and Management, University of Geneva, Geneva, Switzerland

**Antonios Lalas** Centre for Research and Technology Hellas, Information Technologies Institute, Thessaloniki, Greece

**Niklas Liebhauser** Pforzheim University, Pforzheim, Germany

**Matthias Lindemann** Siemens Technology, Accessibility Competence Center, Paderborn, Germany

**Linda Mathé** Siemens Technology, User Experience Design, Munich, Germany

**Sylvie Mira-Bonnardel** École Centrale Lyon, Écully, France

**Maher Ben Moussa** University of Geneva, Carouge, Switzerland

**Gabriele Naderer** Pforzheim University, Pforzheim, Germany

**Eliane Horschutz Nemoto** Pforzheim University, Pforzheim, Germany
CentraleSupélec, LGI, Gif-sur-Yvette, France
ICLEI Europe, Freiburg im Breisgau, Germany

**Niels A. Nijdam** Centre Universitaire d'Informatique, Geneva School of Economics and Management, University of Geneva, Carouge, Switzerland

**Athanasios Papadakis** Centre for Research and Technology Hellas, Information Technologies Institute, Thessaloniki, Greece
Department of Applied Informatics, University of Macedonia, Thessaloniki, Greece

**Sofia Petridou** Department of Applied Informatics, University of Macedonia, Thessaloniki, Greece
**Kevin Salvi** Mobile Thinking, Geneva, Switzerland

**Michael Thalhofer** Software-driven Ecosystems and Market Places, Siemens Technology, Munich, Germany

**Dimitrios Tsiktsiris** Centre for Research and Technology Hellas, Information Technologies Institute, Thessaloniki, Greece

Department of Electrical and Computer Engineering, University of Western Macedonia, Kozani, Greece

**Dimitrios Tzovaras** Centre for Research and Technology Hellas, Information Technologies Institute, Thessaloniki, Greece

**Anastasios Vafeiadis** Centre for Research and Technology Hellas, Information Technologies Institute, Thessaloniki, Greece

**Tobias Viere** Pforzheim University, Pforzheim, Germany

**Konstantinos Votis** Centre for Research and Technology Hellas, Information Technologies Institute, Thessaloniki, Greece

**Christian Zinckernagel** Holo, København N, Denmark

**Quentin Zuttre** Keolis, Lyon, France
Acronyms

<table><tr><td>ADS</td><td>Automated Driving Systems</td></tr><tr><td>AI</td><td>Artificial Intelligence</td></tr><tr><td>API</td><td>Application Protocol Interface</td></tr><tr><td>AV</td><td>Automated Vehicle</td></tr><tr><td>BMM</td><td>Business Modelling Manager</td></tr><tr><td>CAV</td><td>Connected and Automated Vehicles</td></tr><tr><td>DMP</td><td>Data Management Plan</td></tr><tr><td>DTU test track</td><td>Technical University of Denmark test track</td></tr><tr><td>EC</td><td>European Commission</td></tr><tr><td>ECSEL</td><td>Electronic Components and Systems for European Leadership</td></tr><tr><td>EU</td><td>European Union</td></tr><tr><td>EUCAD</td><td>European Conference on Connected and Automated Driving</td></tr><tr><td>F2F</td><td>Face-to-face meeting</td></tr><tr><td>GDPR</td><td>General Data Protection Regulation</td></tr><tr><td>GNSS</td><td>Global Navigation Satellite System</td></tr><tr><td>HARA</td><td>Hazard Analysis and Risk Assessment</td></tr><tr><td>IPR</td><td>Intellectual Property Rights</td></tr><tr><td>IT</td><td>Information Technology</td></tr><tr><td>ITU</td><td>International Telecommunications Union</td></tr><tr><td>LaaS</td><td>Logistics as a Service</td></tr><tr><td>LIDAR</td><td>Light Detection and Ranging</td></tr><tr><td>MaaS</td><td>Mobility as a Service</td></tr><tr><td>ODD</td><td>Operational Domain Design</td></tr><tr><td>OEDR</td><td>Object and Event Detection and Response</td></tr><tr><td>PRM</td><td>Persons with Reduced Mobility</td></tr><tr><td>PTA</td><td>Public Transport Authority</td></tr><tr><td>PTO</td><td>Public Transportation Operator</td></tr><tr><td>PTS</td><td>Public Transportation Services</td></tr><tr><td>SAE Level</td><td>Society of Automotive Engineers Level (Vehicle Autonomy Level)</td></tr><tr><td>SDK</td><td>Software Development Kit</td></tr><tr><td>SLA</td><td>Sales Lentz Autocars</td></tr></table>
<table><tr><td>SoA</td><td>State of the Art</td></tr><tr><td>SOTIF</td><td>Safety Of The Intended Functionality</td></tr><tr><td>SWOT</td><td>Strengths, Weaknesses, Opportunities, and Threats.</td></tr><tr><td>TPG</td><td>Transports Publics Genevois</td></tr><tr><td>UITP</td><td>Union Internationale des Transports Publics (International Transport Union)</td></tr><tr><td>V2I</td><td>Vehicle-to-Infrastructure communication</td></tr></table>
# Chapter 1
## Introduction

<figure><img src="image_8.png" /></figure>

Check for
updates

Guy Fournier, Adrian Boos, Dimitri Konstantas, and Danielle Attias

**Abstract** The AVENUE project, part of European Horizon 2020, investigated the integration of automated vehicles (AVs) into public transport across Europe, focusing on improving mobility through innovative, sustainable solutions. From 2018 to 2022, AVENUE research demonstrated the potential of automated minibuses for safe, efficient and environmentally friendly transport in urban environments. This introduction explains the project's approach to deploy AVs for the first time globally in cities, the impact assessment and the potential for the future. Small summaries of the content of the book parts introduce to the book to give support and guidance to the reader.

### 1.1 Automated Vehicles (AVs) for a New Mobility

Since Adam Smith (1776) and David Ricardo (1817), we know that mobility of people and goods is the basis for the functioning and growth of economies based on the division of labour. In modern economies, in particular, goods can be produced in one place and made available for consumption in another. People can further move long distances to work, consume goods from all over the world and participate in education and social life outside their immediate environment. Mobility is therefore a key factor for growth and prosperity.

G. Fournier (✉)
Pforzheim University, Pforzheim, Germany

CentraleSupélec, Université Paris-Saclay, Gif-sur-Yvette, France
e-mail: guy.fournier@hs-pforzheim.de

A. Boos
Pforzheim University, Pforzheim, Germany

D. Konstantas
Geneva School of Economics and Management, University of Geneva, Geneva, Switzerland

D. Attias
University of Paris-Saclay, Gif-sur-Yvette, France
However, mobility is also criticised for the environmental and social costs it
can cause. There are various strategies to deal with this. One option is to accept
and continue the current paradigm, accepting the associated costs. Another
option is to be more sober and reduce mobility (sufficiency strategy), but this
strategy is not very popular and would as a consequence reduce and focus activ-
ity, purchasing power and the production on a local level to lower environmental
impacts (Matusiewicz, 2024). However, with the new digital and automated
technologies, it seems possible to avoid these negative scenarios and (a) keep or
even increase current prosperity levels while (b) better meeting people's mobil-
ity needs at an affordable price and (c) additionally addressing environmen-
tal issues.

The division of labour can indeed be improved and even automatised through
digital technologies. Transaction and information costs can be significantly reduced
in this way (Rifkin, 2015). As a consequence, the control/management of sophisti-
cated technical systems, such as automated vehicles, can be streamlined and simpli-
fied. At a higher organisational level, such as a city, the coordination among
stakeholders within the entire mobility/transport ecosystems can further be enhanced
and even partly automatised as well. Collaboration could thus optimise the use of
material and energy,<fnref n="1" /> reduce waste and improve the mobility services. Meeting the
mobility needs of citizens by aggregating services and combining them into a seam-
less and comfortable journey could accordingly be better fulfilled. A transformation
towards sustainable mobility could so be the choice of the citizen and be fulfilled
without constraints. Beyond that, new opportunities to improve the efficiency and
flexibility of the transport system arise from the integration of data generated/made
available by the mobility/transport ecosystem, combined with the capabilities of
artificial intelligence (AI). As a consequence, these developments support the disap-
pearance of the traditional distinction between individual transport and the transport
services provided/offered by public (Haan et al., 2020) and/or private transport
operators. Consequently, it appears feasible to revolutionise urban mobility/transport
and enable sustainable mobility without a coercive transport policy. This book
summarises the learnings from the European Horizon 2020 project AVENUE and
would like to contribute how automated vehicles (AVs)<fnref n="2" /> could be a game changer to
realise this transformation.

<footnote n="1">¹The general systems theory is an epistemological approach to solve complex problems, distinguish information, matter (material/resources) and energy as basis of all systems. Information can be exchanged through collaboration to improve the (transport) system as a whole. In contrast to information, data can be objectified because it can be coded, stored, transformed and, above all, transported. Information is “by its very nature processual, knowledge-changing, subject-related and cannot be objectified” (Fournier, 1994; Kesic, 2024; Rifkin, 2015).</footnote>

<footnote n="2">²According to SAE Mobilus (2018, 2021), the word “autonomous” is a misnomer as applied to automated driving technology, because even the most advanced ADSs are not “self-governing”. We thus will follow in the book the recommendation of SAE Mobilus to characterise driving automation and use “automation” instead of the popular term “autonomous”.</footnote>
AVENUE was a European Horizon 2020 project spanning 4.5 years from May 2018 to October 2022. The primary objective of AVENUE was to validate the suitability and efficiency of deploying small- and medium-sized AVs into Europe's public transportation system (Konstantas, 2021). AVENUE aims were to design and carry out full-scale demonstrations of urban transport automation by deploying, for the first time worldwide, fleets of automated minibuses in low- to medium-demand areas of four European demonstrator cities: Geneva (Meyrin, Belle-Idée; Switzerland), Lyon (Parc OL; France), Copenhagen (Nordhavn, Slagelse; Denmark) and Luxembourg (Pfaffenthal, Contern; Luxembourg) and two replicator cities (Uvrier in Switzerland and Esch-sur-Alzette in Luxembourg). The AVENUE vision for future public transport in urban and suburban areas was that AVs will ensure safe, rapid, economic, sustainable and personalised transport of passengers. AVENUE introduced disruptive public transportation paradigms on the basis of on-demand, door-to-door services, aiming to set up a new model of public transportation, by revisiting the offered public transportation services, and aiming to suppress prescheduled fixed bus itineraries.

The progress and findings achieved with the AVENUE project provided evidence supporting the possible role of AVs not only in public transport but also as a possible transformative improvement for the entire transport system of a city (see part 3). The in-depth research by the AVENUE project presented in this book is structured in three parts. Part 1 describes and analyses the complexities of such projects in detail. Part 2 presented the impact assessment of the AVENUE projects where we use an interdisciplinary sustainable urban mobility plan (SUMP)-based holistic approach making a link between social, economic and environmental dimensions and also addressing technical obstacles and legal issues. Part 3 finally explores how AVs could become a game changer for urban transport systems, driving them towards a (more) sustainable transport/mobility system and also examining how this transformation can be realised effectively. The three parts of the book are briefly summarised below and then presented in more detail for each book chapter in the next section “Contents of the Individual Book Parts”.

Part 1 of the book (“AVENUE Project: Implementing Automated Minibuses for Door-to-Door and On-Demand Passenger Transportation”) examines the fundamental transformative role of AVs in public transport as a whole and in four key European cities as test sites of the AVENUE project. AVENUE demonstrated the possibilities of automating mobility/transport by deploying fleets of automated minibuses for the first time worldwide in areas with low to medium demand. This first part of the book looks in particular at the technological advances through the project and challenges of AVs, particularly automated minibuses, and how these vehicles are being integrated into public transport systems. The individual sub-chapters address safety, service quality and the impact of in-vehicle services on user experience and security. The development of in-vehicle services is particularly relevant to prepare the transition from an in-vehicle safety operator to a teleoperator, who will initially manage one and subsequently multiple vehicles from an external location. To this end, safety issues, for example, were thus addressed with artificial intelligence to substitute the services provided by the safety driver when
level 4 will be achieved. Critical aspects of cyber security, data protection and the application of advanced security solutions such as security information and event management (SIEM) are also covered. The part presents last but not least solutions to support vulnerable travellers and concludes with a stakeholder analysis highlighting the need for collaboration in the introduction of automated minibuses in public transport.

Part 2 of the book ("Impact Assessment of AVENUE") presents a multifaceted analysis of the deployment of AMs in mobility ecosystems. It uses a holistic approach to understand the relationships between technical, economic, social, environmental and legal dimensions of such projects. It begins with an introduction to the sustainable urban mobility plan (SUMP) and its integration with AVENUE, emphasising citizen-centric mobility planning. The sections then delve into various aspects of automated minibuses, including technical challenges and advancements, economic analysis focusing on service costs and externalities and the social impacts on mobility behaviour. The governance impact assessment is also explored, highlighting regulatory challenges and solutions. Lastly, a comprehensive sustainability assessment is provided, evaluating the before-mentioned dimensions of the implications of integrating automated minibuses into urban mobility systems. Overall, this section of the book demonstrates the economic, environmental and social potential of AVs for stakeholders like citizen, companies and public transport operators/authorities.

Part 3 of the book ("Future Vision of AVENUE") delves into the prospective advancements and strategies for integrating automated minibuses in intelligent transport systems (ITS). It begins with a discussion on system innovation in passenger transportation, focusing on a citizen-centric approach and a future vision 2030 for that. The section explores various pathways for integrating AVs into mobility ecosystems, emphasising the transformative role of automated minibuses in mobility-as-a-service (MaaS) systems to provide services that are similar to private cars in terms of flexibility (see above). With the use of data, AVs could in this model be further integrated into an ITS. AV would complement private (car sharing, bike sharing, ride sharing, etc.) and public transport and make the transport system as a whole more efficient and resilient. Instead of a product innovation, the entire transport system could be improved towards sustainable mobility. The emphasis is on leveraging data to enhance the efficiency, flexibility and resilience of the transport system, a concept referred to as ambidexterity, meaning that antinomic economic goals can be achieved at the same time. The final chapter addresses transition planning towards a sustainable mobility ecosystem, outlining a strategic, phased approach for this transition, especially to the proposed AM in MaaS/ITS system. However, it highlights the challenges and opportunities in creating effective, sustainable urban mobility plans.

To assist the reader, you will find a brief summary of the chapters below.
## 1.2 Contents of the Individual Book Parts

### 1.2.1 Part 1: The AVENUE Project: Implementing Automated Minibuses for “Door-to-Door” and “On-Demand” Passenger Transportation in Geneva, Lyon, Luxembourg and Copenhagen

#### Chapter 2: AVENUE Site Demonstrators: Geneva, Lyon, Luxembourg and Copenhagen

The first sections examine the transformation of public transport by AVs in Geneva, Lyon, Luxembourg and Copenhagen, within the AVENUE project. It addresses objectives, deployment (automation level, on demand, door to door), achievements, key success factors and future developments of integrating AV in public transport in the different demonstration sites. The chapter underscores the importance of real-world testing within AVENUE project case studies and aims to show how AVs can reshape twenty-first-century public transport as well as the entire mobility ecosystem.

#### Chapter 3: Automated Minibuses: State of the Art and Improvements Through AVENUE

This chapter focuses on advances in AV technology, particularly automated minibuses for public transport. It discusses the development of AV technology, detailing the contributions of NAVYA and the significant technological advances achieved through the AVENUE project. The chapter addresses the integration of AVs into public transport systems, the development of door-to-door on-demand services and the challenges of managing the entire AV ecosystem. It also documents the continuous improvements in software and hardware, the legal and regulatory challenges and NAVYA's role in shaping the AV landscape in Europe and highlights the impact of the project on future technological developments in this area.

