Quantum Computing and Autonomous Electric Vehicles Integrated Technology Roadmapping for the Future Mobility Ecosystem
- 주제(키워드) Quantum Computing , Autonomous Electric Vehicles , Forecasting , Industry Ecosystem , Technology Roadmap
- 주제(DDC) 658
- 발행기관 아주대학교 일반대학원
- 지도교수 장병윤
- 발행년도 2026
- 학위수여년월 2026. 2
- 학위명 박사
- 학과 및 전공 일반대학원 경영학과
- 실제URI http://www.dcollection.net/handler/ajou/000000036070
- 본문언어 영어
- 저작권 아주대학교 논문은 저작권에 의해 보호받습니다.
초록/요약
This study examines the impacts of Quantum Computing (QC) and Autonomous Electric Vehicles (AEV) on the mobility ecosystem. It also outlines their future technological trajectories. Data was collected from international patents, academic research, and news articles. The dataset was analyzed using both quantitative and qualitative approaches. The quantitative analysis employed methods such as Frequency Analysis, Association Analysis, RNN (Recurrent Neural Networks)–LSTM (Long Short-Term Memory), LDA (Latent Dirichlet Allocation), Random Forest, Sentiment Analysis, Association Rule mining, K-means Clustering, Weak Signal Detection, and Logistic Regression. These methods were applied to identify technological and market trends and to forecast future directions. The qualitative analysis referenced technology roadmaps and policy documents issued by governments and corporations. It applied PEST (Political, Economic, Social, and Technology) analysis and strategic TRM (Technology Roadmap) approaches. These qualitative results demonstrate the potential for future development by outlining current technological limitations and strategic plans for advancement. The quantitative results further examined the development trajectories of technologies related to IoT (Internet of Things), big data-driven AI (Artificial Intelligence), quantum- based encryption, semiconductors, and mobility. By integrating quantitative and qualitative findings, the study provides forecasts for QC and AEV individually and proposes a Technology Roadmap for QC & AEV. This TRM systematically presented the future of the QC & AEV ecosystem across short-, mid-, and long-term horizons. By comprehensively analyzing related technologies, industrial infrastructure, and institutional support, this study delivers forecasts that are both realistic and applicable. QC and AEV industries are emphasized as key strategies for sustainable economic growth and strengthening national competitiveness. By providing an in-depth analysis of the transformative impacts of QC & AEV on the mobility ecosystem, the study provides market researchers and investors insights into critical technological trends and strategic investment frameworks. The study is expected to make a meaningful contribution to the development of future strategies for the mobility industry.
more목차
1. Introduction 1
2. Literature Review 4
2.1. Quantum Computing and Autonomous Electric Vehicle 4
2.2. Technology Forecasting 7
2.3. Technology Roadmap 10
2.4. Artificial Intelligence 16
3. Methodology 23
3.1. Research Design 23
3.2. Data Collection 29
3.3. Analysis Method 30
4. