The AutoMat CVIM - A Scalable Data Model for Automotive Big Data Marketplaces

In the past years, connectivity has been introduced in automotive production series, enabling vehicles as highly mobile Internet of Things sensors and participants. The Horizon 2020 research project AutoMat addressed this scenario by building a vehicle big data marketplace in order to leverage and exploit crowd-sourced sensor data, a so far unexcavated treasure. As part of this project the Common Vehicle Information Model (CVIM) as harmonized data model has been developed. The CVIM allows a common understanding and generic representation, brand-independent throughout the whole data value and processing chain. The demonstrator consists of CVIM vehicle sensor data, which runs through the different components of the whole AutoMat vehicle big data processing pipeline. Finally, at the example of a traffic measurement service the data of a whole vehicle fleet is aggregated and evaluated

Mixed-reality Automotive Testing with SENSORIS

Highly automated and autonomous vehicles become more and more widespread changing the classical way of testing and validation. Traditionally, the automotive industry has pursued testing rather in real-world or in pure virtual simulation environments. As a new possibility, mixed-reality testing has also appeared enabling an efficient combination of real and simulated elements of testing. Furthermore, vehicles from different OEMs will have a common interface to communicate with a test system. The paper presents a mixed-reality test framework for visualizing perception sensor feeds real-time in the Unity 3D game engine. Thereby, the digital twin of the tested vehicle and its environment are realized in the simulation. The communication between the sensors of the tested vehicle and the central computer running the test is realized via the standard SENSORIS interface. The paper outlines the hardware and software requirements towards such a system in detail. To show the viability of the system a vehicle in the loop test has been carried out

A Mobile and Web Platform for Crowdsourcing OBD-II Vehicle Data

On-Board Diagnostics 2 (OBD-II) protocol allows monitoring vehicle status parameters. Analyzing them is highly useful for Intelligent Transportation Systems (ITS) research, applications and services. Unfortunately, large-scale OBD datasets are not publicly available due to the effort of producing them as well as due to competitiveness in the automotive sector. This paper proposes a framework to enable a worldwide crowdsourcing approach to the generation of OBD-II data, similarly to OpenStreetMap (OSM) for cartography. The proposal comprises: (i) an extension of the GPX data format for route logging, augmented with OBD-II parameters; (ii) a fork of an open source Android OBD-II data logger to store and upload route traces, and (iii) a Web platform extending the OSM codebase to support storage, search and editing of traces with embedded OBD data. A full platform prototype has been developed and early scalability tests have been carried out in various workloads to assess the sustainability of the proposal

Quantified vehicles: data, services, ecosystems

Advancing digitalization has shown the potential of so-called Quantified Vehicles for gathering valuable sensor data about the vehicle itself and its environment. Consequently, (vehicle) Data has become an important resource, which can pave the way to (Data-driven) Services. The (Data-driven Service) Ecosystem of actors that collaborate to ultimately generate services, has only shaped up in recent years. This cumulative dissertation summarizes the author's contributions and includes a synopsis as well as 14 peer-reviewed publications, which contribute to answer the three research questions.Die Digitalisierung hat das Potenzial für Quantified Vehicles aufgezeigt, um Sensordaten über das Fahrzeug selbst und seine Umgebung zu sammeln. Folglich sind (Fahrzeug-)Daten zu einer wichtigen Ressource der Automobilindustrie geworden, da sie auch (datengetriebene) Services ermöglichen. Es bilden sich Ökosysteme von Akteuren, die zusammenarbeiten, um letztlich Services zu generieren. Diese kumulative Dissertation fasst die Beiträge des Autors zusammen und enthält eine Synopsis sowie 14 begutachtete Veröffentlichungen, die zur Beantwortung der drei Forschungsfragen beitragen

A REVIEW ON INTERNET OF THINGS ARCHITECTURE FOR BIG DATA PROCESSING

The importance of big data implementations is increased due to large amount of gathered data via the online gates. The businesses and organizations would benefit from the big data analysis i.e. analyze the political, market, and social interests of the people. The Internet of Things (IoT) presents many facilities that support the big data transfer between various Internet objects. The integration between the big data and IoT offer a lot of implementations in the daily life like GPS, Satellites, and airplanes tracking. There are many challenges face the integration between big data transfer and IoT technology. The main challenges are the transfer architecture, transfer protocols, and the transfer security. The main aim of this paper is to review the useful architecture of IoT for the purpose of big data processing with the consideration of the various requirements such as the transfer protocol. This paper also reviews other important issues such as the security requirements and the multiple IoT applications. In addition, the future directions of the IoT-Big data are explained in this paper

The Digital Transformation of Automotive Businesses: THREE ARTEFACTS TO SUPPORT DIGITAL SERVICE PROVISION AND INNOVATION

Digitalisation and increasing competitive pressure drive original equipment manufacturers (OEMs) to switch their focus towards the provision of digital services and open-up towards increased collaboration and customer integration. This shift implies a significant transformational change from product to product-service providers, where OEMs realign themselves within strategic, business and procedural dimensions. Thus, OEMs must manage digital transformation (DT) processes in order to stay competitive and remain adaptable to changing customer demands. However, OEMs aspiring to become participants or leaders in their domain, struggle to initiate activities as there is a lack of applicable instruments that can guide and support them during this process. Compared to the practical importance of DT, empirical studies are not comprehensive. This study proposes three artefacts, validated within case companies that intend to support automotive OEMs in digital service provisioning. Artefact one, a layered conceptual model for a digital automotive ecosystem, was developed by means of 26 expert interviews. It can serve as a useful instrument for decision makers to strategically plan and outline digital ecosystems. Artefact two is a conceptual reference framework for automotive service systems. The artefact was developed based on an extensive literature review, and the mapping of the business model canvas to the service system domain. The artefact intends to assist OEMs in the efficient conception of digital services under consideration of relevant stakeholders and the necessary infrastructures. Finally, artefact three proposes a methodology by which to transform software readiness assessment processes to fit into the agile software development approach with consideration of the existing operational infrastructure. Overall, the findings contribute to the empirical body of knowledge about the digital transformation of manufacturing industries. The results suggest value creation for digital automotive services occurs in networks among interdependent stakeholders in which customers play an integral role during the services’ life-cycle. The findings further indicate the artefacts as being useful instruments, however, success is dependent on the integration and collaboration of all contributing departments.:Table of Contents Bibliographic Description II Acknowledgment III Table of Contents IV List of Figures VI List of Tables VII List of Abbreviations VIII 1 Introduction 1 1.1 Motivation and Problem Statement 1 1.2 Objective and Research Questions 6 1.3 Research Methodology 7 1.4 Contributions 10 1.5 Outline 12 2 Background 13 2.1 From Interdependent Value Creation to Digital Ecosystems 13 2.1.1 Digitalisation Drives Collaboration 13 2.1.2 Pursuing an Ecosystem Strategy 13 2.1.3 Research Gaps and Strategy Formulation Obstacles 20 2.2 From Products to Product-Service Solutions 22 2.2.1 Digital Service Fulfilment Requires Co-Creational Networks 22 2.2.2 Enhancing Business Models with Digital Services 28 2.2.3 Research Gaps and Service Conception Obstacles 30 2.3 From Linear Development to Continuous Innovation 32 2.3.1 Digital Innovation Demands Digital Transformation 32 2.3.2 Assessing Digital Products 36 2.3.3 Research Gaps and Implementation Obstacles 38 3 Artefact 1: Digital Automotive Ecosystems 41 3.1 Meta Data 41 3.2 Summary 42 3.3 Designing a Layered Conceptual Model of a Digital Ecosystem 45 4 Artefact 2: Conceptual Reference Framework 79 4.1 Meta Data 79 4.2 Summary 80 4.3 On the Move Towards Customer-Centric Automotive Business Models 83 5 Artefact 3: Agile Software Readiness Assessment Procedures 121 5.1 Meta Data 121 5.2 Meta Data 122 5.3 Summary 123 5.4 Adding Agility to Software Readiness Assessment Procedures 126 5.5 Continuous Software Readiness Assessments for Agile Development 147 6 Conclusion and Future Work 158 6.1 Contributions 158 6.1.1 Strategic Dimension: Artefact 1 158 6.1.2 Business Dimension: Artefact 2 159 6.1.3 Process Dimension: Artefact 3 161 6.1.4 Synthesis of Contributions 163 6.2 Implications 167 6.2.1 Scientific Implications 167 6.2.2 Managerial Implications 168 6.2.3 Intelligent Parking Service Example (ParkSpotHelp) 171 6.3 Concluding Remarks 174 6.3.1 Threats to Validity 174 6.3.2 Outlook and Future Research Recommendations 174 Appendix VII Bibliography XX Wissenschaftlicher Werdegang XXXVII Selbständigkeitserklärung XXXVII