#### Chapter 4: Safety, Security and Service Quality for Automated Minibuses: State of the Art, Technical Requirements and Data Privacy in Case of Incident

This chapter proposes the critical aspects of safety and service quality in the use of AMs. It discusses the state of the art in safety measures, the need for technical reliability and the challenges of data protection and cyber security. The chapter emphasizes the importance of maintaining high safety standards for the successful integration of automated minibuses into public transport and examines strategies to continuously improve safety and service quality, including regulatory compliance and incident management.
**Chapter 5: In-Vehicle Services to Improve the User Experience and Security when Traveling with Automated Minibuses**

This chapter deals with the development and implementation of various in-vehicle services designed to improve the user experience and safety in automated minibuses. It addresses the integration of advanced technologies such as artificial intelligence and deep learning models to address the challenges related to passenger safety and comfort. The chapter emphasises the importance of these services in the context of driverless public transport and highlights how they contribute to the overall efficiency and acceptance of AVs in the urban environment.

**Chapter 6: Cybersecurity and Data Privacy: Stakeholders' Stand on Regulations and Standards**

This chapter discusses the importance and challenges of ensuring cybersecurity and data protection in the context of connected AVs. It investigates technological and regulatory aspects through outlining the threat landscape within the AV's ecosystem and showcasing how such threats are considered within a case study where AVs are foreseen as a means of public transport. The study results demonstrate these vehicles' resilience from cyber and privacy threats. With an alignment to the core regulations and standards, this chapter also derives the main mitigation strategies and requirements to strengthen the evolving technology in automated transport.

**Chapter 7: Technical Cybersecurity Implementation on Automated Minibuses with Security Information and Event Management (SIEM)**

This chapter discusses the integration of security information and event management (SIEM) solutions in automated minibuses. It discusses the importance of SIEM in real-time monitoring and response for cybersecurity and examines its application in the context of automated minibuses. The chapter provides an analysis of different SIEM software solutions and their role in protecting against cyberthreats and highlights the critical need for advanced security measures in the automated transport sector.

**Chapter 8: Persons with Reduced Mobility (PRM): Specific Requirements for Passenger Transportation Services**

The use of fully automated vehicles in public transport has the potential to revolutionise the complete landscape of public transport. Fully automated vehicles can provide the necessary frequency even in places with a low passenger volume. In addition, these vehicles can stop even in places which are not yet integrated into the public transport network, thus better meeting the needs of passengers as public transport becomes more and more individual. The absence of a driver, however, also implies that these vehicles must provide more services than conventional ones. This chapter presents the findings on passenger services for fully
automated minibuses after 2 years of studies with passengers. These findings
were gathered based on observations, workshops, questionnaires and interviews
with (disabled) passengers, safety drivers, bus drivers, PTOs and associations of
disabled persons.

**Annex 8: AnnexMobile Apps for Blind and Low-Vision Public Transport Travellers**

This chapter focuses on mobile applications designed to help blind and visually impaired people on public transport. It lists various iOS apps, such as GoodMaps Outdoors, BlindSquare, myfinder and Seeing AI and describes their functions such as GPS navigation, obstacle detection and information provision. The chapter emphasises that these apps are complementary aids and not a replacement for conventional aids. It also emphasises the need to equip vehicles with assistive technologies to provide visually impaired users with a comprehensive public transport experience.

**Chapter 9: Stakeholder Analysis and AVENUE Strategies**

This chapter presents a comprehensive stakeholder analysis for the use of auto-
mated minibuses in public transport systems. The most significant stakeholder
groups and their expectations, needs and impacts are identified using qualitative
methods. It discusses the diverse impact different stakeholder groups have on the
advancement of automated minibuses and provides strategic recommendations for
stakeholders such as governments, public transport operators and citizen groups. It
emphasises the importance of stakeholder collaboration, collective action in updat-
ing regulatory frameworks and the integration of AM into mobility-as-a-service
(MaaS) systems.

**1.2.2 Part 2: Impact Assessment of AVENUE**

**Chapter 10: Research Approach: Introduction to SUMP and AVENUE Methodology**

The first chapter of this second part of the book outlines the concept of the sustain-
able urban mobility plan (SUMP) and its integration with the AVENUE project. It
describes SUMP as a planning paradigm that moves from motorised road planning
to people-centred urban mobility planning and how it incorporates elements such as
micromobility, AVs and mobility as a service (MaaS). The chapter describes how
the different work packages of the AVENUE project, each focusing on automated
minibuses, align with SUMP by improving public transport and integrating innova-
tive mobility solutions. It emphasises the importance of interdisciplinary approach
to address sustainable planning strategies which integrates economic environmental and social impact assessments (see chapter about sustainable assessment and the developed indicators) but also the stakeholders to formulate recommendations which satisfy citizen, the original transport operator (OEM), the public transport operator and the city, for example.

**Chapter 11: Technical Impact Assessment: Obstacles and Development of Automated Minibuses for Public Transport**

The first section begins by exploring the assessment of technical obstacles and advancements of automated minibuses in public transport, drawing upon insights collected from urban areas like Geneva, Lyon, Luxembourg and Copenhagen within the AVENUE project. This initial exploration provides valuable perspectives on the development of mobility ecosystems. Furthermore, a closer examination unfolds, focusing on specific facets of this evaluation which are critical for the seamless integration of automated minibuses into public transport. Through this study, a spectrum of challenges and progress points observed in AVENUE are described, revealing insights into regulatory compliance, safety demonstration and technological constraints. This chapter emphasises in particular the importance of creating and adopting new open standards for the interoperability of automated technologies. Such standards are central to fostering robust competition between different technological stakeholders, including vehicle manufacturers, fleet management services, V2X technology developers and others, thereby promoting a dynamic and sustainable fair ecosystem in the field of automated transport.

**Chapter 12: Economic Impact Assessment: Local Service Costs of Automated Minibuses for Public Transport**

This chapter provides a detailed economic analysis of AVs in public transport. It presents an economic assessment tool, EASI-AV, which was developed to support public policy in the introduction of innovative mobility services. The tool takes into account the total cost of mobility (TCM) and reflects a modern approach to fleet management, including automated electric mobility. Real data from the pilot sites of the AVENUE project confirm the relevance of the tool as a decision-making aid for the introduction of AVs. The focus of the chapter is on understanding the economic feasibility and impact of integrating AVs into public transport networks.

**Chapter 13: Environmental Impact Assessment: Automated Minibuses for Public Transport**

This chapter assesses the environmental impacts of integrating automated minibuses into public transport systems. It analyses the balance between energy savings offered by automated minibuses through efficient routing and vehicle operation and the increased energy demand due to their connectivity and automation features. Using life cycle assessment (LCA), the study shows that the magnitude of environmental benefits of automated minibuses depends largely on the electricity mix,
passenger occupancy (i.e. how many passengers use the vehicle at the same time) and vehicle utilisation over its lifetime.

Future use cases with renewable energy mixes, high passenger occupancies and overall vehicle utilisation highlight the full potential of automated minibuses to become a game changer towards a more environment-friendly transport system.

**Chapter 14: Economic and Environmental Impact Assessment: Externalities of Automated Vehicles for Public Transports**

This chapter analyses the externalities of deploying automated minibuses in public transportation, particularly focusing on possible reductions of external costs. It utilises scenario planning and an externalities model to assess the impact of automated minibus deployment in AVENUE cities. The chapter explores different deployment scenarios, including substituting buses and private cars with automated minibuses, and their potential negative and positive externalities. It provides a nuanced understanding of how different automated minibuses integration strategies can affect transportation systems' economic and environmental aspects.

**Chapter 15: Social Impact Assessment: Changing Mobility Behaviour by Understanding Customer Needs and Attitudes**

This chapter focuses on the social impact of the use of automated minibuses in the four AVENUE cities. It presents the results of studies on mobility needs, attitudes towards automated minibuses and user experiences in pilot and replicator cities. The results show a generally positive, open-minded attitude of citizens towards automated minibuses and a higher willingness to use automated minibus services when they are on demand, door to door and integrated into public transport systems. The chapter emphasises the influence of real-life experiences on acceptance and risk perception and highlights the potential of automated minibuses to transform urban mobility when flexibly integrated into urban transport systems. The quantitative results on user acceptance, which are presented at the end of the chapter, are especially important for the planning of future mobility ecosystems. In particular, the representative survey revealed that a significant proportion of respondents, especially car owners, are willing to switch to automated minibuses if they prove to be efficient and reliable. This shift in preferences highlights the potential impact of AVs on mobility ecosystems and car ownership trends and reflects openness to new, technologically advanced transport solutions. In particular, the representative survey of 1816 citizens in the four AVENUE cities shows that 45% of drivers are “willing” (22%) or even “very willing” (23%) to give up their car to use automated minibuses to cover the first and last mile, if this becomes possible.
**Chapter 16: Governance Impact Assessment, Regulatory Recommendations and Challenges**

This chapter examines the regulatory and governance challenges posed by AVs, focussing in particular on the changes in legislation and governance models required for AVs. It outlines different governance approaches, including global, governmen-tal, self-directed, co-operative, social, technological and financial governance. The chapter highlights the need for an integrated and collaborative approach to creating regulations, taking into account the unique characteristics of AVs and the impor-tance of harmonising laws at different levels. It discusses in detail the impact of the use of AVs on various legal and societal areas and presents legal recommendations for public authorities, emphasising the need for governance that supports societal benefits and addresses ethical, privacy and liability issues.

**Chapter 17: Sustainability Assessment of the Integration of Automated Minibuses in Urban Mobility Systems: Learnings from the AVENUE Project**

The sustainability assessment provides a comprehensive evaluation of the sustain-
ability of automated minibuses in urban mobility ecosystems based on the pilot tests
of the AVENUE project. It takes an interdisciplinary approach, integrating environ-
mental, economic and social assessments with a range of sustainability indicators.
The chapter assesses the impact of integrating AMs into urban mobility and dis-
cusses related challenges, potential benefits and strategies for their integration into
sustainable urban mobility plans. It emphasises the importance of aligning AMs
with sustainable development goals and the need for system innovation to achieve
public transport-centric mobility as a service (MaaS).

**1.2.3 Future Vision of AVENUE**

**Chapter 18: System Innovation in Passenger Transportation with Automated Minibuses in ITS: The Citizen-Centric Approach of AVENUE**

The first chapter of this third part of the book discusses the integration of automated minibuses in intelligent transport systems (ITS) with a citizen-centric approach, as part of the AVENUE project. It explores three pathways for incorporating AVs into mobility ecosystems: private AVs, robotaxis and automated minibuses in a mobility-as-a-service (MaaS) system. The chapter emphasises that automated minibuses in MaaS could be a “game changer”, enhancing public transport efficiency and flexibility and filling mobility gaps. The successful implementation of this concept hinges on open data and APIs and the potential of artificial intelligence to create a self-learning transport system. The chapter argues that this integration aligns with SUMP, aiming to meet citizens’ needs more effectively while addressing sustainability challenges.
**Chapter 19: Transition Planning Towards a Sustainable Urban Mobility Ecosystem**

The last chapter discusses the process of transitioning towards sustainable mobility, focusing on automated minibuses within MaaS/ITS. It outlines a three-phase process: analysing the status quo, defining a future vision and designing the transition from current scenarios to the envisioned future. The chapter provides a road map for this transition, encompassing critical success factors, stakeholder identification, goal setting and strategic recommendations. It emphasises the need for an integrated approach to create effective transition plans and highlights the challenges and opportunities in realising a sustainable mobility ecosystem.

**Acknowledgements** This project has received funding by the European Union's Horizon 2020 research and innovation program under grant agreement No. 769033.

**References**

Fournier, G. (1994). Informationstechnologien in Wirtschaft und Gesellschaft - Sozioökonomische Analyse einer technologischen Herausforderung. *Volkswirtschaftliche Schriften (VWS)*, 439, 1-253.

Haan, P. d., Straumann, R., Bianchetti, R., Stetter, A., Oehry, B., & Jermann, J. (2020). Verkehr der Zukunft 2060: Technologischer Wandel und seine Folgen für Mobilität und Verkehr. In *Forschungsprojekt SVI 2017/003 auf Antrag der Schweizerischen Vereinigung der Verkehrsingenieure und Verkehrsexperten (SVI)*. Bundesamt für Strassen (ASTRA). http://www.mobilityplatform.ch

Kesic, S. (2024). Universal complexity science and theory of everything: Challenges and prospects. *Systems*, 2024(12), 29. https://doi.org/10.3390/systems12010029

Konstantas, D. (2021). From demonstrator to public service: The AVENUE experience. In S. Mira-Bonnardel, F. Antonialli, & D. Attias (Eds.), *The robomobility revolution of urban public transport. Transportation research, economics and policy*. Springer. https://doi.org/10.1007/978-3-030-72976-9_5

Matusiewicz, M. (2024). Framework for physical Internet deployment in cities. *Urban, Planning and Transport Research*, 12(1), 2303341. https://www.tandfonline.com/doi/full/10.1080/21650020.2024.2303341

Rifkin, J. (2015). *Zero marginal cost society*. The rise of the collaborative commons and the end of capitalism, Palgrave Macmillan.

SAE International. (2018). Taxonomy and definitions for terms related to driving automation systems for on-road motor vehicles. Ground Vehicle Standard J3016_201806. Published June 15, 2018 by SAE International in United States. Available online at https://saemobilus.sae.org/content/J3016_201806/

SAE International. (2021). SAE Levels of Driving Automation™ Refined for Clarity and International Audience. SAE Blog, Published May 3, 2021 by SAE International in United States. Available online at https://www.sae.org/blog/sae-j3016-update
**Open Access** This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

The images or other third party material in this chapter are included in the chapter's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.

<figure><img src="image_9.png" /></figure>
Part I

# The AVENUE Project: Implementing Automated Minibuses for “Door-to-Door” and “On-Demand” Passenger Transportation in Geneva, Lyon, Luxembourg and Copenhagen
Chapter 2
# AVENUE Site Demonstrators: Geneva, Lyon, Luxembourg, and Copenhagen

<figure><img src="image_10.png" /></figure>

Check for
updates

Jeroen A. Beukers, Quentin Zuttre, Georges Hilbert, Daniel Kaeding,
Albert Hoffmann, Christian Zinckernagel, Nanna May Felhaus,
Nicole van den Boom, Adrian Boos, and Dimitri Konstantas

**Abstract** The AVENUE project, which was carried out in Geneva, Lyon, Luxembourg, and Copenhagen, demonstrates the innovative integration of automated vehicles (AVs) into urban public transport systems. This initiative investigated the use of AVs in different urban environments and achieved remarkable progress in the areas of mobility, environmental sustainability, and accessibility. Through real-world testing, the project identified key success factors such as technological integration, social acceptance, and infrastructural adaptation. Achievements include on-demand services, seamless integration into existing transport networks and the promotion of multimodal transport solutions. The experiences from the AVENUE project provide crucial insights into operational and societal aspects of AV implementation in public transport and emphasise the importance of ongoing innovation and research in the field of automated mobility for future urban transport ecosystems.

J. A. Beukers (✉)
tpg, Geneva, Switzerland
e-mail: Beukers.Jeroen@tpg.ch

Q. Zuttre
Keolis, Lyon, France

G. Hilbert · D. Kaeding · A. Hoffmann
SALES-LENTZ (S.L.A. S.A.), Bascharage, Luxembourg

C. Zinckernagel · N. M. Felhaus
Holo, København N, Denmark

N. van den Boom
Pforzheim University, Pforzheim, Germany

CentraleSupélec, LGI, Gif-sur-Yvette, France

A. Boos
Pforzheim University, Pforzheim, Germany

D. Konstantas
Geneva School of Economics and Management, University of Geneva, Geneva, Switzerland
## 2.1 Introduction

As urban populations continue to surge and our cities grapple with ever-increasing traffic congestion and environmental concerns, the quest for innovative and sustainable public transportation solutions has intensified. Among the emerging technologies at the forefront of this transformation is fully automated vehicles. These self-driving vehicles have the potential to revolutionise public transportation, offering eco-friendly, efficient, and convenient mobility options for commuters in urban, suburban, and even rural areas.

Today, automated vehicles are proposed and employed across various use cases, leading to some confusion and unrealistic expectations. To provide clarity on the objectives of the AVENUE project, we categorised them into the following applications of automated<fnref n="1" /> vehicles in today’s context:

1. Public Transport Fixed Line or Predefined Geofenced Zone Local Transport:

- Operates within predetermined geofenced areas with established stop points.

- May or may not require physical infrastructure.

- On-demand transport is possible, with ride pooling options typically mandatory.

2. Shared Autonomy for Long and Short Distances (VDV, 2015):

- Involves shared or private transportation using non-privately owned vehicles.

