APPLYING COLLABORATIVE ONLINE ACTIVE LEARNING IN VEHICULAR NETWORKS FOR FUTURE CONNECTED AND AUTONOMOUS VEHICLES

The main objective of this thesis is to provide a framework for, and proof of concept of, collaborative online active learning in vehicular networks. Another objective is to advance the state of the art in simulation-based evaluation and validation of connected intelligent vehicle applications. With advancements in machine learning and artificial intelligence, connected autonomous vehicles (CAVs) have begun to migrate from laboratory development and testing conditions to driving on public roads. Their deployment in our environmental landscape offers potential for decreases in road accidents and traffic congestion, as well as improved mobility in overcrowded cities. Although common driving scenarios can be relatively easily solved with classic perception, path planning, and motion control methods, the remaining unsolved scenarios are corner cases in which traditional methods fail. These unsolved cases are the keys to deploying CAVs safely on the road, but they require an enormous amount of data collection and high-quality human annotation, which are very cost-ineffective considering the ever-changing real-world scenarios and highly diverse road/weather conditions. Additionally, evaluating and testing applications for CAVs in real testbeds are extremely expensive, as obvious failures like crashes tend to be rare events and can hardly be captured through predefined test scenarios. Therefore, realistic simulation tools with the benefit of lower cost as well as generating reproducible experiment results are needed to complement the real testbeds in validating applications for CAVs. Therefore, in this thesis, we address the challenges therein and establish the fundamentals of the collaborative online active learning framework in vehicular network for future connected and autonomous vehicles.Ph.D

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