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Innovation in ecosystem business models : An application to MaaS and Autonomous vehicles in urban mobility system

Rodrigo Gandia

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Rodrigo Gandia. Innovation in ecosystem business models : An application to MaaS and Autonomous vehicles in urban mobility system. Economics and Finance. Université Paris-Saclay; University of Lavras, UFLA (Brésil), 2020. English. ꢀNNT : 2020UPASC018ꢀ. ꢀtel-02895349ꢀ

HAL Id: tel-02895349 https://tel.archives-ouvertes.fr/tel-02895349

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Innovation in Ecosystem Business
Models: An Application to MaaS and Autonomous Vehicles in
Urban Mobility System

Thèse de doctorat de l'université Paris-Saclay

École doctorale n° 573 Interfaces : approches interdisciplinaires, fondements, applications et innovation (Interfaces)

Spécialité de doctorat : Ingénierie des systèmes complexes

Unité de recherche : Université Paris-Saclay, CentraleSupélec,
Laboratoire Genie Industriel, 91190, Gif-sur-Yvette, France.
Référent : CentraleSupélec

Thèse présentée et soutenue à Lavras, le 23 avril 2020, par

Rodrigo Marçal GANDIA

Composition du Jury

Jakob PUCHINGER

  • Président
  • Professeur, U. Paris Saclay, Chaire

Anthropolis (IRT Systemix-LGI CS)

Gilmar MASIERO

Professeur, Université de São Paulo

Marcio PIMENTA

Rapporteur

  • Rapporteur
  • Professeur, Université Fédérale de

Uberlândia

André GRÜTZMANN

Professeur, Université Fédérale de Lavras
Examinateur Directrice de thèse Directeur de thèse

Isabelle NICOLAI

Professeur, CentraleSupélec

Joel SUGANO

Professeur, Université Fédérale de Lavras

École doctorale n°573 Interfaces

Approches interdisciplinaires, fondements, applications et innovation (Interfaces)

Titre : Innovation dans les Modèles D’affaires D’écosystèmes : Une Application au MaaS et à L’intégration

des Véhicules Autonomes dans un Système de Mobilité Urbaine. Mots clés : Mobilité comme Service ; Véhicules Autonomes ; Mobilité Urbaine. Résumé : Le concept de mobilité comme service Nous avons constaté que pour prendre une place (MaaS) s’est généralisé dans les pays occidentaux et durable dans le système de mobilité urbaine, le est devenu une option de marché concrète, présen- MaaS doit être considéré comme un modèle d’aftant une offre de système de transport basée non faires modulaire et adaptable, applicable à tous les plus sur la propriété mais basée sur l'usage. L’utilisa- contextes socio-politiques, réglementaires, enviteur est ainsi au centre des questions de mobilité ur- ronnementaux et économiques. Pour cela, le baine, de sorte que les consommateurs doivent être modèle d’affaires de cet écosystème innovant doit ouverts à l'adoption de nouvelles technologies, telles tenir compte de l'acceptation des consommateurs, que les véhicules autonomes. Cette thèse vise à d’une coordination des multiples acteurs constituanalyser le concept de MaaS pour identifier les con- ant la chaine de valeur au sein d’un MaaS et des ditions de sa mise en œuvre et de sa diffusion dans systèmes de transport existant avec leur dé-

  • la mobilité urbaine de demain.
  • veloppement d’innovations technologiques (véhic-

ule autonome).

Title : Innovation in Ecosystem Business Models: An Application to MaaS and Autonomous Vehicles in Ur-

ban Mobility System. Keywords : Mobility as a Service ; Autonomous Vehicles ; Urban Mobility. Abstract : The concept of Mobility as a Service We found that to take a sustainable place in the ur(MaaS) has become widespread in Western countries ban mobility system, MaaS must be considered as and has become a solid market option, presenting a a modular and adaptable business model applicatransport system offer based no longer on ownership ble to all socio-political, regulatory, environmental, but use. This approach places the user at the heart of and economic contexts. To this end, the business urban mobility issues, so consumers must be open to model of this innovative ecosystem must take into adopting new technologies and services, such as au- account consumer acceptance, coordination of the tonomous vehicles. Based on our research, this Ph.D. multiple actors making up the value chain within a thesis aims to analyze the concept of MaaS in order MaaS and existing transport systems that are speto identify the conditions for its implementation and cific with their development of technological. diffusion in tomorrow's urban mobility.

Innovation in Ecosystem Business Models:

An Application to MaaS and Autonomous Vehicles in Urban Mobility System

Final deposit

Thesis National Number (NNT) : 2020UPASC018.
By: Gandia, Rodrigo 1,2
Supervised by: Sugano, Joel1; Nicolaï, Isabelle2

1: Universidade Federal de Lavras, Brazil ; 2: CentraleSupélec, Université Paris-Saclay, France

For my parents, my cornerstone, my everything, Marta and Lourenço.
To my brother, my friend, my inspiration, Rômulo.
To my love, my safe place, Andréia.

I Dedicate

Acknowledgements

It is a little bit funny to stop and write “acknowledgments” when in fact, thanking should be a daily habit of our journey... Unfortunately, we cannot always say thank you; sometimes, it passes… the rush of everyday life often tries to justify a thank you’ forgotten hug.

However, this is the time to externalize in words - at least to try - a bit of the gratitude’ feeling for each of the essential people to complete this journey named “doctorate”.

First and foremost, I thank God and my family, my father Albany Lourenço Godoy Gandia and my mother Marta Lúcia Perujo Marçal Gandia, examples of determination, inspiration, and life; and my brother Rômulo Marçal Gandia, who has always been in my side given support, encouragement, and plenty of laughs, love you all!

To my loving fiancée, Andréia Nunes Campos, for the belief, complicity, friendship, and patience, always being there for me.

To my advisors, professor Joel Yutaka Sugano and professor Isabelle Nicolaï, who have always been by my side, helping to make possible the moments when everything seemed impossible. To professor Arthur, responsible for the beginning of this incredible journey looking for solutions on urban mobility in Brazil and - why not - the world.

In the “UFLA world” many friends were present. To the professors and researchers of the Laborató- rio de Mobilidade Terrestre - LMT and to the Grupo de Estudos em Redes e Estratégia - GEREI, especially to the professors Daniel Rezende, Grützmann, Antonialli, Danilo Alves, Zambalde, and Luiz
Henrique. To Deila and the entire staff of the Programa de Pós-Graduação do DAE.

To my statistical friends, who helped me so much in my journey through the world of numbers, professor Izabela and Julia, thank you.

To my siblings by choice, Fabio and Bruna, without words to thank you for everything. To the great friends that the academy gave me - and became for life - Thais, Daniel Leite, Guilherme, Dudu,
Elisa, Cassiano, Ricardo, and Zé Willer. You all made this journey lighter.

To PH, who introduced me to the academic world back in the master's degree and, since then, more than a professor, I have a friend for life.

There are too many people to “remercie” in France too! To the professors and staff of École CentraleSupélec, in particular the members of Laboratoire Génie Industriel - LGI, especially professors
Bernard, Pascal, Jakob, Flore, and Danielle. To my friends of LGI Abood, Hichem, Haythem,
Tasneem, Selmen, Ouaïl, Islam, Bassem, Gustavo, Ikaro, Rongyan, and Hoang-Phuong (FonkTronk). Besides, of course, to the dears’ Delphine, Sylvie, Corrine, Carol, Mathieu, and Suzanne Thuron.

To the whole deuxième étage from Maison du Brésil and my friends Jeferson, Lucio, and Fillipo. To Fapemig and CAPEs for the scholarships granted to me for the accomplishment of this thesis.

Thank You | Muito Obrigado | Merci Beaucoup

“If I have seen further, it is by standing on the shoulders of Giants.”
Isaac Newton

GENERAL ABSTRACT

Given existing environmental pressures, the importance of traffic safety, and increasing regulatory constraints, mobility in cities is a significant concern for communities and citizens. In this context, technological innovations based on the widespread use of connected and shared vehicles, the emergence of Autonomous Vehicles (AVs), impose a reflection on the definition of sustainable urban mobility in the cities of the future. In addition to traditional transport, individual solutions are being developed (car sharing, soft mobility, autonomous shuttle, son on), which must be part of a global urban mobility system. In this sense, the concept of Mobility as a Service (MaaS) has gained ground and has become a concrete market option ensuring a transition from the existing property-based transport system to a use-based system. MaaS meets the transport needs of users through a single interface of a service provider by combining different modes of transport to provide a tailor-made mobility offer. This approach places the user at the center of mobility issues. The innovations involved in urban mobility are technological but also social and organizational. They are multi-actor and require coordination of each actor involved in the value chain to develop and disseminate these innovations. We are thus talking about innovation in a business ecosystem. To date, like any innovation, MaaS is a source of uncertainty for markets and surrounded by ambiguities. Moreover, MaaS deployments are mainly concentrated in developed countries with efficient public transport systems. However, we believe that MaaS is modular, adaptable, and applicable to a variety of realities (including a wide variety of public-private transport systems). Based on this research, this Ph.D. thesis aims to analyze the concept of MaaS in order to identify its implementation and acceptance within an urban mobility system. The results of our work indicate that the MaaS system can be based on the theoretical tripod of “Product-Service System (PSS),” "business ecosystem", and "eco-innovation." Also, we propose that MaaS can be thought of not only as a transport concept, phenomenon, or solution but also as a business model. Therefore, we propose that MaaS should be oriented towards the value proposition of users, within addition, a reflection based on the successful dissemination of MaaS in southern countries. In order to take its place in the urban mobility of the future, MaaS must be considered as a modular and adaptable economic model, applicable to all contexts (the efficiency - or inefficiency - of public transport must not be limited). To this end, the MaaS business model must be established as part of a systemic rethinking around the mobility ecosystem, and sustainability should not be considered as an intrinsic characteristic of a MaaS model. This innovative ecosystem business model is oriented towards consumer acceptance (user-centric innovation) and acceptance of existing transport modes that fit the specific context established. We will broaden our analysis of the conditions of development and diffusion of the autonomous vehicle within a MaaS at the socio-political level. In this sense, shared and connected AVs must be considered as one among several elements of the urban mobility ecosystem.

Keywords: Mobility as a Service; Autonomous Vehicles; Urban Mobility.

RÉSUMÉ GÉNÉRAL

Compte tenu des pressions environnementales existantes, de l'importance de la sécurité routière et des contraintes réglementaires croissantes, la mobilité dans les villes est une préoccupation majeure pour les collectivités et les citoyens. Dans ce contexte, les innovations technologiques basées sur l'utilisation généralisée de véhicules connectés et partagés, l'émergence des Véhicules Autonomes (VA) imposent une réflexion sur la définition de la mobilité urbaine durable dans les villes du futur. A coté des transports traditionnels se développe des solutions individuelles (autopartage, mobilité douce, navette autonome…) qui doivent s’insérer dans un système global de mobilité urbaine. En ce sens, le concept de Mobilité comme Service (MaaS) a gagné du terrain et est devenu une option de marché concrète assurant une transition du système de transport basé sur la propriété existant vers un système basé sur l'usage. MaaS répond aux besoins de transport des utilisateurs via une interface unique d'un fournisseur de services en combinant différents modes de transport pour proposer une offre de mobilité sur mesure. Cette approche place l'utilisateur au centre des questions liées à la mobilité. Les innovations engagées dans la mobilité urbaine sont technologiques mais aussi sociales et organisationnelles. Elles sont multi-acteurs et nécessitent une coordination de chaque acteur impliqué dans la chaine de valeur pour développer et diffuser ces innovations. Nous parlons ainsi d’innovation dans un écosystème d’affaires. A ce jour, comme toute innovation, le MaaS est source d’incertitudes pour les marchés et entouré d’ambiguïtés. De plus, les déploiements MaaS sont principalement concentrés dans les pays développés dotés de systèmes de transport public efficaces. Or, nous pensons que le MaaS est modulaire, adaptable et applicable à plusieurs réalités (dont des systèmes public-privé de transport très variés). Sur la base de ces recherches, cette thèse de doctorat vise à analyser le concept de MaaS pour identifier sa mise en œuvre et son acceptation au sein d’un système de mobilité urbaine. Les résultats de nos travaux indiquent que le concept de MaaS peut avoir comme fondement le trépied théorique de système produit-service (PSS), de « l'écosystème d’affaires » et de « l’éco-innovation ». Aussi, nous proposons que le MaaS puisse être pensé non seulement comme un concept, un phénomène ou une solution de transport, mais aussi comme un modèle d’affaires. Nous proposons alors que le MaaS soit orienté vers la proposition de valeur des utilisateurs, avec une réflexion appuyée sur les modalités de diffusion réussie du MaaS dans les pays du sud. Afin de prendre place dans la mobilité urbaine du futur, le MaaS doit être considéré comme un modèle économique modulaire et adaptable, applicable à tous les contextes (l'efficacité - ou l'inefficacité - des transports publics ne doit pas être limitative). Pour cela, le modèle commercial du MaaS doit être établi dans le cadre d’une réflexion systémique autour de l’écosystème mobilité, et la durabilité ne doit pas être considérée comme une caractéristique intrinsèque d'un modèle MaaS. Ce modèle économique d'écosystème innovant est orienté vers l'acceptation des consommateurs (innovation centrée-usagers) et des modes de transport existant qui correspondent au contexte spécifique établi. Nous élargirons notre analyse des conditions de développement et diffusion du véhicule autonome au sein d’un MaaS au niveau socio-politique. En ce sens, les VA partagés et connectés doivent être considérés comme un, parmi plusieurs éléments de l'écosystème de la mobilité urbaine.

Mots clés : Mobilité comme Service ; Véhicules Autonomes ; Mobilité Urbaine.

SUMMARY

FIRST PART ..............................................................................................................10 GENERAL INTRODUCTION.....................................................................................11

Research Contextualization and Motivation........................................................................11 Research Question and Objectives..........................................................................................12 Research Justifications..................................................................................................................13 Doctoral Thesis Structure............................................................................................................15

THEORETICAL FOUNDATIONS...............................................................................16

Mobility as a Service (MaaS) and Autonomous Vehicles................................................16
MaaS as a Disruptive Innovation and AVs as a...............................................................19 Disruptive Technology..............................................................................................................19
MaaS and AVs as a Product Service System (PSS) ............................................................23 Business Ecosystem.......................................................................................................................26 Consumer Behavior .......................................................................................................................32 Socio-Economic Perspective (Quintuple Helix Model)....................................................33 Theoretical Key Constructs.........................................................................................................34

METHODOLOGY ......................................................................................................37 PART TWO ...............................................................................................................39 ARTICLES..................................................................................................................40

ARTICLE 1: The business ecosystem of Mobility as a Service as a productservice system: An eco-innovation.........................................................................................40

ARTICLE 2: Autonomous vehicles: Scientometric and bibliometric review.............69 ARTICLE 3: Willingness to use Mobility as a Service in a developing .....................102 country.............................................................................................................................................102 ARTICLE 4: Casual carpooling as a strategy to implement Mobility as a Service systems in a developing country...........................................................................127

ARTICLE 5: The quintuple helix model and the future of mobility: The role of autonomous vehicles in a developing country................................................................158

PART THREE...........................................................................................................186 GENERAL CONSIDERATIONS ...............................................................................187 REFERENCES...........................................................................................................192

FIRST PART

“We can't solve problems by using the same kind of thinking we used when we created them.”
(Albert Einstein)

General Introduction

GENERAL INTRODUCTION

The present study addresses the issue of the Future of Urban Mobility in the context of Autonomous Vehicles and Mobility as a Service (MaaS) as an Innovative Ecosystemic Business Model. This introductory section is composed of the contextualization and motivation to the study, the research question, the objectives and the justifications of research. Finally, the doctoral thesis structure is discussed.

Research Contextualization and Motivation

Nowadays, around 54 percent of the world’s population is currently living in urban areas (Population Reference Bureau, 2016), with estimates of a 66 percent by 2050 when the world’s population expects to reach nine billion people (Fournier, 2017; EEA, 2013). In this sense, with the continuing global trend of urbanization and the growing demand for transportation, urban mobility poses significant challenges for the future.
To address these challenges is essential to look closely at the transportation sector, which, for most of its history, has remained mostly unchanged (Karlsson et al. 2016; Kamargianni and Matyas, 2016). It is predicted that the need for transportation will rise, resulting in a more significant increase in noise and air pollution, overloaded infrastructure, and congestion. Furthermore, contemporary transport practices are increasingly compromising the well-being of existing populations. Hence, there is a consensus among authors in the study-field that changes are needed (Mulley, 2017; Kamargianni et al., 2016).’
Among the many changes foreseen for the transport paradigm (Mulley, 2017), the arrival of new information and communication technologies (ICTs) increasingly promote the development of business concepts for more efficient use of vehicles, optimization of the transport network, better use of infrastructure and seamless commute (Kamargianni and Matyas, 2016).
Therefore, it is held that technology changes will make the future of mobility occur.
For Saddi (2018), three factors must be considered: 1) data collection, 2) autonomous (and electric) vehicles, and 3) multimodal transport. Also, Kuhnert & Stirmer (2017), states that the car of the future will be EASCY, that is: Electrified, Autonomous, Shared, Connected, and Yearly updated. For the relations established among these factors, we understand that they have to be analyzed together as part of a unique ecosystem. Thus, we believe that these new mobility trends are concomitant with the generalization of the service economy in which owning a car will no longer be seen as a priority for users, particularly for urban citizens.
In this sense, the concept of Mobility as a Service (MaaS) has been gaining ground in recent years and becoming a solid market option, by presenting a shift away from the existing ownership-based transport system toward an access-based one (Jittrapirom et al., 2017; Ambrosino et al. 2016; Mulley, 2017; Kamargianni et al., 2016).

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    Connected and Automated Vehicles: The Long and Winding Road Glenn N. Havinoviski, PE Iteris, Inc. © 2016 Iteris, Inc. All rights reserved. © 2016 Iteris, Inc. All rights reserved. Overview • Historical Perspective • Yes, It’s Really Happening • What are the Impacts? • Where We are Headed 2 © 2016 Iteris, Inc. All rights reserved. March 6, 2018 Historical Perspective 3 © 2016 Iteris, Inc. All rights reserved. March 6, 2018 Historical Perspective 4 © 2016 Iteris, Inc. All rights reserved. Timeline to Automation • 1939 – NY World’s Fair Demo by GM • 1945 – First Cruise Control • 1950-60s – RCA and GM test automated highways (guide by wire) • 1960s-80s – Assorted tests and vehicle sensor tests, led by Japan / Europe 5 © 2016 Iteris, Inc. All rights reserved. March 6, 2018 Automated Highway System Demo (1997) • ISTEA (1991) authorized National Automated Highway System Consortium • Focus on safety, efficiency, throughput • 7.6 mile corridor in San Diego (I-15) • On-vehicle sensors tracked lane guidance markers, supported adaptive But…… cruise control, collision avoidance Clear outcome was not defined! • Limited testing of automated bus 6 © 2016 Iteris, Inc. All rights reserved. Setting the stage (2000s) • Main USDOT focus “Connected Vehicles” (vehicle-to- infrastructure, vehicle-to-vehicle communications) using 5.9 GHz DSRC • Research initiatives addressed AV’s for military and urban use (not using V2V or V2I) o Carnegie-Mellon Navlab (1995) o DARPA Challenge (2004, 2005, 2007) KAT-5 (2005) o Team behind 2005 winner developed Google (now Waymo) Gray Insurance (Metairie, LA) & Car Tulane University • High-definition mapping, real-time updates a core element of AV’s (and a link to concept of CV’s) 7 © 2016 Iteris, Inc.
  • Study on Electrical Vehicle and Its Scope in Future

    Study on Electrical Vehicle and Its Scope in Future

    © 2018 JETIR February 2018, Volume 5, Issue 2 www.jetir.org (ISSN-2349-5162) Study on Electrical Vehicle and Its Scope in Future Divya Sharma, Department of Electrical Engineering Galgotias University, Yamuna Expressway Greater Noida, Uttar Pradesh ABSTRACT: The cars are based on programming in advanced time to give the individual driver relaxed driving. In the automobile industry, various opportunities are known, which makes a car automatic. Google, the largest network, has been working on self-driving cars since 2010 and yet an innovative adaptation to present a mechanised vehicle in a radically new model is continuing to be launched. The modelling, calibration and study of changes in city morphology in autonomous vehicles (AVs). Transport system are utilized to travel among the tangential houses as well as the intermediate work and necessitate transportation space. The main benefits of an autonomous vehicle areit can be operated day parking area for other uses, mitigatemetropolitanground. We also reduce the cost per kilometre of driving. Researchers are interested in the area of automotive automation, where most applications are found in different places. The technology in this research paper will help to understand the quick, present and future technologies used or used in the automotive field to render automotive automation. KEYWORDS: Autonomous Vehicle, Linriccan Wonder, Robotic Van, Self-Driving Car, Tesla corporation. INTRODUCTION Users all over the world are delighted with the introduction of an automated vehicle for the general
  • Towards Autonomous Vehicles Report # MATC-UI

    Towards Autonomous Vehicles Report # MATC-UI

    Report # MATC-UI: 117 Final Report 25-1121-0003-117 Towards Autonomous Vehicles ® Chris Schwarz, Ph.D. Associate Research Engineer National Advanced Driving Simulator University of Iowa Geb Thomas, Ph.D. Associate Professor Kory Nelson, B.S. Student Michael McCrary, B.S. Student Nicholas Schlarmann Student Matthew Powell Student 2013 A Coopertative Research Project sponsored by U.S. Department of Tranportation-Research, Innovation and Technology Innovation Administration The contents of this report reflect the views of the authors, who are responsible for the facts and the accuracy of the information presented herein. This document is disseminated under the sponsorship of the Department of Transportation University Transportation Centers Program, in the interest of information exchange. The U.S. Government assumes no liability for the contents or use thereof. Towards Autonomous Vehicles Chris Schwarz, Ph.D. Michael McCrary, B.S. Associate Research Engineer Student National Advanced Driving Simulator Electrical and Computer Engineering The University of Iowa The University of Iowa Geb Thomas, Ph.D. Nicholas Schlarmann Associate Professor Student Mechanical and Industrial Engineering Department of Mathematics The University of Iowa The University of Iowa Kory Nelson, B.S. Matthew Powell Student Student Mechanical and Industrial Engineering Electrical and Computer Engineering The University of Iowa The University of Iowa A Report on Research Sponsored by Mid-America Transportation Center University of Nebraska–Lincoln December 2013 Technical Report Documentation Page 1. Report No. 2. Government Accession No. 3. Recipient's Catalog No. 25-1121-0003-117 4. Title and Subtitle 5. Report Date Towards Autonomous Vehicles November 2013 6. Performing Organization Code 7. Author(s) 8.
  • Forecasting Americans' Long-Term Adoption of Connected And

    Forecasting Americans' Long-Term Adoption of Connected And

    FORECASTING AMERICANS’ LONG-TERM ADOPTION OF CONNECTED AND AUTONOMOUS VEHICLE TECHNOLOGIES 1 Prateek Bansal 2 Graduate Research Assistant 3 Department of Civil, Architectural and Environmental Engineering 4 The University of Texas at Austin 5 [email protected] 6 Phone: 512-293-1802 7 Kara M. Kockelman 8 (Corresponding Author) 9 E.P. Schoch Professor in Engineering 10 Department of Civil, Architectural and Environmental Engineering 11 The University of Texas at Austin 12 [email protected] 13 14 15 The following paper is a pre-print, the final publication can be found in 16 Transportation Research Part A: Policy and Practice, 95:49-63 (2017). 17 18 19 ABSTRACT 20 Automobile enterprises, researchers, and policymakers are interested in knowing the future of 21 connected and autonomous vehicles (CAVs). To this end, this study proposes a new simulation- 22 based framework to forecast Americans’ long-term (year 2015 to 2045) adoption levels of CAV 23 technologies under eight different scenarios based on: 5% and 10% annual drops in technology 24 prices; 0%, 5%, and 10% annual increments in Americans’ willingness to pay (WTP); and 25 changes in government regulations. This simulation was calibrated with the data obtained from a 26 survey of 2,167 Americans, in order to obtain their preferences for CAV technologies and their 27 household’s annual vehicle transaction decisions. 28 29 Results indicate that the average WTP (of respondents with a non-zero WTP) to add connectivity 30 and Level 3 and Level 4 automations are $110, $5,551, and $14,589, respectively. Long-term 31 fleet evolution suggests that the privately held light-duty vehicle fleet will have 24.8% Level 4 32 AV penetration by 2045 under an annual 5% price drop and constant WTP values.
  • Self-Driving Cars: a Survey Claudine Badue A,∗, Rânik Guidolini A, Raphael Vivacqua Carneiro A, Pedro Azevedo A, Vinicius B

    Self-Driving Cars: a Survey Claudine Badue A,∗, Rânik Guidolini A, Raphael Vivacqua Carneiro A, Pedro Azevedo A, Vinicius B

    Expert Systems With Applications 165 (2021) 113816 Contents lists available at ScienceDirect Expert Systems With Applications journal homepage: www.elsevier.com/locate/eswa Review Self-driving cars: A survey Claudine Badue a,<, Rânik Guidolini a, Raphael Vivacqua Carneiro a, Pedro Azevedo a, Vinicius B. Cardoso a, Avelino Forechi b, Luan Jesus a, Rodrigo Berriel a, Thiago M. Paixão c, Filipe Mutz c, Lucas de Paula Veronese a, Thiago Oliveira-Santos a, Alberto F. De Souza a a Departamento de Informática, Universidade Federal do Espírito Santo, Av. Fernando Ferrari 514, 29075-910, Goiabeiras, Vitória, Espírito Santo, Brazil b Coordenadoria de Engenharia Mecânica, Instituto Federal do Espírito Santo, Av. Morobá 248, 29192–733, Morobá, Aracruz, Espírito Santo, Brazil c Coordenadoria de Informática, Instituto Federal do Espírito Santo, ES-010 Km-6.5, 29173-087, Manguinhos, Serra, Espírito Santo, Brazil ARTICLEINFO ABSTRACT Keywords: We survey research on self-driving cars published in the literature focusing on autonomous cars developed Self-driving cars since the DARPA challenges, which are equipped with an autonomy system that can be categorized as SAE Robot localization level 3 or higher. The architecture of the autonomy system of self-driving cars is typically organized into Occupancy grid mapping the perception system and the decision-making system. The perception system is generally divided into many Road mapping subsystems responsible for tasks such as self-driving-car localization, static obstacles mapping, moving obstacles Moving objects detection Moving objects tracking detection and tracking, road mapping, traffic signalization detection and recognition, among others. The Traffic signalization detection decision-making system is commonly partitioned as well into many subsystems responsible for tasks such as Traffic signalization recognition route planning, path planning, behavior selection, motion planning, and control.