- These vehicles are capable of traveling and stopping at various locations.

3. Owned Autonomy (ibidem):

- Refers to private transportation using privately owned vehicles.

- Offers 100% control over mobility requirements for the vehicle owner.

This categorisation helps define the different levels of automated mobility services, each catering to specific needs and preferences in urban transportation. Public transport, which is the target of the AVENUE project (Konstantas, 2021), targets the first of the above categories. Public transport serves a distinct role that distinguishes it from a taxi service as it is intended to be the most cost-effective mode of non-human-powered travel, remaining cost-effective and accessible, while other options provide varying degrees of flexibility and control to users but at higher costs.

The deployment of automated shuttles for public transportation is a promising development, but it is crucial to emphasise that their success hinges on testing and evaluation under real-world conditions, as the road to a seamless automated future is paved with uncertainties, technical challenges, and regulatory hurdles (Antonialli et al., 2022). Therefore, it is imperative to conduct real tests in actual deployment

<footnote n="1">¹According to the taxonomy recommendation of the On-Road Automated Driving (ORAD) Committee of SAE Mobilus related to driving automation systems for on-road motor vehicles, we will use in the following the term “automated” instead of the popular “autonomous” (SAE International, 2023).</footnote>
scenarios to identify potential issues, correct mistakes, and obtain invaluable feedback from users.

In this chapter, we present the deployments in the different sites of the AVENUE project where fully automated shuttles were (and in some still are) being deployed for shared public transportation services. These case studies serve as compelling examples of how automated shuttle technology is evolving and adapting to the unique challenges and opportunities presented in different urban landscapes. Through these deployments, we were able to understand and concretise the hidden issues, for which we had just some vague idea, and refine this models, technology, and services developed in order to ensure integration into our daily lives and related urban environment.

The significance of this research lies not only in its contribution to the development of automated shuttle technology but also in its potential to reshape the way we envision public transportation in the twenty-first century. By highlighting the challenges faced, lessons learned, and the ultimate goal of enhancing the daily commute for countless individuals, this chapter aims to provide a comprehensive perspective on the deployment of automated shuttles for public transportation.

In the pages that follow, we will delve into the specific case studies, examining the unique contexts and challenges of each deployment site (an overview is provided in the following table). Through these analyses, we hope to shed light on the multifaceted nature of automated shuttle integration and inspire continued research, innovation, and collaboration in the field of automated public transportation (Table 2.1).
<table><caption>Table 2.1 Summary of AVENUE operating site (+ODD components)</caption><thead><tr><th></th><th>(TPG) Geneva</th><th></th><th>(Holo) Copenhagen</th><th>(Holo) Oslo</th><th>(Holo) Copenhagen</th><th>(Keolis) Lyon</th><th>(Sales-Lentz) Luxembourg</th><th></th><th></th><th></th></tr></thead><tbody><tr><td>Site</td><td>Meyrin</td><td>Belle-Idée</td><td>Nordhavn</td><td>Ormøya</td><td>Stagelse</td><td>Parc OL</td><td>Pfaffenthal</td><td>Contern</td><td>Esch-sur-Alzette</td></tr><tr><td>Funding</td><td>TPG</td><td>EU + TPG</td><td>EU + Holo + AM + Ruter/Movia</td><td>EU + Holo + AM + Ruter/Movia</td><td>EU + Holo + AM + Ruter/Movia</td><td>EU + Keolis</td><td>EU + SLA</td><td>EU + SLA</td><td>EU + SLA + Ville d'Esch</td></tr><tr><td>Start date of the project</td><td>August 2017</td><td>May 2018</td><td>May 2017</td><td>August 2019</td><td>August 2019</td><td>May 2017</td><td>July 2018</td><td>July 2018</td><td>February 2021</td></tr><tr><td>Start date of trial</td><td>July 2018</td><td>June 2020</td><td>September 2020</td><td>December 2019</td><td>August 2021</td><td>November 2019</td><td>September 2018</td><td>September 2018</td><td>September 2021</td></tr><tr><td>Type of route</td><td>Fixed circular line</td><td>Area</td><td>Fixed circular line</td><td>Fixed circular line</td><td>Area</td><td>Fixed circular line</td><td>Fixed circular line</td><td>Fixed circular line</td><td>Fixed circular line</td></tr><tr><td>Level of on-demand service*</td><td>Fixed route/fixed stops</td><td>Flexible route/ on-demand stops</td><td>Fixed route/fixed stops</td><td>Fixed route/fixed stops</td><td>Flexible route/ on-demand stops</td><td>Fixed route/ fixed stops</td><td>Fixed route/ fixed stops</td><td>Fixed route/ fixed stops</td><td>Fixed route/fixed stops</td></tr><tr><td>Route length</td><td>2.1 km</td><td>38 hectares</td><td>1.3 km</td><td>1.6 km</td><td>5 km</td><td>1.3 km</td><td>1.2 km</td><td>2.3 km</td><td>1 km</td></tr><tr><td>Read environment</td><td>Open road</td><td>Semiprivate</td><td>Open road</td><td>Open road</td><td>Open road</td><td>Open road</td><td>Public road</td><td>Public road</td><td>Public road/ pedestrian zone</td></tr><tr><td>Type of traffic</td><td>Mixed</td><td>Mixed</td><td>Mixed</td><td>Mixed</td><td>Mixed</td><td>Mixed</td><td>Mixed</td><td>Mixed</td><td>Mixed</td></tr><tr><td>Speed limit</td><td>30 km/h</td><td>30 km/h</td><td>30 km/h</td><td>30 km/h</td><td>30 km/h</td><td>8–10 km/h</td><td>30–50 km/h</td><td>50 km/h</td><td>20 km/h</td></tr><tr><td>Roundabouts</td><td>Yes</td><td>Yes</td><td>No</td><td>No</td><td>No</td><td>Yes</td><td>No</td><td>No</td><td>No</td></tr><tr><td>Traffic lights</td><td>No</td><td>No</td><td>No</td><td>No</td><td>No</td><td>Yes</td><td>Yes</td><td>Yes</td><td>No</td></tr><tr><td>Type of service</td><td>Fixed line</td><td>On demand</td><td>Fixed line</td><td>Fixed line</td><td>On demand</td><td>Fixed line</td><td>Fixed line</td><td>Fixed line</td><td>Fixed line/ on demand</td></tr><tr><td>Concession</td><td>Line (circular)</td><td>Area</td><td>Line (circular)</td><td>Line (circular)</td><td>Area</td><td>Line (circular)</td><td>Line (circular)</td><td>Line (circular)</td><td>Line (circular)</td></tr><tr><td>Number of stops</td><td>4</td><td>>35</td><td>6</td><td>6</td><td>6</td><td>2</td><td>4</td><td>2</td><td>5 (+4 on demand)</td></tr><tr><td>Type of bus stop</td><td>Fixed</td><td>Fixed</td><td>Fixed</td><td>Fixed</td><td>Fixed</td><td>Fixed</td><td>Fixed</td><td>Fixed</td><td>Fixed (+4 virtual)</td></tr><tr><td>Bus stop infrastructure</td><td>Yes</td><td>Sometimes, mostly not</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Number of vehicles</td><td>1</td><td>3–4</td><td>1</td><td>2</td><td>2</td><td>2</td><td>2</td><td>1</td><td>1</td></tr><tr><td>Timetable</td><td>Fixed</td><td>On demand</td><td>Fixed</td><td>Fixed</td><td>On demand</td><td>Fixed</td><td>Fixed</td><td>Fixed</td><td>Fixed/ on demand</td></tr></tbody></table>
<table><thead><tr><th></th><th>Monday–Friday (5 days)</th><th>Sunday– Saturday (7 days)</th><th>Monday–Friday (5 days)</th><th>Monday–Sunday (7 days)</th><th>Monday–Friday (5 days)</th><th>Tuesday and Thursday, Saturday, Sunday, and every public holiday (6 days)</th><th>Monday–Friday</th><th>Monday–Saturday</th></tr></thead><tbody><tr><td>Operation hours</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Timeframe weekdays</td><td>06:30–08:30/ 16:00–18:15</td><td>07:00–19:00</td><td>10:00–18:00</td><td>7:30–21:30</td><td>07:00–18:00</td><td>08:30–19:30</td><td>12:00–16:00, 16:45–20 h00</td><td>7:00–9:10, 15:50–18:35</td></tr><tr><td>Timeframe weekends</td><td>No service</td><td>07:00–19:00</td><td>No service</td><td>9:00–18:00</td><td>Only at special events</td><td>08:30–19:30</td><td>10:00–21:00</td><td>No service</td></tr><tr><td>Depot</td><td>400 m distance</td><td>On-site</td><td>800 m distance</td><td>200 m distance</td><td>200 m distance</td><td>On-site</td><td>On-site</td><td>On-site</td></tr><tr><td>Driverless service</td><td>No</td><td>No</td><td>No</td><td>No</td><td>No</td><td>No</td><td>No</td><td>No</td></tr><tr><td>Drive area type/ ODD</td><td>B roads</td><td>Minor roads/ parking</td><td>B roads/minor roads</td><td>B roads</td><td>B roads/parking</td><td>B roads</td><td>B roads/parking</td><td>B roads</td></tr><tr><td>Drive area geo/ ODD</td><td>Straight lines/plane</td><td>Straight lines/ plane</td><td>Straight lines/plane</td><td>Curves/slopes</td><td>Straight lines/curves</td><td>Straight lines/ plane</td><td>Straight lines/ plane</td><td>Straight lines/ plane</td></tr><tr><td>Lane specification/ ODD</td><td>Traffic lane</td><td>Traffic lane</td><td>Traffic lane</td><td>Traffic lane</td><td>Traffic lane</td><td>Traffic lane</td><td>Traffic lane</td><td>Traffic lane</td></tr><tr><td>Drive area signs/ ODD</td><td>Regulatory</td><td>Regulatory</td><td>Regulatory, warning</td><td>Regulatory</td><td>Regulatory</td><td>Regulatory</td><td>Regulatory</td><td>Regulatory</td></tr><tr><td>Drive area surface/ODD</td><td>Standard surface, speed humps</td><td>Standard surface, speed humps</td><td>Standard surface, speed humps</td><td>Frequent ice, snow</td><td>Standard surface, snow during winter</td><td>Standard surface, potholes</td><td>Standard surface</td><td>Standard surface</td></tr></tbody></table>
## 2.2 The Changing Landscape of Mobility

There is a noticeable trend of people leaving rural areas and migrating towards more densely populated cities and suburbs. This mass movement results in higher population concentrations per square mile (United Nations, 2018). The consequence of this increased population density is an upsurge in commuter numbers and a growing demand for urban and suburban transportation services, leading to an increased use of private vehicles for commuting.

In response to the ever-increasing number of private vehicles within cities, a current prevailing trend in Europe is the restriction of traditional motorised individual traffic in city centres. Instead, there is a focus on providing shared public transportation options with the aim of reducing environmental impacts and enhancing the overall quality of life for both citizens and commuters (Nieuwenhuijsen & Khreis, 2016).

The future of transportation hinges on collaborative efforts to create sustainable mobility options, with on-demand automated public transport at the forefront. This represents a transformative shift in public transportation and has the potential to be a catalyst for social change.

In the following sections, we will explore the AVENUE deployments in Europe. Before delving into these specific deployments, we will elucidate the driving factors behind this trend and explore potential solutions that have paved the way for the adoption of automated vehicles in public transportation.

### 2.2.1 Fighting Congestion

The primary goal of contemporary mobility regulation is to mitigate the environmental impact, specifically stemming from CO₂ emissions resulting from various modes of transportation (European Commission, 2020). A fundamental step towards addressing climate protection is the transition from internal combustion engine vehicles to electric ones. However, this shift alone may not be adequate, as it fails to alleviate the overall strain on road infrastructure. Mere replacement of traditional individual vehicles with electric counterparts still results in the same road occupancy and congestion issues.

An alternative approach to combat traffic congestion could involve restricting the entry of single-occupant or dual-occupant vehicles into inner cities. Instead, priority could be given to purpose-designed vehicles capable of efficiently transporting a significant number of passengers or goods while optimising road space utilisation. This approach might encompass larger vehicles for mass transportation along prominent routes, alongside smaller vehicles ready to promptly respond to on-demand requests.

By adopting this strategy, non-essential traffic could be reduced, and curbside parking areas could be repurposed for intelligent mobility solutions, bicycle lanes,
and other innovative transportation methods. This transformation would inevitably reshape urban infrastructure and create fresh opportunities for public transportation agencies, provided they can offer more customer-centric transport services (OECD/ ITF, 2015, 2016, 2017, 2018).

### 2.2.2 The Transformation of Public Transportation

In response to the growing need to transport larger numbers of people efficiently, especially in urban centres and mobility hubs, the conventional approach has often involved separate ground-level railway and bus lines. These systems serve the majority of commuters effectively but fall short of providing the door-to-door convenience associated with individual car travel.

Public transportation journeys often consist of a collective core, with personalised segments at the start and end to accommodate the individual needs of passengers. To address the growing demand for smooth door-to-door transportation solutions within the public transport system, it is imperative to adopt a multifaceted approach. This approach entails the integration of various transportation modes into a unified and interconnected system, commonly referred to as mobility as a service (MaaS). The central challenge for public transport operators is to create a multi-modal transportation solution that not only matches the convenience of private car usage but actually surpasses it in terms of quality.

The transformation of city centres, coupled with the phasing out of private cars, necessitates the introduction of green and health-conscious mobility alternatives or robust public transport systems. While walking and cycling are gaining traction, there will always be a segment of the population reliant on vehicle transit. On-demand public transport with smaller vehicles could address this need within car-free city areas. To integrate the related external costs (competition with public transport in particular mass transit, additional congestion costs, and/or other costs) for the city and the citizen, a different price should be claimed to the users.

On-demand public transport represents enhanced efficiency and sustainability. Passengers can schedule their trips at their convenience within designated service hours, arranging for minibus pickups and drop-offs at agreed-upon locations, all facilitated through online booking or dedicated applications. This flexibility streamlines the public transport experience, making it more convenient for daily commuters (Alonso-González et al., 2018).

Another crucial aspect of this evolution is the development of high-capacity, demand-responsive vehicles designed to maximise passenger capacity and minimise overall travel distance. The primary challenge lies in coordinating passenger collection and drop-off for on-demand travel, which may require either a few larger vehicles or numerous smaller ones, with the latter incurring higher costs due to the need for dedicated drivers for each.

Currently, public transport operators tend to utilise vehicles that are specialised for either bulk transportation or individual travel. However, it can be highly
inefficient and impractical to transfer a large group of, for example, 200 people using minibuses designed for just 12 passengers each, as this approach essentially forces the implementation of a monomodal transport solution.

Nevertheless, there are innovative options available. For example, large trolleybuses, specifically designed for fixed main routes equipped with overhead electricity lines, can offer efficient transportation solutions. These vehicles can also serve the first and last mile on an on-demand basis by using an additional battery pack when traveling off the main electrified routes. However, it is important to note that large trolleybuses may come with a higher cost and could present challenges when navigating through smaller neighbourhoods due to their size and overhead line constraints.

A potential solution to overcome these challenges is the utilisation of shared driverless vehicles for public transportation. Automated and connected vehicles have already undergone successful testing, with the primary hurdle being their interaction with older vehicles, bicycles, pedestrians, and existing infrastructure.

### 2.2.3 Readiness to Adopt New Transportation Means

End users seek a seamless, user-friendly travel experience. They desire an all-encompassing travel assistant that plans their journey, anticipates their travel habits, and provides real-time information on vehicle arrivals, appearance, pickup locations, drop-off points, delays, and essential itinerary changes, all while ensuring an efficient flow of pertinent information.

In the modern transportation landscape, passengers are increasingly open to adopting innovative transportation modes that make use of cutting-edge technologies and alternative means of mobility. A prime example of this is the surging popularity of electric bicycles. These battery-powered models have become a captivating category within the evolving transportation ecosystem, attracting a growing number of enthusiasts. Electric bicycle riders often sidestep the complexities of multimodal transportation chains, as they can journey directly from their starting point, “A”, to their destination, “B”, without relying on other modes of transport. The introduction of electric bicycles has not only extended the range of cyclists but has also enhanced their capabilities, allowing them to cover even greater distances by combining their pedal power with electric assistance. This trend underscores passengers’ readiness to embrace innovative, eco-friendly transportation solutions. Holiday travel stands as a well-established example of the widespread shift towards multimodal transportation. It vividly illustrates the transformation of our travel habits over time. Historically, families used to embark on monomodal journeys, primarily traveling by car directly from their residences to their holiday destinations. However, the landscape of holiday travel has evolved significantly, and contemporary vacations now often involve a more intricate and multimodal approach.

Today, families embark on individualised journeys, departing from their homes to reach airports. Once at the airport, they collectively board planes, and upon arriving at their destination, they are individually dispatched to reach their final holiday
spots. Surprisingly, many travellers have come to embrace this somewhat complex multimodal approach, despite its inconveniences. This shift is primarily driven by the numerous advantages it offers, including cost-effectiveness, speed, and the ability to access more remote and distant locations. It underscores how passengers are adapting to and appreciating the benefits of multimodal travel experiences.

### 2.2.4 Challenges for Public Transport Operators (PTOs)

We find ourselves at a critical juncture in public transportation, where a paradigm shift is on the horizon. The necessary technology is readily available, and passengers are eager to embrace a new and improved transportation experience. However, public transport operators (PTOs) face a complex array of challenges that must be addressed to make this transformation a reality. These challenges include V2X communication, fleet orchestration intelligence, GDPR compliance, cybersecurity, data collection, legal considerations, societal changes, economic implications, environmental costs, and more (Davidsson et al., 2016; Konstantas & Fournier, 2023).

In addition to addressing these challenges, achieving passenger and citizen acceptance is a pivotal aspect of the successful transformation of public transportation. This involves not only overcoming technological and regulatory challenges but also re-evaluating the cost structure and providing new services that align with evolving passenger expectations. Here we can mention some expectations of passenger like transparent and affordable pricing, recognising that passengers have diverse needs and preferences and offering personalised services, introducing innovative and convenient services that enhance the passenger experience, creating feedback channels for passengers to express their opinions, and finally effectively communicating the benefits of the new transportation options and services.

By focusing on these aspects, public transport operators can foster passenger acceptance and encourage the adoption of multimodal and innovative transportation solutions. This, in turn, can contribute to the success of the paradigm shift in public transportation towards more sustainable mobility.

In the subsequent sections of this document, we delve into the endeavours of public transport operators within the AVENUE project. They aim to address the questions raised earlier by drawing from their experiences gained through various deployments in diverse European cities.

## 2.3 The Geneva Sites

### 2.3.1 Objectives

Starting 2017, Transport Publics Genevois (TPG), the public transport operator in the Swiss Canton of Geneva, has been testing an automated vehicle on a fixed 2.1-km route with four bus stops. This first experience allowed TPG to be a partner in
<figure><img src="image_11.png" /><figcaption>**Fig. 2.1** The Belle-Idée with 75 stop points</figcaption></figure>

the European co-funded H2020 AVENUE project and to set up a fully automated transport system on the Belle-Idée estate in Thônex, Geneva, Switzerland, combining all future key elements of on-demand automated public transport (Fig. 2.1).

As part of the AVENUE project, the aim was to demonstrate a comprehensive, shared, on-demand, door-to-door, and dynamically routed public transport service. This service utilised a fleet of automated minibuses operating within a geofenced zone, eliminating the need for fixed routes, set timetables, or traditional bus stops. The system was seamlessly integrated into the existing transport network.

Passengers had the exclusive option to book rides through a dedicated application. The project also explored the feasibility of allowing passengers to board and disembark at system-defined stop points without the need for physical infrastructure like ground markings or information display poles.

*The objective was to develop a 100% automated public transport service in which the passenger is the only human link.*

The following steps showcase how this objective was brought into practice:

1. A user on-site wants to be transported as soon as possible from his current position to the entrance of building 8, named reception.

2. The user takes his smartphone and opens up the tpgFlex on-demand application from TPG.

3. The user only has to submit his final destination. His smartphone already knows the user's current position and, if not changed by the user, assumes that he is alone and wants to travel right away.

4. The moment the user validates one of the proposed offers according to his requirements regarding travel time, service level, and pricing, a door of the on-site depot opens, and one of the induction-charged electric minibuses drives out automatically and heads down to the user's location via the fastest route.
5. Once the vehicle arrives at the pickup location, the user opens the doors of the minibus, gets in, and finds a seat. The vehicle automatically closes its doors and directly hovers to the user's destination by choosing the fastest or most convenient route.

6. If another person makes a reservation at the same time on a very similar itinerary as the first user, the minibus will divert its trajectory to combine both reservations and serve the other user as well.

7. After it arrives at the user's destination, the on-demand system can send the vehicle to another location in order to achieve a new mission, back to the depot to charge batteries, or place the vehicle at a key location since the on-demand system knows from experience that most of the bookings are being made at that bus stop at that time of the day.

The 100% automated system, comprising three to four vehicles, is continuously supervised by an on-site supervisor who is supported by two automated monitoring systems:

1. The vehicle monitoring system supervises the vehicle's road-handling capabilities, such as monitoring harsh braking and object detection.

2. The passenger monitoring system is responsible for ensuring the passengers' well-being while on board. It monitors for situations like passengers falling, experiencing health issues, engaging in altercations, or potential incidents like bag snatching. Additionally, this system checks the available interior space for the on-demand system.

Both systems provide the supervisor with visual and acoustic alerts, enabling him/her to take appropriate action. These actions may include observing monitoring tools to assess the situation, inspecting the interior of the vehicle, stopping the vehicle remotely, opening doors from a distance, or contacting emergency services such as calling an ambulance (Fig. 2.2).

<figure><img src="image_12.png" /><figcaption>**Fig. 2.2** Belle-Idee on-site supervision office</figcaption></figure>
It is worth noting that, as of the current date, there is no functionality for the supervisor to remotely control or manoeuvre a vehicle at low speeds (<6 km/h) to a safe position. This capability is not included in the project's objectives due to technical limitations.

The on-demand system is fully accessible from the supervision office, allowing the supervisor to dispatch a vehicle to individuals who may not have access to a smartphone and have made reservations by telephone.

As of the date of this document and not included in the project's objectives due to legal restrictions, the possibility of removing the operator (driver) from the vehicle is not yet allowed. However, the primary objective within the AVENUE project was to demonstrate the ability to operate without the need for an onboard operator.

### 2.3.2 Deployment

Due to the complexity of the project and the fact that most partners did not have experience in combining all these technologies, the deployment of the entire project was divided into three phases.

#### Phase 1: Between July and September 2020

* Mapping of the entire Belle-Idée site (summer map)

* Deployment of one vehicle on 45% of all available roads

* Creation of 27 stop points, 4 existing TPG bus stops, and 23 virtual stop points

* First tests with a safety operator and without passengers

* Training of safety operators

#### Phase 2: Between October and December 2020

* Deployment of/increase to two vehicles on 70% of all available roads

* Creation of/increase to 53 stop points, 4 existing TPG bus stops, and 49 virtual stop points

* Vehicle testing with a safety operator and without passengers

* First "fully automated on-demand system" testing.

* First software release 6.0 test

* Training of safety operators

#### Phase 3: Between January and March 2021

* Mapping of the entire Belle-Idée site (winter map)

* Deployment of/increase to three vehicles on 99% of all possible roads

* Tracing of a route to the TPG Seymaz bus stop outside the domain

* Creation of/increase to 75 stop points, 5 existing TPG bus stops and 70 virtual stop points

* Installation of software update to version 6.1 which enabled better road holding and easier on-demand

* Fully automatic depot entrance and exit of vehicles

* Vehicle testing with a safety operator and without passengers

* On-demand system testing with application booking, 100% automated

* Training of safety operators
<figure><img src="image_13.png" /><figcaption>**Fig. 2.3** Belle-Idee service travel information</figcaption></figure>

At the end of 2021, software update 6.2 was installed which enabled for a dynamic update of an ongoing on-demand mission, hence vehicles already on their way to the next bus stop could be rerouted to being able to pick up or drop off passengers elsewhere (Fig. 2.3).

At the end of 2022, the operating hardware and software of the vehicles was changed from Windows to Linux for better system stability.

During the deployment phases, every safety operator drove numerous kilometres on-site to test and identify issues as well as to get acquainted with the overall traffic after being trained and accompanied by the automated vehicle assistant trainer.

### 2.3.3 Achievements and Key Success Factors

Due to the willingness to make the project happen and the combined forces from the Swiss Federal and Geneva Cantonal Authorities, the AVENUE project partners, as well as the TPG Managing Board, the project team was able to create and set up the project and start giving demos for select groups of people and testers after 2.5 years.

Unfortunately, the partner in charge of the on-demand vehicle dispatching system went bankrupt soon after and the project was brought to a halt. It then took another 8 months to start for the second time. Since the service started its operation again, various public transport delegations from all over the world who systematically validated the importance of the solution have been welcomed.
At the end of the project, the only issue that kept the vehicles from driving fully automated was obstacles on the streets, such as wrongly parked cars, which the vehicle cannot bypass (yet). When the vehicle detects an object that is not moving, it will stop driving until the object has been removed. When it arrives at an object moving in the same direction as the vehicle, the vehicle will adapt its speed and follow the object from a distance. When an object is moving in another direction as the vehicle, the vehicle comes to a halt and waits for the object to go out of the way, and when the road is free, it starts driving again.

### 2.3.4 Recommendations

**SAE Level 4+ for Public Transport** The development of fully automated vehicles has progressed at a slower pace than initially anticipated and previously announced by international car manufacturers. The most notable achievements currently available on the market can be categorised into two main use cases:

1. SAE Level 3 Automated Highway Lane and Traffic Jam Driving: This represents an advanced driver assistance system that enables automation for highway lane keeping and managing traffic jams.

2. SAE Level 4 Fully Automated Driving: This pertains to fully automated driving on pre-programmed virtual routes, typically at very low speeds.

These advancements illustrate the current status of automated driving technology, where different levels of autonomy and capabilities are achieved. The key distinguishing factors revolve around speed and the complexity of driving conditions. As of the present, achieving SAE Level 5 fully automated driving, as well as SAE Level 4 pre-programmed automated driving at speeds exceeding 30 km/h, remains unattainable. Commercial availability for such advanced capabilities is not anticipated before 2027. This, however, does not mean that the development and testing of fully automated vehicles need to stop. With regard to public transport operators, there is an important use case being created on a political level: thermic-powered vehicles are starting to be banned from city centres, parking spots removed, and speed limits reduced to 30 and even 20 km/h. This means that, as public transport is deployed in a well-defined geofenced area in the city, with all the roads and bus stops known in advance, a highly efficient public transportation service can be provided with SAE Level 4 vehicles, integrated in a MaaS system with the existing main lines of bus, metro, and tram.

As it is not economically feasible for public transport companies to equip every fully automated vehicle with a legally required safety operator, removing the safety operator as in SAE Level 5 is essential. The interim solution could be to create an extra SAE Level, between Levels 4 and 5, for public transport only which aligns with the following requirements:
* 30 km/h speed limit

* Pre-programmed virtual line driving

* Without a safety operator

* Supervision at near distance

The creation of such a “SAE Level 4+ for public transport” or SAE Level 4.5, hence between SAE Level 4 and 5, has already been proposed by the Association of German Transport Companies—VDV—in 2020.<fnref n="2" />

### 2.3.5 Future Developments

Due to the maturity of the project and Europe-wide recognition as being an urban public transport solution, TPG will continue gaining experience with new transport modes and technologies within the Horizon Europe Ultimo project. Firstly, TPG will scale up the current Belle-Idée living lab test site with the following steps:

1. Connect the Belle-Idée estate to the nearest train/metro station via a 1.5-km route.

2. Test at least one vehicle in 100% fully automated mode, without an operator on board, with the authorisation to supervise several vehicles simultaneously at a distance.

3. Reduce or eliminate the motorised traffic on the Belle-Idée estate completely.

4. Offer a made-to-measure mobility service to be able to transport everyone on-site.

5. Test the transport of goods in off-peak hours.

The second objective is to transform the existing classic driver-based rural on-demand service tpgFlex of the Champagne/Mandement region in the Swiss Canton of Geneva into an on-demand, door-to-door, fully automated, people and goods transport service integrated in the TPG transport system and later perhaps in a MaaS.

## 2.4 Denmark and Norway

In the AVENUE project, AM was running three test sites:

* Nordhavn, Copenhagen, and Denmark

* Ormøya, Oslo, and Norway

* Slagelse and Denmark

<footnote n="2">²Verband Deutscher Verkehrsunternehmen e. V. (VDV): Eckpunkte zum Rechtsrahmen für einen vollautomatisierten und fahrerlosen Level 4 Betrieb im öffentlichen Verkehr, Positionspapier / September 2020, Köln.</footnote>
The Ormøya route was originally initiated without being a part of AVENUE, but an agreement has been made to include the site for 5 months, to begin with. The Norwegian site ended in December 2020. A new Danish site in Slagelse Hospital began in September 2021, with a focus on on-demand transportation service.

### 2.4.1 Nordhavn

The Copenhagen pilot site was situated in an area of the city called Nordhavn. Nordhavn is an active industrial port that is undergoing a transformation—turning into Copenhagen's new international waterfront district offering residential and commercial buildings. When the development of Nordhavn is done, the area will house more than 40,000 residents and 40,000 employees.

Nordhavn aims at being an eco-friendly neighbourhood and contributes to boosting Copenhagen's image as an environmental metropolis. The city should vibrate with life as a versatile urban area with a multitude of activities and a wide range of shops, cultural facilities, and sports facilities. The area is becoming more and more populated, and the need for local transportation is expected to keep growing (Fig. 2.4).

Currently, the Nordhavn area is serviced by a nearby S-train station (approx. 1.1 km away) and bus stops located near the train station. There are, however, no buses or trains running directly in the area—creating a great opportunity for

<figure><img src="image_14.png" /><figcaption>**Fig. 2.4** The Nordhavn route area seen from above</figcaption></figure>
automated vehicles to function as a new public transport solution, connecting the area much better than it is today. In 2020 two new metro stations have been built—opening in the periphery of the neighbourhoods.

### 2.4.1.1 Objectives

The main users of the shuttle service have been the residents of Nordhavn (including families, children, and elderly), commuters working in Nordhavn, and visitors to the area. Several usage scenarios can thereby be anticipated:

* Ease mobility within the area for the residents and commuters working in the area.

* Used for the first/last mile from the main road/entry point to the different stops within the area for residents and commuters working there.

* Provide easier access from the main road to, e.g. the harbour pool, restaurants, and cultural facilities for visitors and families.

Planned services provided for the end users:

* The shuttles are free of charge during the pilot project in Denmark, so there is no ticketing yet.

* There are static bus stops providing the position of the bus, relative to the given stop.

* The real-time location of buses can be seen in the mobile application.

* Besides the bus stop signs, users can find information about the pilot project on the AM website and in the AVENUE mobile application.

During the project period, it was the aim to test the services developed through the AVENUE project, e.g. real-time position of the bus, on-demand booking, and accessibility for disabled persons.

### 2.4.1.2 Deployment

The first route was placed in the area called Århusgadekvarteret. This area was the first one finished, and residents started moving there in 2015. Since then, different squares, the harbour promenade, and a rooftop gym have been evolved and taken into use. Furthermore, special attention has been paid to developing local retail, so today there are supermarkets, cafes, restaurants, and different specialised retailers. There are several shared space areas on the route including a bathing zone.

The first route is a circle line around the area (blue line on the map below), making it easier to get around and to enter the area from outside Nordhavn. Our garage is located on the next peninsula close to Århusgadekvarteret (the red line on the below map) (Fig. 2.5).
<figure><img src="image_15.png" /><figcaption>**Fig. 2.5** Map showing Nordhavn route</figcaption></figure>

The pilot route is going to be in mixed traffic with cars, pedestrians, bicycles, etc. The area is, in general, a low-speed area with 20–50 km/h speed limits on the route, and in the 50 km/h limit areas, the recommended speed for cars is 30 km/h.

Operation facts:

* 2 AVs running (initially)

* Mon–Fri 10.00–18.00

* Loop route with six stops

### 2.4.1.3 Achievements and Key Success Factors

#### Passengers and Distance Driven

Passengers we counted every day of operation. In total, we have transported 1579 passengers. It is seen that most passengers were transported at the beginning of the pilot, possibly due to the route location close to the harbour popular in the summer time. Another possible explanation could be that locals got used to the shuttle as an attraction and as time went by a sense of novelty disappeared (Fig. 2.6).

A total of 2.417 km has been driven in Nordhavn. The count can be seen increasing in almost linear progress since August 2020 (Fig. 2.7).

#### Driving Speed and Automated vs. Manual Mode

The driving speed is seen to be increasing slightly over the operational time period from an initial 7 km/h to 7.89 km/h. This is despite an increase in manually driven kilometres primarily related to an increase in parked cars on the route.

In total, close to 992 h have been driven during the pilot. In regard to the navigation mode, 82.6% of overall driving on the route was done in automated mode. The
Distance and passengers pr. month

<figure><img src="image_16.png" /><figcaption>**Fig. 2.6** Distance and passengers per month in Nordhavn</figcaption></figure>

Total distance

<figure><img src="image_17.png" /><figcaption>**Fig. 2.7** Accumulated distance driven in Nordhavn</figcaption></figure>

rest of 17.4% driven in manual mode was mostly due to a large amount of illegally parked cars on the route and due to roadworks. Driving manual to and from the garage is filtered out.

Issues Reported on Route

The main issue reported through the safety operator app was parked cars on the road. The parked cars disturb the driving, as the AV is not able to diverge from its planned trajectory, and hence the operator is forced to do a manual takeover in order to pass the parked vehicle. In total, this has been registered 1995 times.
Operational hours lost pr. downtime cause

<figure><img src="image_18.png" /><figcaption>**Fig. 2.8** Causes of downtime in Nordhavn by downtime hours</figcaption></figure>

The issue of parking on the road has been reported in several locations on the route. Mostly around Århusgade, Sandkaj, and Göteborg Plaza. The issues with parked cars in the Nordhavn area were significantly contributing to impeding the operation, finally resulting in its closure.

Downtime and Cancelled Operation

The following figure illustrates the distribution of the five most common reasons for downtime/cancelled operation per downtime hour it caused. The downtime was primarily due to roadwork on the route, which made driving in the designated trajectory impossible and manual takeover necessary (Fig. 2.8).

2.4.1.4 Recommendations

During the deployment of the shuttles in Nordhavn, multiple learnings were achieved. They are described in the following.

Object-Detection Challenges

The Nordhavn area is packed with restaurants, cafes, and shops with outdoor seating and display areas. Larger parts of the Nordhavn route are shared space areas, where pedestrians, bicycles, and vehicles interact in a shared road, rather than separated lanes. This type of city planning causes many situations where the automated shuttles detect obstacles and stop as a consequence. Furniture and other objects
cross into the driving lanes, causing the shuttle to stop and requiring the safety operator to move the objects away from the driving lanes or manoeuvre manually around obstacles. For a completely automated operation without a safety operator, the area would probably not be ideal because of these shared space areas, and at least it would require significant technological breakthroughs before an automated vehicle would be able to operate in the Nordhavn area without a safety operator. This is also due to narrow roads, where two cars cannot pass each other without human interaction.

## Increased Mixed Traffic in High Seasons

During the summer period, the swimming areas at Nordhavn attract many visitors who arrive by bike. Due to the large number of bikes, bikes are sporadically parked outside of the appointed areas for bike parking. This caused difficult driving conditions, and many operational days were shortened as the vehicles were not able to drive due to the many parked bikes, and it was deemed impossible to have the safety operator remove the bikes during every round of driving.

## Consequences of Construction Work

As the Nordhavn area is under heavy construction, the shuttles have had to operate in an area with many trucks and work-related vehicles being parked illegally and shutting off parts of the route. This has caused delays and cancellations of the operation for shorter periods and sometimes days.

## Lack of Parking Spots Compared to the Number of Cars

The Nordhavn area is a very busy area with local residents, offices, shops and restaurants, and many daily visitors. Some of these visitors travel by car and can find it very difficult to find a place to park the car during peak hours. This resulted in many illegally parked cars on the route, and the safety operators have been taking over manually multiple times every day to overtake parked cars. Driving in an area that requires manual overtaking does affect the total percentage of kilometres driven in automated mode.

## Low-Speed Limit

Most streets in Nordhavn have a speed limit of 30 km/h which suits the automated vehicles' speed capabilities. In general, a low gap between the vehicle's top speed and the speed limit provides a more safe operation, with less risky overtaking from other road users. This contributes to Holo's general assessment of the Nordhavn area as a safe environment to drive and test low-speed automated vehicles.
### 2.4.1.5 Future Developments

Unfortunately, the route in Nordhavn had to be shut down, and AM has investigated several scenarios to still meet the learning objectives for the AVENUE project. In the following the process and reasoning for shutting down the Nordhavn site will be further elaborated.

#### Complications in Nordhavn

In the fall of 2020 AM started to investigate the potential for expanding the Nordhavn site. AM investigated several routes which could be added to the already active route in Nordhavn. The selection and evaluation focused on last-mile transportation from the two metro stations and to both residential and various business areas of Nordhavn.

In November 2020 all the potential new routes were discarded by By & Havn, as construction plans for the area would interfere with the automated minibuses. The area of Nordhavn is undergoing heavy construction, and due to delays in the construction work, several roads have been unavailable to use for the remaining period of the AVENUE project.

The above challenges in Nordhavn caused AM to seek alternatives for automated operations in the Copenhagen area. AM has evaluated several scenarios for how to still meet the objectives of the AVENUE project and decided to use the AVENUE shuttles on an existing Amobility site. In order to minimise the risk of delaying operations substantially, caused by long approval processes, AM investigated the use of an existing site in Denmark for the remaining months of operations in AVENUE.

AM was granted approval to start operations at Slagelse Hospital (Denmark) in March 2020. However, the project had been paused due to COVID-19. In the fourth quarter of 2020 AM and Movia (PTA) decided to restart the project in August 2021. AM and Movia discussed the possibility of integrating AVENUE as part of the Slagelse Hospital site and agreed to proceed with this possibility.

Even though this alternative only can support operations with Navya vehicles, AM has identified several crucial learnings in relation to on-demand and integration with PTA for ordering.

### 2.4.2 Ormøya

Due to the delays in launching the Danish demonstration site, it took some time before all four buses were in operation. Therefore, in May 2019 AM agreed with the consortium to include our subsidiary in Norway as a third party, so that two of AM's AVENUE buses could be deployed on a route there. This way AVENUE would still gain useful insights into the operation while awaiting the launch of the Copenhagen site.
Originally the plan was to include the two buses on the route Akershusstranda in central Oslo for 5 months beginning in June 2019. This would be a route with four buses running and the service fully integrated with existing public transport in Oslo. However, due to heavy construction, this route had to be cancelled. It was therefore decided to integrate AM's AVENUE buses on the second route "Ormøya" just outside Oslo centre. Ormøya is an island south of Oslo city centre connected by a bridge to the mainland and a bridge to a second island called Malmøya.

### 2.4.2.1 Objectives

AM is collaborating with Oslo Municipality, the Norwegian Public Roads Administration, and Ruter<fnref n="3" /> on a 3-year self-driving trial project. The project is an important milestone in the process of getting self-driving buses to the Oslo area. Oslo and Akershus wish to have 0% emissions across their public transportation, and this project will test if self-driving buses can support these ambitions for a sustainable public transport system. The end goal is for automated buses to be part of Ruter's regular offer in a few years.

The main purpose of the project was to investigate what self-driving vehicles can mean for everyday logistics in a neighbourhood. By increasing the frequency of public transport by means of small self-driving vehicles, the goal was to reduce the need for private cars in the area. One road leads in and out of the two islands that have a total of around 500 households. The local residents have a 12-m bus service which departs around once an hour for most of the day. On the mainland just off the inland is one of the major thoroughfares going into Oslo from the south, Mosseveien/E18. This main road has frequent express buses going in and out of Oslo. The automated bus service provided a high-frequency last-mile solution for the residents of Ormøya and Malmøya which connected them to the express service on Mosseveien/E18.

### 2.4.2.2 Deployment

The route is 1.6 km one way (3.2 km round trip) and has six bus stops. It runs from Nedre Bekkelaget bus stop which is located near Mosseveien/E18 where users can access high-frequency express buses to and from Oslo. Also near this end point is the local area public school that kids from Malmøya and Ormøya attend.

The other end point, the Malmøya bus stop, is right on the landing on the island of Malmøya where there is a turning place for the vehicles. This bus stop is also located close to a marina, where lots of Oslo residents keep their recreational boats. The four other bus stops are evenly distributed along the two end points. The bus stop Mailand is also located close to a public beach/swimming area and a marina

<footnote n="3">³The public transport authority for Oslo and Akershus counties.</footnote>
<figure><img src="image_19.png" /><figcaption>Fig. 2.9 Map of Ormøya route</figcaption></figure>

which attracts lots of visitors in the summer. The route can be seen below with the stops marked (Fig. 2.9).

The speed limit on the entire route is 30 km/h, and it contains several speed bumps which generally keep the speed in the area low. The condition and build of the road vary quite a bit along the route. Several places are very narrow, just barely wide enough for two vehicles to pass each other, and several stretches have poor asphalt quality. There is also a lot of vegetation close to the route.

In order to be able to offer the inhabitants a valuable self-driving travel service, we had to ensure high operational stability along the stretch. This has been challenging due to several elements, and we have therefore made ongoing adjustments in the offer to explore what it takes to ensure stable and reliable operation. Operational stability will be a success factor in initiating new, more complex self-driving bus lines in the years to come.

### 2.4.2.3 Achievements and Key Success Factors

#### Passengers and Distance

In total, 6637 passengers were transported and 22,984 km driven on the Ormøya route. During the 1-year pilot, there were over 5233 h of operation (total number when all three vehicles are added together). That is equal to approximately 395 operational days or 131.67 full operational days with 3 vehicles (1 operational day = 13.25 h) (Figs. 2.10 and 2.11).

The route in Ormoya was severely impacted by operational challenges and COVID-19 lockdowns in some months during the project period. This resulted in some periods with few passengers and less distance driven. In terms of passenger distribution, passengers were using the shuttle service for transport every day of the week. However, there was a somewhat higher number of passengers during the weekdays than the weekend.
## Total distance and total passengers

<figure><img src="image_20.png" /><figcaption>**Fig. 2.10** Accumulated distance and passenger count at Ormøya</figcaption></figure>

## Distance and passengers pr. month

<figure><img src="image_21.png" /><figcaption>**Fig. 2.11** Distance and passenger count per month at Ormøya</figcaption></figure>

## Automated vs. Manual Driving

In regard to the navigation mode, 93.8% of overall driving on the route was driven in automated mode. The rest of 6.8% driven in manual mode was mostly due to technical issues. Driving to and from the garage is filtered out.

Driving speed on the Ormøya route was between 9.44 and 10.53 km/h. The overall average speed was approximately 10 km/h. By the summer of 2020, a recommendation was done to improve driving in areas of the route.
## Issues Encountered on the Route

When looking at the distribution of different issues reported by the safety operator, again for this route “parking on road” is the most frequent issue occurring with a total occurrence of 1725 times. Operators fall as many as 62 times, signalling a safety issue in the working position of the operators (Fig. 2.12).

### 2.4.2.4 Recommendations

#### Public Transport in Oslo

The service at Ormøya functioned as an integrated part of Ruter's public transport offerings in the general Oslo area. This meant that the bus required a standard ticket which gives access to the entire network and that the service was included in Ruter's overall route planning tools for users. Neither Holo nor Ruter performed checks of valid tickets.

By all indications, users did not complain about the ticket requirement but viewed it as natural for service in Ruter's network.

#### User Experience

During the final quarter of operations, Ruter conducted a user survey around the shuttle. The survey was conducted by interviewing people walking or moving around the general area of Ormøya. In total Ruter collected 107 interviews each lasting

<figure><img src="image_22.png" /><figcaption>**Fig. 2.12** Issue distribution at Ormøya</figcaption></figure>
5-8 min during weeks 38, 39, 41, and 42 in 2020. The main purpose of the survey was to evaluate what users and local residents think of the self-driving bus service.

In general, respondents were positive towards the tests and felt that it was safe. However, the survey also showed clearly that the service was not providing a valuable mobility solution. Approximately 82% of passengers took the bus merely out of curiosity, while only 12% used the service for their daily commute. When local residents at Ormøya and Malmøya were asked why they did not use the automated bus for their daily mobility needs, two of the top answers were the low speed and that the bus did not go where they needed to go. Furthermore, low reliability was also noted as a reason why the service was not used for their daily mobility needs.

## Vegetation and Snow

The narrow road on Ormøya makes this site especially challenging when it comes to vegetation. There is little to no margin for the growth of vegetation. Both vegetation on the sidewalk and overhanging bushes and branches are stretching into the safety zones interfering with smooth operation.

Another issue at Ormøya is the high and low overhanging branches interfering are then detected by the vehicle causing it to brake or slow down (Fig. 2.13).

The rapid growth of vegetation in the summer months has led to constant interference with operations. In periods operations have been halted until the vegetation has been properly cut. In the summer months, April to September, we have seen the need to cut vegetation up to every second week.

<figure><img src="image_23.png" /><figcaption>Fig. 2.13 Photos showing the vegetation close to the vehicle trajectory on the route in Ormøya</figcaption></figure>
<figure><img src="image_24.png" /><figcaption>**Fig. 2.14** Photos showing snow and snow banks in and close to the vehicle's trajectories on the route at Ormøya</figcaption></figure>

Vegetation-related issues have heavily impacted the stability of the operation on this route. Comparing this site to other routes with less vegetation clearly shows a negative impact on the performance of the vehicles. Additionally, sudden braking caused by vegetation is a major safety concern. The sudden braking can cause cyclists, pedestrians, and following cars to potentially collide with the vehicle when it makes unexpected and seemingly irrational decisions like braking hard for a small branch near the trajectory.

In the winter months snow and ice proved a similarly big challenge. The operational design domain (ODD) for the Navya Arma vehicles states that they cannot operate when snow is falling or when the route is covered in snow. Falling snow proved quickly to be unsuitable for operation. With snow in the air, the vehicles make continuous false obstacle detections, and every snowfall resulted in a halt of operations.

The year 2020 did not see very much snow at the Ormøya site, and only on a couple of occasions did snow on the ground cancel operations, mainly because snow clearing was not done well enough to clear the vehicle's trajectory as highlighted in the image below (Fig. 2.14).
## Major Safety Issues

Already in the risk analysis of the route, before the operation commenced, the major safety concerns were identified as other road users behaving dangerously around the shuttle due to low speed and slow reaction to clear road or similar. Also, passengers and operators getting hurt inside the shuttle due to sudden and hard braking were highlighted along with intentional disturbances. These safety concerns proved to have been correctly assessed from the beginning, and they were the major safety concerns throughout the operation.

Through the Holo operator app, Holo was able to collect data on the potentially most dangerous situations that occurred on the route. The four most important categories that data was collected on are dangerous overtaking of the vehicle, intentional disturbance, operator falls, and passenger falls. Two major safety concerns that remain with an operation like the one on Ormøya are:

* The operators of Navya Arma vehicles do not have ideal working conditions. Sudden and hard braking has resulted in several mild injuries because of the lack of proper seating and suitable working positions.

* The low speed of the shuttle does cause other road users to act irresponsibly and attempt overtaking in areas that are not suited for overtaking like areas with bad overview or near pedestrian crosswalks.

## 2.4.3 Slagelse

The Nordhavn area should originally have been finished in 2020, but due to major delays in construction plans, parts of the Nordhavn route (streets) were closed permanently for longer periods of time during the remainder of the AVENUE project in that area. Hence, AM and Copenhagen area PTA Movia agreed on introducing an AVENUE shuttle on the two shuttle project at Slagelse Hospital. Here the main learnings were aimed at on-demand driving and integrations with public transport PTA Movia, their client systems, etc.

The Slagelse site was an interesting case, as the distances between the departments in the hospital are too long for patients to walk between them and a shuttle moving between different departments and connecting parking lots would improve the mobility in the area.

### 2.4.3.1 Objectives

The goal for the on-demand service is (1) hospital staff can book trips for patients and visitors, and (2) patients and visitors can book their trip. Transportation between parking lots and other entrances makes good sense because of the large distances in the hospital area. The status of the trips booked is updated through the tool used by
hospital staff, hereby passengers can get info on when to expect pickup time. Safety stewards will greet passengers when the vehicle arrives at the pickup point. Without any direct input from the safety steward, the vehicle will begin its trip once the doors are closed.

The on-demand service initiated with one vehicle. The second vehicle was included in the on-demand service as soon as possible. The goal was to service both vehicles on demand as much as possible.

At this stage, there were some technical activities that need to be performed in order to prepare the service:

* Update Navya vehicle software to 6.1

* Integrate Holo system with Navya API

* Integrate Holo system with a dispatcher at Movia

* Movia to develop User Interface for booking

There will be a full focus on the technical integration and stability/performance of the service created, in order to gain the full learning experience in trying to service a robust on-demand service.

There will be less focus on the development of apps and screen content, hereby limiting the investigations into the whole automated minibus customer journey. This is in order to favour the technical development and achievement of back-end software—customer interfaces are owned by Movia.

This priority is possible because the user who is booking the trips will be hospital staff and passengers via the Movia interfaces. The passengers will receive the necessary info from the hospital staff and the interfaces. Furthermore, the safety operator still has to be present in the vehicles and will be utilised to give the needed information to the user.

The practical test process will look like this:

* Outline vehicle behaviour in all possible on-demand situations on Holo's test track in Copenhagen. SW version 6.1. Holo internally dispatches missions to vehicles.

* Outline vehicle and integration behaviour in all possible on-demand situations with missions received from Movia. Still on Holo's test track.

* Move to Slagelse and perform similar tests on the real route. Reach a satisfactory level of performance before servicing passengers.

### 2.4.3.2 Deployment

The shuttle was driving on a 770-m-long stretch on Fælledvej at Slagelse Hospital. Besides driving on Fællesvej, the shuttle was driving in five parking areas, with multiple stops, to turn the shuttle and re-enter the stretch of Fælledvej. The route and the stops can be seen below. Besides the stops placed in the parking areas, the shuttle also stopped at the western part of Fælledvej, in both directions (Fig. 2.15).
<figure><img src="image_25.png" /><figcaption>Fig. 2.15 Map showing the route at Slagelse</figcaption></figure>

<figure><img src="image_26.png" /><figcaption>Fig. 2.16 Map showing the route sections at Slagelse</figcaption></figure>
The shuttle was driving on sections of the road with different infrastructure set-
tings. These different sections are shown in the following picture and further
described below (Fig. 2.16).

Red Section

The red section is a 240-m stretch with parking spots alongside the road on the south side, parking booths between the two driving lanes, and a double-edged bicycle lane on the north side of the stretch. There is a sidewalk for pedestrians on both sides of the road and no facilities for scooters in the eastbound direction. Meaning, scooters and, to some extent, bicycles must use the road in the eastbound direction. The speed limit for the stretch is today 50 km/h, and the red section has a width of 6 m. On the red section, there are three road connections with an unconditional right of way for the road users on Fælledvej. The municipality of Slagelse has approved the speed limit to be decreased to 30 km/h during the hospital pilot project.

Green Section

The green section is a 300-m stretch with parking booths between the two driving lanes and a walking path on the west and south sides of the road, as shown in the picture below. There is no sidewalk on the north side of the stretch (meaning that it is assumed that pedestrians may walk on the roadway on the north side). On the green section, there are no implemented facilities for scooters or bicycles, meaning that they will drive on the roadway on the green section. The speed limit for the stretch is today 50 km/h, but it is assumed that the driving speed is lower because of two sharp curves on the stretch, with a small turning radius, which cannot be driven with 50 km/h. The green section has a width of 6 m. On the green section, there are five entry roads for parking facilities. From the parking facilities to Fælledvej drivers have an unconditional obligation to give way. There is a road connection in one of the sharp curves, where drivers have an unconditional obligation to give way to drivers on Fælledvej. The municipality of Slagelse has approved the speed limit to be decreased to 30 km/h during the Hospital Trials.

Blue Section

The blue section is a 230-m stretch with barriers separating the road and newly
implemented speed signs, recommending 20 km/h on the stretch. There are side-
walks for pedestrians on both sides of the stretch. There are approximately 35 m of
bicycle lanes on both sides by the exit from entrance 11. On the remaining part of
the stretch, the road is shared with bicycles and scooters. The driving lane has a
width of 3.25 m in both directions, and there are five cross sections with an obliga-
tion to give way for the traffic on Fælledvej. Slagelse municipality has approved
speed limits of 30 km/h during the Hospital Trials.
A regular Movia bus (line 902) operates on Fælledvej with 30-min intervals during weekdays. The line has two stops (for each direction) on the part of Fælledvej that the shuttles were driving on. At the main entrance of Slagelse Hospital, a patient bus of the same size as Movia's regular bus departed a couple of times during the day. The patient bus had a marked parking area in front of Slagelse Hospital that has been placed outside the self-driving shuttle's route. During entry and exit to and from Slagelse Hospital, the self-driving shuttle and the patient bus could lock. This required the safety driver to manually take over and give way for the patient bus.

## Parking Conditions

The area in which the automated minibus had been operating has a high density of parking areas. There are parking facilities in Fælledvej, where drivers dismount their cars directly onto the road. Further, there are marked parking booths on these parking facilities, which the automated minibus had to drive past. Besides parking

<figure><img src="image_27.png" /><figcaption>**Fig. 2.17** Photos showing parking conditions at Slagelse</figcaption></figure>
areas defined by regulations or signs, there was a high degree of parking outside of
these designated areas, as seen below. Based on this, it is uncertain how much effect
the parked cars outside of designated areas will have on the operation of the shuttle.
Unwanted stops and brakes may occur if parked cars are blocking the route of the
shuttle (Fig. 2.17).

Total distance and total passengers

<figure><img src="image_28.png" /><figcaption>**Fig. 2.18** Total number of passengers and distance driven in the Slagelse project</figcaption></figure>

Distance and passengers pr. month

<figure><img src="image_29.png" /><figcaption>**Fig. 2.19** Distribution of passengers and distance driven per month in the Slagelse project</figcaption></figure>
### 2.4.3.3 Achievements and Key Success Factors

#### Distance and Passengers

In total, 1659 passengers were transported and 4595 km driven on the Slagelse route. During the pilot, there were over 2117 h of operation (Figs. 2.18 and 2.19).

#### Automated Vs. Manual Driving

In regard to the navigation mode, 93.9% of overall driving on the route was driven in automated mode. The rest of 6.1% driven in manual mode was mostly due to technical issues. Driving to and from the garage is filtered out.

### 2.4.3.4 Recommendations

#### User Experience Learnings

##### Patients

Moving patients from A to B on a hospital site has proven to be a very good use case for the Navya vehicles, as patients often do not need high speeds but rely on the comfort and the ability to be moved. This means that even if the shuttle's top speed is 18 km/h, the patients still experience high value, as the alternative would be to walk or wait for local flex taxis, etc.

##### Relatives/Visitors

Being a relative at a hospital site is often associated with difficult parking conditions and lots of walking on the hospital sites. With the service provided in the AVENUE project, relatives and visitors have had the opportunity to park in large parking areas away from the hospital entrances but then being carried by the shuttle to the entrances. This means less congestion and car hassle at the entrances of the hospital, resulting in emergency vehicles having more space and less reckless parking from visitors.

##### Employees

As for the relatives and the visitors, the employees have used the shuttle service to get from larger parking areas to the entrances of the different departments—but also to accompany patients from one department to another—cutting off time from walking and waiting on flex taxis.
## Performance Learnings

### Low-Speed Environment

The Slagelse Hospital site has shown to be a very good fit for the deployment of the Navya vehicles. Being the site in Amobility's history with the highest automated uptime percentage, 93.9% of the planned operation has been delivered in automated mode. The environment at Slagelse Hospital is a low-speed (20–30 km/h) zone. Passengers, employees, and relatives visiting the hospital with cars drive slowly and are in general not in a hurry—meaning less dangerous overtaking and reckless driving around the shuttle.

### Low Complexity Environment

The roads on the Slagelse Hospital are public with low-speed zones. The roads are wide and have designated lanes for pedestrians, bicycles, and cars. This has provided a good environment and level of complexity for the deployment of the Navya vehicles. Historically Amobility has experienced many issues with bicycles sharing the roads with cars, resulting in many overtaking close to the vehicle causing severe and hard braking of the vehicle—a huge risk for the passengers inside the vehicle. Having this environment, more suited for the Navya vehicle, has had a huge impact on the high uptime in a positive direction.

### 2.4.4 Conclusions

The main conclusions that can be drawn from the Amobility efforts in the AVENUE project and the implementation of self-driving vehicles in Nordhavn, Copenhagen, Ørmoya, Oslo, and Slagelse, Copenhagen, are summarised in the following points.

* The approval process in Denmark has been a slow start where multiple stakeholders in the approval process had to learn the basics of self-driving vehicles, resulting in an approval process with inspirations from the railway approval systems—hence a documentation level out of the ordinary, seen from the perspective of the self-driving vehicles industry, where the technology is still at a low maturity level. A new approval is on average considered to take between 9 and 14 months in Denmark, and the adjustments and changes to an already given approval are rigid and require a new approval in most cases.

* The entire approval process in Denmark with multiple approvers is very expensive and requires a huge amount of work from Amobility, in terms of documentation, separate approvals, tests, risk assessments, and so forth.

* The approval process in Norway is structured in a very different way, allowing for a more dynamic and communicative approach. It is Amobility's experience that the Norwegian system is more agile and ready to adjust to the rapid develop-
ment of self-driving technologies. A new approval is on average considered to take between 3 and 5 months in Norway, and the adjustments and changes to an already given approval are seen as dynamic and innovative.

* Based on the experiences and knowledge that Amobility has gained so far, a recommendation for the Danish legal framework has been provided, with both direct and indirect changes that can be made to ease up the approval process.

* Amobility has suggested that when testing/driving in SAE Level 3 or lower, only approval from the DRSA, local police, and road owners should be necessary. Furthermore in projects with SAE Level 4-5 operation, AM recommends having either (1) approval from the appointed assessor, DRSA, police, and road owner(s) or (2) an approval by the Danish Road Directorate (taskforce), DRSA, police, and road owner(s). AM also suggests authorities to allow approvals for areas rather than single route approvals. Also, AM recommends that the Danish authorities target public funds more towards AV implementation. Ultimately AM recommends removing the political approval process entirely. For each project to have its own executive order completely diminishes the flexibility and innovation for existing and future pilot projects.

* Inspiration and know-how from the Norwegian approval system have been recommended to the Danish authorities as a comparison, aiming at showcasing the potential loss of innovative projects in Denmark if the approval system does not adapt to the innovative and rapid developments of self-driving technologies.

- From a technical perspective, Amobility has experienced that the technology and industry in general have developed at a slower pace than anticipated and the objectives of AVENUE have been difficult to meet.

- The Navya vehicles are not able to drive in SAE Level 4 as there are still many aspects of the safety-related features that need to mature before Amobility can take out the safety operator from the vehicles. As a part of the risk assessment in Denmark, there are certain jobs related to risks in traffic that the safety operator has to perform to verify and support the vehicle in public transport.

- During the project of AVENUE, Amobility deployed Navya vehicles at three different sites in both Norway and Copenhagen, Denmark. Experience has shown that the route in Slagelse offers the best circumstances for operating Navya vehicles with the right amount of complexity still ensuring the opportunity for high uptime. The maintenance cost is historically low in Slagelse, and major breakdowns and issues have not been experienced. At the same time, passengers at Slagelse Hospital have been very happy with the service of moving patients from department to department. This highlights why the use case in Slagelse is better than the other sites, as the patients do not demand speed but comfort and the ability to avoid walking. They are not in a hurry, as Amobility experienced passengers in Nordhavn to be due to the city centre position having both residents, employees, and tourists.

- To be able to reach higher speeds with the shuttles, the sensory systems have to be improved allowing for a larger safety net of lidars, etc. Given the
Amobility experience in Nordhavn and Ormøya, the average speed is still as low as 7–8 km/h. The top speed of the Navya vehicle is currently 18 km/h. It is Amobility’s opinion that the average speed is more important to increase than the speed of vehicles as the most important improvement for the operation is to move the passenger faster from A to B and not at the highest top speed. The objective is to try to raise the average speed to 14–16 km/h.

- Driving in snow and heavy rain in Oslo has turned out to be quite the challenge for the Navya shuttles. The big snowflakes are often confusing the lidars and tricking the system into thinking that there is an object that the vehicle has to avoid, hence usually a severe braking causing the passengers and safety operator to fall.

- The map of the vehicle (from the commissioning process) does not take into account that vegetation changes from season to season, even from the day the commissioning was executed to the day the operation begins. This has caused many problems for the vehicles that have performed many hard and severe braking. Often the branches are seen as obstacles in front of the vehicle in the safety zones. Amobility and the clients have spent both time and resources on keeping the vegetation to a minimum (preferably exactly as it was during the commissioning).

## 2.5 Lyon, France

### 2.5.1 Objectives

Launching a transport service with automated vehicles open to the public on an open road in the Confluence district in September 2016, Keolis Lyon is an early adapter of this research field. They are part of a local dynamic that is pushing the development of automated vehicles, with a political vision supported by the public transport operators (PTOs), as the means of the future to complete public transport offers. This first experiment allowed the creation of a public transport line serving a 1.6-km-long neighbourhood, thus connecting residents to a tramway line. This helped Keolis Lyon to lay the foundations for the use of automated vehicles as part of a strategy to bring passengers back to other modes of the urban transportation network (tramway, metro, high service level bus) making the public transport network more attractive.

The objective is to test a technology capable of revolutionising public transport, by offering PTOs a new way of developing their transport offer. Keolis Lyon is hoping that automated vehicles could modify the distribution of funding in public transport, which decides whether new public transport lines can be developed.

To understand the context of this project, it is important to acquire knowledge about the economic background of public transport. In Europe, mobility and the development of public transport in urban areas are two important issues. Therefore, the involvement of public authorities in urban transport is essential to ensure the
availability of a quality service at affordable prices. The management of a high-quality urban transport network represents an important public service mission (PSM) for the community, as it justifies the granting of subsidies to transport companies.

Indeed, most urban transport networks are not commercially viable. The public authorities must therefore cover all or at least part of the costs of investment in infrastructure and vehicles. Operators also receive subsidies for the operation of public transport, which vary in size from community to community. For example, in 2002, subsidies covered 45% of operational costs in Helsinki, 50% in Stockholm, 51% in Lyon, and 60% in Brussels. To meet the mobility needs of the urban population and the expansion of the areas served, the supply of urban transport has increased considerably over the last two decades. The French networks have become increasingly busy, and operating costs have increased very rapidly. However, the networks have not compensated for the increase in their operating costs with fare increases. Thus, from 2000 to 2015, the average rate of coverage of operating expenses by fare revenues has been steadily decreasing. It fell from 31% to 18% in networks with 50–100,000 inhabitants, from 33% to 18% in those without metro or tramway systems, and from 37% to 32% in those including them (Coppe & Gautier, 2004).

Reviewing these figures, it is important to point out that a significant part of the operating costs is represented by the drivers’ wage bill. This is how the idea that the creation of a new public transport line depends mainly on the expected volume of demand can be confirmed. Following this logic, it can be considered that if the operating costs of a new line are fixed according to its frequency (driving costs, investment, and maintenance of vehicles and infrastructure), the share of the territorial authority will decrease with the increase in frequency. Busy lines are therefore more profitable because they benefit from additional revenue. Thus, in an area with insufficient passenger density, the local authority will not be able to support the costs of creating and operating a new line.

In this paradigm, the automated vehicle could change the equation by considerably lowering operating costs, particularly by reducing the cost of labour, which is not negotiable for vehicles with drivers.

The experiment carried out in 2016 was therefore intended to enable a better assessment of the capacities of automated vehicles to accompany public transport networks in this transition.

## 2.5.2 Deployment

In 2018, after 2 years of operation of the experiment in the Confluence district, the opportunity to join the AVENUE consortium and to participate in the H2020 project led Keolis Lyon to look for a new and more ambitious field of experimentation. The Parc OL experimentation made it possible to work on several use cases.
<figure><img src="image_30.png" /><figcaption>Fig. 2.20 Parc OL route</figcaption></figure>

**Description:**

* 2.6 km round trip

* 3 crossroads with V2X

* 1 roundabout with V2X

* High frequentation open road

* 4 schools on the itinerary which cause high pedestrian traffic

**Goals:**

* Full integration on Public Transport

* Support for OL City development (hotel, restaurant, office)

* Fluid interaction between automated vehicles and urban traffic

* Social acceptance of automated vehicles

* Improve passenger's information

**Economic use case:** The Parc OL is the stadium of the professional football team which attracts about 40,000 spectators on event nights. The ambition is to create an economic activity around this stadium, in a project called “OL Vallée”. Therefore, there was a certain number of buildings to be built throughout the experiment which would completely change the way people travel in the area (leisure centre, restaurants, office buildings, medical centre and analysis laboratory, hotel). With a progressive increase in the number of passengers per day, the automated shuttles were seen as a way to offer a complementary public transport solution to accompany the economic development of this district. While it was clear that in the long term a mode of transport with more capacity would have to serve the OL Valley area, the automated shuttles were to provide a link during the increase in transport demand.

**Technological use case:** The first phase of experimentation was to connect the nearest tram stop (T3 Décines-Grand Large) with the Parc OL, by carrying out a route of approximately 2.6 km round trip. The route that the automated shuttles were to take allowed them to be integrated into a large flow of cars, passing crossroads and roundabouts for which the automated shuttle technology alone was insufficient. It was, therefore, necessary to equip four intersections with communicating traffic lights and to develop communications between the automated shuttles and the traffic light intersections. Thus, several insertion levels with or without priority for the automated shuttles were developed.

**Social acceptance use case:** The route of this experiment required the shuttles to cross a sensitive neighbourhood, in which road incivilities are regularly observed by the police. The question of the appropriation of these new technologies by the local population was therefore a central issue. This project was an opportunity to meet the inhabitants of the district to present the project, the technology used, its
operation, and its constraints. This promotion of the project was done through several communication channels and by going to meet the schools of the district. The objective of this phase was to allow residents to take ownership of the project and to integrate the automated shuttles into the urban landscape as a new everyday object (Fig. 2.20).

### 2.5.3 Achievements and Key Success Factors

Unfortunately, after an inauguration of the experiment on 18 November 2019, the crisis of COVID imposed the stop of this experimentation on 16 March 2020. New health regulations have forced French public transport operators to respect social

<figure><img src="image_31.png" /><figcaption>Fig. 2.21 Kilometres travelled/theoretical kilometres</figcaption></figure>

<table><caption>Table 2.2 Shuttle data</caption><thead><tr><th>Month</th><th>P108<br>% Auto</th><th>P108<br>Average speed (km/h)</th><th>P104<br>% Auto</th><th>P104<br>Average speed (km/h)</th></tr></thead><tbody><tr><td>Nov 2019 (starting from 15 Nov)</td><td>93%</td><td>9.6</td><td>95%</td><td>9.7</td></tr><tr><td>Dec 2019</td><td>91%</td><td>9.7</td><td>92%</td><td>9.8</td></tr><tr><td>Jan 2020</td><td>88%</td><td>9.9</td><td>89%</td><td>10.0</td></tr><tr><td>Feb 2020</td><td>85%</td><td>10.1</td><td>87%</td><td>10.1</td></tr><tr><td>Mar 2020</td><td>75%</td><td>8.9</td><td>93%</td><td>10.1</td></tr></tbody></table>
distancing in their vehicles. However, given the size of the automated shuttles, respecting these social distances was not possible. Although a resumption was allowed in September 2020, the context had evolved and no longer allowed for qualitative observations of this experiment. The number of passengers had dropped significantly on the whole network, with traffic of less than 70% of the normal attendance. The figures presented below are therefore only for the period before the COVID-19 crisis (Fig. 2.21 and Table 2.2).

Monitoring of the experiment:

* 4000 passengers

* 6400 km

* 1.13 passengers/journey made

Awareness among CT users (650 people from the panel to link with the social impact chapter):

* 46% are aware of the experiments in Lyon.

* 55% have a favourable opinion of automated vehicles.

* 33% would be ready to give up their car if a TAD service with automated vehicles was proposed.

Rate of completion of the service:

* 85% (theoretical kilometre to kilometre to be achieved by a shuttle when it is out of service and kilometre to be achieved during operational stops caused by external reasons).

* 65% if all theoretical kilometres are kept.

* Equipment reliability problem and known cause:

- Prototype vehicle

- (1800 km of untested operation + Transpolis tests where the limits of the shuttles were tested)

The average speed was provided by Navya. It represents the average of all operating speeds. The average speed is usually low because it includes slowdowns when approaching stops where passengers get on and off the vehicle, as well as all the slowdowns caused by events on the route (red lights, crossing times at junctions, awkward parking, etc.).

### 2.5.4 Future Development

While the question of the technical capabilities of automated vehicles seems central to the anticipated developments, it is necessary to put them in perspective with the needs of mobility services. For automated vehicles to be commercially successful in public transport, it is imperative that the service offered is relevant.
By integrating this reflection, it is easily understandable that the principle of a fixed line, with regular and reliable schedules, can be a relevant service. The regularity of the passages could facilitate the habitual travels of the users, as well as their confidence in this service. Nevertheless, this is only true when the frequency of passage of automated vehicles at the stops is very high. This allows the customer to remove the constraint of planning these trips. In the same way as a metro, we do not look at the time of arrival because we know that they run frequently and that the waiting time between two metros is always acceptable. The logic for a fixed line of automated shuttles is therefore the same. Even if this is feasible, it implies a constraint on the size of the vehicle fleet. To be able to guarantee a high-frequency operation, the transport operator will have to exponentially increase the size of their fleet with the increase in the size of the area to be served. This principle may therefore create a strain on investment requirements and operating costs. The increase in fleet size implies more vehicles but also more supervisors and intervention teams, which will still be needed in case of problems and disrupted situations.

In this paradigm, we could therefore deduce that the development of fixed public transport lines operated with automated shuttles is only relevant considering certain characteristics of the site, including size or certain constraints related to the types of routes available for automated shuttles (e.g. industrial site with a single road).

Based on these observations, we can therefore anticipate that the aggregation of automated shuttle technology and vehicle fleet management technologies to offer an on-demand transport service would offer an answer to several constraints.

### 2.5.4.1 The Constraints of Availability for Users

With an on-demand transport system, the constraints on the availability and regularity of automated shuttles are perceived differently from a fixed route. The automated shuttles will be available through a spontaneous reservation, and waiting times can be anticipated by the users. For example, users of conventional on-demand transport platforms (e.g. Uber) have learnt through use that certain times are to be preferred and others to be avoided to use the services offered.

The second option for the user is to book their journey in advance, giving them more freedom to choose the time they want to be picked up. With this proposal, the transport operator encourages the user to anticipate his trips, which subsequently facilitates the organisation of services and the dispatching of vehicles according to the time slot of the day. The more customers anticipate their journeys, the more efficient the transport operators can be in managing production.
### 2.5.4.2 Energy Constraints and Battery Capacity

In addition, on-demand transport helps to increase the ratio of passengers to kilo-
metres travelled, thus improving energy efficiency as the energy requirement on
the batteries is reduced. While creating a fixed route, the battery capacity is an
important factor for the dimensioning of the vehicle fleet. This is less important for
a fleet of automated shuttles in demand-responsive transport because the services
are composed of breaks during which the automated shuttles can recharge the
batteries.

### 2.5.4.3 Facilitate the Relationship with the User

As on-demand transport services are mostly based on a digital solution that inte-
grates a smartphone interface, the relationship with the user becomes easier.
Important top-down information such as the waiting time before the next trip, the
proposal to use another more efficient mode in a mobility-as-a-service (MaaS) envi-
ronment, the monitoring of use and the valorisation of loyalty, and the listening of
the customer can be managed via this interface. Thanks to this possibility, the trans-
port operator minimises their investment in infrastructure by creating passenger
information.

On the other hand, it is important to note that this vision of the service excludes
users without a smartphone, which is notably the case for the oldest and most iso-
lated population. It is therefore necessary to think about an accompanying service if
automated shuttles are to fulfil a public interest mission and thus be a fully fledged
mode of the public transport network. It is important to not exclude any population
from a new service.

### 2.5.4.4 Pricing Issue

In a regular and fixed service, the question of pricing arises. Even if a validator were
to be installed inside a shuttle, it would be difficult to automate the validation pro-
cess at this stage of technological development. This leaves the possibility of carry-
ing out control actions, in the same way as on the other vehicles of a public transport
network. However, when considering the development of automated vehicles, we
must consider the use cases that will minimise human intervention. In this context,
the use of the on-demand transport service supported by a smartphone interface
facilitates the act of payment of the service by the customer. It is easily imaginable
that the customer can register their credit or debit card or their transport card in the
application (depending on the fare choices of the PTO). In this case, only people
who have a good knowledge of the current fare system will be able to make a reser-
vation and use the service.

However, this is only part of the answer to the problem of fraud. It will also be
necessary to investigate the control of access to the automated shuttles by people
who take advantage of another person in a legal situation to get on board the auto-
mated shuttle.

The reasons given above are not intended to be exhaustive, but they do help to understand the interest in on-demand transport for automated vehicle technologies. It also allows us to observe that many questions arise with this type of service. This is why Keolis Lyon has committed to an evolution of the transport service initially proposed. The initial fixed line will have to increase its perimeter and offer a transport-on-demand service within a district that has been energised by the recent arrival of numerous centres generating daily passenger flows, with different motivations, and different travel times, not subject to the two peak full stops of the morning and evening.

## 2.6 Luxembourg

### 2.6.1 Pfaffenthal

Pfaffenthal is a small, urban living area located in Luxembourg City, the capital of Luxembourg. This urban area with around 1300 inhabitants is based in a valley between the historical centre of Luxembourg City and Kirchberg, the business district that is home to the European Investment Bank and the Court of Justice of the European Union.

Pfaffenthal is connected to the city centre via a public elevator and to Kirchberg via a funicular railway. Several bus connections are available in the surroundings of the elevator entrance at the city centre level. The funicular is part of a multimodal station that has been newly implemented in Pfaffenthal. Besides the funicular station, this multimodal station consists of a train station, a stop for several bus lines, as well as a bike sharing station. A tram connection and additional bus stops are situated on the Kirchberg side (of the topography). Over the course of 1 day, a variety of individuals traverse the Pfaffenthal Valley via a range of transportation methods. During the morning and evening rush hours, the majority of individuals commuting through Pfaffenthal do so by tram (Fig. 2.22).

The specific characteristics of the Pfaffenthal Valley make it the ideal use case scenario for the demonstration of a first and last-mile mobility service. Prior to the beginning of the project, no interconnectivity between the various modes of transportation arriving in the distinct regions of Pfaffenthal existed. Furthermore, Pfaffenthal offers a very diverse traffic situation with all kinds of different road users. It is a showcase to see how an automated vehicle can be integrated into such a diverse environment.
<figure><img src="image_32.png" /><figcaption>**Fig. 2.22** Route and automated minibuses stops</figcaption></figure>

### 2.6.1.1 Objectives

Until the beginning of the project, no transportation solution existed to overcome the distance between the residential area, the multimodal station, and the public elevator. The core objective is to fill this lack of transportation to connect the different means of transportation as well as the different areas of Luxembourg City with each other.
During the day, residents, employees, and a vast number of tourists are using the multimodal station in combination with the elevator to get to the different parts of Luxembourg City. The distance between the public elevator and the multimodal station is 500 m, and the distance between the residential area and the public elevator is 800 m. This corresponds to a 5–10-min walking distance. To connect the public elevator, the multimodal station, and the residential area with each other, the following route for the automated minibuses has been selected.

### 2.6.1.2 Deployment

The automated minibus shares the street with all kinds of different traffic users from cyclists and pedestrians to trucks, buses, and individual cars. Even with the speed limit of 30 km/h, the automated minibus encounters numerous overtaking maneuvers, which cause harsh breakings. Complex traffic situations around the automated minibuses cause rough driving behaviour. The shuttles need to identify other traffic and not only detect it. The automated minibuses speed of max. 18 km/h is slowing down traffic in Pfaffenthal, especially in the morning peak hours when the traffic is very dense, and the drivers seem to be very nervous and hectic. This is also the reason for the change of operational hours in 2019. It was decided to keep the automated minibuses out of the morning peak hours to prevent them from slowing down traffic. There is no need for an on-demand system because the shuttle only serves three stations. A safety operator has to be on board all the time by law (at all sites).

### 2.6.1.3 Achievements and Key Success Factors

With more than 25,000 passengers and over 9000 km driven in around 18 months, Pfaffenthal is the most successful site regarding the deployment of automated minibuses. The presence of the tourist destination Pfaffenthal, along with the prime location between the two elevators, was the key contributor to the success. The shuttle service did not require any promotional campaigns as it enabled users to travel distances that would normally be traversed on foot, thus providing them with the opportunity to reduce their transit times and to experience new technology.

### 2.6.1.4 Future Development

In the near future the city of Luxembourg is willing to restart the service. The restart on the existing route and with enough time to get all authorisations is a good way to get back to the service. Afterwards, the extension or implementation of other options and routes can be conducted, if required.

The vision for the trial in Pfaffenthal is to deploy more routes within Luxembourg City to establish a network and an on-demand service of automated minibuses that
are linked to each other, to the different parts of Luxembourg City, and to the public transport of the city. SLA can implement the on-demand option because Esch has shown that this service can be offered in Luxembourg. During the time of the AVENUE project, there were plans to expand the route. The objective of this route extension is to provide a transport service to:

* Hospice de Pfaffenthal (limit in parking space).

* Youth Hostel (limit in parking space).

* Servior, a retirement home (limit in parking space).

These three future partners do not have enough parking facilities and no nearby bus stops for passengers taking the Panorama Lift from the upper town. An emerging factor is providing accessibility to different users where transportation is scarce. The city of Luxembourg wanted to get a few months of experience with the original route before giving the authorisations for on-demand and door-to-door service. Due to COVID and the full stop of the service until the end of the project, the extension has never been realised but is still a possible option in the future.

## 2.6.2 Contern

Contern is a city located around 10 km southeast of Luxembourg City. An industrial zone with different companies has been implemented on its territory. A railway station and a stop for public buses are located on the border of the industrial zone. There are several other stops within the zone, but no direct connection exists from the train station to Campus Contern.

In this first phase, the automated minibus was operating between a real estate development company called “Campus Contern” with more than 300 employees and the train station.

### 2.6.2.1 Objectives

The aim was to dispatch individuals arriving via public transit to various firms in the industrial section and to offer a transport solution within this area. The trial in the industrial zone of Contern was chosen for its different environment compared to Pfaffenthal. Whereas Pfaffenthal has a busy inner-city traffic situation with various types of road users, the traffic in the industrial area of Contern is primarily composed of industrial vehicles, trucks, and cars, with fewer cyclists and pedestrians. The morning and afternoon hours in Pfaffenthal are marked by a considerable rise in individual car traffic because of people going to and coming from work. This phenomenon is far less accentuated in Contern (Fig. 2.23).

The vast majority of the company's employees was using their private car for their work commute as well as for transfers inside the zone. The shuttle is a good alternative because it closes the last-mile gap from the train station during the rush hour.
<figure><img src="image_33.png" /><figcaption>Fig. 2.23 Route Contern</figcaption></figure>

hour. Frequent traffic with heavy vehicles and increased commuter activity during peak hours is observed in the industrial area.

### 2.6.2.2 Deployment

The percentage of the automated mode with 50% is very low compared to other sites because it takes 30 min for the shuttle to get from Campus Contern to the train station and back. The train arrives every 30 min. To arrive in time, the safety operator switches into the manual mode and drives a little faster than in the automated mode. In Contern very few issues occurred during the operation that were caused by external factors. There is less traffic in the industrial zone of Contern compared to Pfaffenthal; thus the automated minibuses encountered less
overtaking. However, there were more heavy vehicles, which made the overtak-
ing more dangerous for the shuttle. The main issue encountered was vehicles
parked illegally on the automated minibus’s path. From the view of the other road
users, the automated shuttle is driving comparatively slow. This can result in less
acceptance of the automated minibuses as a new kind of road user and on the
other hand to use the shuttle itself, as long as it is driving slower than their own
cars. There is no need for an on-demand system because the shuttle only serves
two stations.

2.6.2.3 Achievements and Key Success Factors

There were over 850 passengers transported and 4000 km driven over 26 months. This is not as much as in Pfaffenthal, but there were a lot of breaks because of construction sites and COVID (including strict home office rules for a long time), and the people accepted the service and used it every time it was running. The length of the route and the slow speed of the shuttle prevented more people from using it.

As the automated minibus was operating exclusively for “Campus Contern”, the
total costs were paid by this company. On this extended route, the automated mini-
bus is passing several other companies and thus could connect more of them to the
railway station.

The continuation of the contract depends on other companies to join the
service and to lower the costs for the participants. It is very important to notice
that the operation of the automated minibuses is linked to very high costs—as
long as a safety operator is on board and not supervising several shuttles from
a central office. A lot of companies, cities, authorities, etc. are very interested
in such an innovative mobility solution, but they are not able to bear the respec-
tive costs.

Other than in Pfaffenthal, one does not simply walk into the shuttle. The people have to know that there is a service because it is only two times an hour at the stops. Campus Contern engaged in extensive internal communication, and on average there was at least one person per ride in the shuttle. With more companies joining, the amount of passengers can rise and provide a good alternative for taking the car.

2.6.2.4 Future Development

The industrial zone in Contern was seen as an appropriate use case for the establish-
ment of an on-demand mobility system. The demand varies with the time of the day.
During the peak hours in the morning and in the afternoon, the request for the auto-
mated minibuses is mainly done between the train station and the different compa-
nies. During non-peak hours, there is a shift in demand towards the interior of the
industrial area between various businesses and locations of interest, such as
restaurants.

It was hypothesised that the routes could be extended to the other side of the industrial area, as well as additional stops being added in front of companies that expressed a desire to use the service. Due to the stop of the service during COVID and the slow return of the employees from the home office, there were too few passengers to justify the (expensive) extension of the existing service. Nevertheless, other companies are still interested.

The vision for Contern is to establish a system of automated vehicles connected to the bus network and other shared transport modes like carsharing, establish the on-demand system, and implement the shuttles into the public transport information system. Like this, it is possible to synchronise the shuttle with the train in time, even in case of delays. Numerous shuttles could be available for the different parts of the industrial zone, which can be ordered on demand. This will facilitate the last mile of travel between public transportation stops and the workers' final destinations.

### 2.6.3 Esch-Sur-Alzette

Esch-sur-Alzette with 35,000 inhabitants from more than 120 nationalities is the second most populated town in Luxembourg and is located on the border to France in the south of the country around 17 km away from the capital Luxembourg City. The introduction of a shuttle service to the longest shopping street in the country could facilitate the revitalisation of the area through improved mobility. The shuttle ends on one side near a bus stop, while at the other end, there is no public transport. In this way, the shuttle closes the gap between the public transport stop and the inner city.

#### 2.6.3.1 Objectives

In September 2021 the service started in the main pedestrian/shopping street. In this part of the city, no public transport can be provided, but the mobility of the people can be optimised, especially the elderly, wheelchairs, strollers, or people with heavy shopping bags by providing the shuttle service. On rainy days the shuttle service can get people dry from one spot of the shopping street to another.

In September 2022, the planned on-demand service was launched, extending service hours from 11:00 am to 9:00 pm. The shops are closed after 6:00 pm, but the cafés and restaurants are still open. The presence of a shuttle during the evening hours in the more quiet street can provide a sense of security to pedestrians due to its illumination and motion.

The long-term vision is an automated-based, door-to-door service in Esch-sur-Alzette. The objective is to start first trials of an automated minibus with dynamic
<figure><img src="image_34.png" /><figcaption>Fig. 2.24 Route Esch</figcaption></figure>

routing in a geographically defined area, without fixed bus lines or predefined
timetables.

2.6.3.2 Deployment

The shuttle is driving on a 1-km section of the street “Rue de l’Alzette” with several stops at the crossings. It is driving at around 5 km/h as it should not be a disturbing element in the street but merge with the pedestrians. Only pedestrians and bikes are allowed in the street. Before 11:00 am and after 6:00 pm, delivery traffic is allowed, too. The on-demand service started on 12 September 2022, extended the service hours to 9:00 pm, and added four virtual stops on the same route (Fig. 2.24).

In terms of the shuttles’ operating environment, Esch is very different to Pfaffenthal and Contern. The very dense and narrow shopping street is only used by pedestrians and sometimes by bikes and scooters. Some people want to test the “reflexes” of the shuttles’ systems, and others are not paying attention even if the automated minibus rings the bell. Occasionally, there were objects (e.g. chairs from restaurants or a fence of a long-term construction site) on the driving path of the automated minibus. Due to these circumstances, SLA was required to communicate the challenges for the service to restaurant owners or to the city of Esch. The testing and further development of the pedestrian mode resulted in less harsh braking.
Furthermore, the implementation of the on-demand service resulted in longer service hours and a demand-orientated service for the users.

### 2.6.3.3 Achievements and Key Success Factors

With around 12,000 passengers in 12 months, the site in Esch is nearly as successful as Pfaffenthal.

In the summer of 2022, the mobility service had to be paused for 2 weeks due to technical difficulties. After the break, the passenger numbers were as high as before. This underlines that the people got used to the shuttle service, as they use it despite a longer operational break.

The street is wide enough for one vehicle, but with a lot of pedestrians, bicycles, maintenance cars, events, and construction sites, it can be difficult for the shuttle to drive all the time in automated mode. Intensive communication with the city of Esch is necessary to solve these problems, and it is working out very well.

The ODS started on 12 September 2022, extended the service hours to 9:00 pm, and added four virtual stops to the six existing ones. An app is required to book the shuttle for the desired time. The user cannot see the stops in the app but the service area. The user can choose the pickup and drop-off location freely within the area but is guided to one of the ten stops. These stops are very close to each other, so the user does not need to walk more than 1 min. Although it is a slight restriction, it allows the user to flexibly book the automated minibus.

Similar to the operation in Pfaffenthal, the people see the shuttle running and can use it to shorten their walking route. Since the service hours are the same as the shops' opening hours, no additional advertisement is required.

### 2.6.3.4 Future Development

There was a long-term vision for an automated-based, door-to-door service in Esch-sur-Alzette, which should have covered the whole inner city. Due to COVID, there was a significant delay in the planned schedule. The normal shuttle service started one and a half years later than initially planned. Additionally, it was early obvious that for a useable service covering a whole city centre, much more shuttles are required. This requirement is going to be fulfilled within the ULTIMO project from 2023 on. Although this plan is desirable, the process of service implementation in Esch may have to be conducted with more steps.

The service should continue in 2023. It is also possible that the service hours will be extended. If people use the shuttle starting at 6:00 pm often and get used to it, it will show that the shuttle is part of their mobility and can maybe even drive until 10:00 pm—with or without the on-demand service. Another option is to add another street at the end of the existing route where a lot of restaurants are, enabling that the customers are closer to the shuttle service. In conclusion, the shuttle itself is not
only an additional mobility option but is also a contributing factor in revitalising the
city centre, making it safer, cleaner, and more liveable.

2.7 Lessons Learned

Automated vehicles for public transportation are seen as a promising solution to the
growing urban mobility challenges. Despite significant investments in improving
technology, the transition from a “technology offer” to a “service offer” remains
unclear, and until today there has not been a real commercial deployment of auto-
mated vehicles in urban mobility. This is primarily due to the lack of experience on
how to develop viable and sustainable business models, which, in turn, results from
a lack of real large scale.

The several real-life deployments of the automated vehicles in different public transportation set-ups of the AVENUE project allowed us to identify the vast majority of issues and to imagine and implement solutions. In this chapter, we have described the AVENUE site deployments, and we have outlined the key elements that require further study and development. The key lessons learned are that, on one side, long-term planning needs to be established by public transportation operators (PTOs) and public transportation authorities (PTAs) over a decade, with the creation and implementation of new policies, infrastructures, and passenger services. On the other side, new open standards that support the interoperability of automated technologies must be developed and adopted. This will foster competition among technology players, including vehicle manufacturers, fleet management and orchestration providers, V2X technology developers, and more, thereby creating a sustainable ecosystem.

While the issues discussed in this chapter are significant, they are not the only
challenges. Additional hurdles include retraining maintenance personnel from
mechanical to IT and electronics expertise and addressing the transition of existing
drivers to new roles, such as intervention teams or back-office operators.
Furthermore, deploying automated vehicles with on-demand, door-to-door public
transportation services may face opposition from other transportation actors, such
as taxi services, who might view this innovation as a direct threat to their business.
Additionally, the certification of automated drivers remains an open question since
public transportation vehicles are currently certified for their mechanical capabili-
ties, and human drivers are “certified” for their driving skills. Approaching these
issues, along with any unforeseen challenges that arise during actual very large
scale service deployment, will require a concentrated effort from PTOs, PTAs, leg-
islators, and service users to develop workable solutions.

Ultimately, this is the objective of the European project ULTIMO, initiated in
October 2022 based on the learnings of the AVENUE and other European projects.
ULTIMO aims to lay the foundation for a large-scale deployment and develop the
necessary standards, policies, and road maps to create a viable, user-oriented, and
economically sustainable public transportation service using automated vehicles.
We expect that large-scale deployments in Europe and around the world will start appearing from 2026 and on, with the parallel introduction to the market of new types of highly performant SAE L4 vehicles.

**Acknowledgements** This project has received funding by the European Union's Horizon 2020 research and innovation program under grant agreement No. 769033.

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**Open Access** This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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**Chapter 3**

# Automated Minibuses: State of the Art and Improvements Through AVENUE

Pierre Chehwan

**Abstract** This chapter looks at advances in automated vehicle (AV) technology, focusing on the central role of AVs in revolutionizing public transport as part of the AVENUE project. It traces the path of AV development, highlighting NAVYA's pioneering contributions and the significant technological advances that have been achieved. The chapter describes the evolution of NAVYA technology and the disruption of the transport ecosystem during the ambitious goals of the AVENUE project. The project's mission to integrate automated minibuses into the public transport ecosystem is critically analyzed, highlighting operational innovations, the integration of on-demand door-to-door services, and the comprehensive management of an AV ecosystem. Technology, legal, and regulatory challenges and continuous improvements in AV software and hardware are discussed, emphasizing NAVYA's influential position in the European AV landscape. The chapter concludes with a reflection on the implications of the AVENUE project for future technological directions, emphasizing the wider implications for automated mobility and the need to navigate the complex interplay of innovation, regulation, and public acceptance.

**3.1 Introduction**

The idea of AVENUE project was triggered in 2017 when the technology companies started to challenge the car original equipment manufacturers (OEMs) on their ground stating that the software will take control of the vehicles and change the way cars will be driven in the future. While car OEMs were working in a progressive V cycle way adding features one after the other to their cars, software companies

NAVYA assets were taken over on April 23, 2023, by Gama (Gaussin Macnica Mobility joint venture, 51% owned by Gaussin and 49% by Macnica)

P. Chehwan (✉)

NAVYA Group, Courbevoie, France

beti - Experts Mobilité Automatisée, Saint-Donat-sur-l'Herbasse, France
disrupted this process with an out of the box thinking, where they considered cars
as connected computers on wheel driven by a software that is developed in fast
delivery AGILE process with AI model.

NAVYA (founded in 2014 from a group, Induct, which had launched a driverless electric minibus called Navia for Navigation par Intelligence Artificielle) took part of this disruption, as a pioneer by introducing the first commercial automated shuttle in 2015. The Autonom® Shuttle was built without a steering wheel nor pedals to be SAE Level 4 by design. The strategy aimed to introduce shared and public automated shuttles in urban areas, thereby reducing reliance on cars for short trips, alleviating traffic congestion, freeing up parking spaces, and reducing greenhouse gas emissions. NAVYA became the reference in this automated public transport shuttle area showcasing its technology around the world, for public transport operators, advanced cities, universities and research around the world. At that time NAVYA was deploying the Autonom® Shuttle in geofenced areas with 1–2 vehicles per site with round trips of 1–2 km.

The AVENUE concept was to raise the challenge and to integrate the automated minibus in the public transport systems. By putting the services in the heart of the project, the technology should solve more operational situations, go into mixed traffic, connect to public transport infrastructure, bring new adapted and disruptive mobility services, and deliver smooth and seamless riding like any other public transport service. Among all, the on-demand (1) combined with a door-to-door (2) approach in public transport where a passenger can use a mobile application to order a ride and be hailed was the major disruption.

To raise this challenge, NAVYA developed advanced technologies for its auto-
mated driving system (ADS) and established open-standard connectivity from the
shuttles to external IT systems, enhancing operational excellence for these new
mobility services.

This chapter will detail these elements and what was done to make the AVENUE
project one of the major automated vehicle (AV) projects in Europe for the European
Commission. AVENUE paved the way for competition and changed the perspective
on automated driving, not only in terms of technology but also in the realms of ser-
vices and even in the legal and regulatory framework.

## 3.2 Automated Driving Context before Starting AVENUE

Before the AVENUE project in 2018, the hype on automated driving was predicting the arrival of driverless cars by 2022.

Technology leaders like Google, with a dedicated subsidiary WAYMO, planned huge investments and forecast that robotaxis will cover major cities around the world in 2022 with at least 3000 taxis per major city. Uber was stating that they will leverage their margin by reducing the cost of human drivers, and they started investing billions in the technology. Lyft, Apple, and many other tech giants jumped in the competition pushing car leaders to react and create dedicated departments for advanced driver assistance systems (ADAS) and autonomous driving system (ADS). All the ecosystem was looking to the future with the robotaxi point of view.
Although NAVYA was working on robotaxi vision following the trend, the core business was to focus on L4 automated shuttles for shared and public transport. The idea was to bring as quick as possible these shuttles on the market by managing the risk one after the other. This was also driven by the lack of investment. As you aim for higher performance, you will require a greater financial investment, potentially accelerating your go-to market timeline by several years. NAVYA's practical approach was to begin implementing automated driving in restricted geofenced areas, whether private or public, with limited features, low speeds, and minimal interactions with other road users. This strategy aimed to minimize safety risks, reduce costs, and address issues one by one. Once you begin, you can gradually scale up to higher performance, increase interactions, and add features incrementally. This incremental approach to the operational design domain (ODD) would enable AV shuttles to enter the market quickly, albeit with limited capabilities, while continuously building data and knowledge to help the technology learn, mature, and advance. This would allow NAVYA to start selling and engaging investments.

With the AVENUE project, the idea was to put in place several shuttles on open roads of several cities in Europe, connect them to the public transport network, and create new mobility services. One of the major concepts of AVENUE was to demonstrate a door-to-door on-demand service covering a large geofenced area with public and shared transport, rather than just having fixed bus stops and shuttles driving in a round trip. The vehicle can pick you up from where you are and drop you to where you want to go, and the same time it hails other passengers on the road as a normal public transport. It is a mix between taxi and public transport. The difference with a robotaxi is that a 15-passenger vehicle will pick up additional passengers along the route, even if their destinations differ. However, both pickups and drop-offs must be within the shuttle's range (ride pooling).

Such a challenge needs to manage the whole AV system and ecosystem and not only the automated driving technology of the vehicle. It needs technologies to drive the vehicle, technologies to assist and secure the passengers, and technologies to receive and manage missions to a fleet vehicle. All this should be done safely with respect to the legal framework in place.

From 2018 to 2022, within the 4 years of AVENUE project, high technological and operational investment was made to develop such technologies and to reach the target fixed by AVENUE. To better understand the technological and operational leap done, we need to put the project in the technological and economical context of 2018 to allow a clear vision. Then we will draw the technological advancements made during AVENUE project. We will finish by a projection action triggered during AVENUE and will build the technological long tale to show market needs.

### 3.2.1 Market Projection

Before 2018, automated driving was at the top of the hype cycle for emerging technologies published by Panetta (2017). All major players and OEMs were projecting to have a prominent market in the coming years. The scale of the market projections was extreme, exceeding $60 billion by 2030 (Frost & Sullivan, 2018).