Conference Agenda

As autonomous driving system (ADS) continues to evolve, adopting Society of Automotive Engineers (SAE) levels 4~5 concepts, the advances of driving automation/autonomy technologies include to fulfill modern vehicle market demands. ADS solutions require large integrations of multiple engineering disciplines, such as mechanical engineering, electrical engineering, computer science, and cognitive science for ADS’ human-machine interactions. Many ADS developers are actively engaged in R&D in interdisciplinary technologies, such as the domains of perception systems, communication systems, automatic route/path planning, and autonomous driving safety systems. Despite the rapid progress in ADS, there are challenges in various ADS domains to allow its popular- and safe-adoptions on the road! Therefore, this research conducts a comprehensive patent analysis for ADS domains. We first define the domain ontology schema (based on ADS literatures and experts’ verifications). Then, advanced patent search strategies (combing semantic and keyword Boolean search methods) and macro- and micro-levels patent analyses are conducted to present global ADS patent landscape. Overall, this study integrates multiple ADS transdisciplinary knowledge domains and patent analytical methods with various viewpoints. The analytical result provides a viable technological direction(s) for global ADS R&D teams to accelerate high-level autonomous vehicle development. Finally, based on the patent data resources, we also zoom in the ADS patenting landscape of Taiwan’s automotive companies and their main suppliers in ITC components. This research provides evident-based recommendations on the innovation and patenting strategies to increase their competitiveness in the ADS solution.

The progress of Unmanned Aerial Vehicle (UAV) technology development has spanned in a wide spectrum of multidisciplinary science and engineering research, with respect to fundamental technologies and various application domains. The growing UAV demands have prompted global manufacturers into large-scale R&D efforts, resulting transformative impacts on intellectual property (IP) domains, subsequently escalating IP right (IPR) litigation (e.g., patent invalidation and infringement disputes). This trend reflects the competitive landscape of technological innovations, unveiling the legal and business challenges brought about by the pursuit of emerging technologies and their wide adoptions in society. To gain a deeper understanding of the development and transformation within the UAV domains, we employed methods including, literature/patent bibliometric analysis, and text mining to identify the knowledge ontology structure in this multidisciplinary field. It conducted comprehensive patent analyses (e.g., Technology Function Matrix, S-Curve). This study contributes to insightful examinations of patent holders and technological shifts within the UAV industry, supporting subsequent investigations into infringement cases involving major global UAV manufacturers and technology leaders, such as SZ DJI Technology and Autel. The study found that “target detection”, “controllers”, and “power systems” are the most sought-after sub-domains for research and development. The R&D trends and subsequent IPR issues indicate that societal transformation brings about changes in technology and industry structures, driving the evolution of intricate IPs and their industrial applications. Furthermore, to ensure IPR protection in the UAV industry, the study encompasses the global patent landscape, their legal dispute characteristics through case example, and IP/patenting strategies tailored toward the industry's current IP legal status.

This paper contributes to the discipline and measurement of transdisciplinary diffusion of innovations. We present our quantitative framework, fresh methods, and tools to measure and improve the diffusion of innovations. Innovation is frequently conflated with creativity as a synonym. They are entirely different concepts, though related by cause and effect. However, ideas remain as mental abstractions until they are made real as innovations. Innovations are novel and valuable ideas that have been transformed into man-made artifacts. However, innovations are neither automatically accepted nor widely adopted until they have diffused externally. By definition, diffusion means occupancy in more places and new spaces. The intensity, speed, scale, and scope of diffusion are determined by interacting demand-pull and supply-push sociotechnical factors that generate more positive economic, cultural, business, and functional benefits. Therefore, the diffusion of innovations occurs in transdisciplinary, dynamic, and complex sociotechnical contexts. Though the diffusion of innovations literature is perceptive, a theory that systematically integrates actionable methods, quantitative tools, and measurements remains conspicuously thin. We address this gap by extending the creative Quantitative Creativity Scores (QCS) framework with our Quantitative Innovation Scores (QIS) framework. QIS quantitatively measures the diffusion intensity into new spaces and places. As an example of our QIS framework, we evaluate the diffusion of 4GLTE and 5G telecom. QIS allows us to systematically identify and pursue creative strategies to establish faster and more effective acceptance of innovations. This, in turn, can strengthen the position of creative ideas in the market and industry.

The associated research work to be presented will address issues of modelling efficiency and therefore develop insights into the nature and principles of how ATM networks are constructed and how they can be more effectively designed, by using the operational performance nature that becomes evident through the modelling. In general, the paper will present how the simulation tool a) models the network, b) implements the optimisation technic, and c) validates the approach. Consequently, this provides the platform that is then used for two real ATM networks, in both China and Europe as two selected case studies, in order to provide results. At a more fundamental abstract level, such a network is a complex system, or system-of-systems that is transdisciplinary in nature. The inherent design parameters (1) are different and diverse in nature, including aircraft, airports, and routes; the operational parameters and variables (2) are multicriteria in nature, and diverse in units and type; and causes-of-change (3) are disruptive at a mono, inter, and trans-disciplinary levels to effect multi-attribute characteristics and performance metrics that attempt to capture the impact on the network system functioning as designed and planned. Consequently, the authors intend to use the application related to ATM network performance in order to understand at a more fundamental level elements of transdisciplinary science and transdisciplinary performance both in terms of optimal level (capacity) and robustness (performance reduction and recovery).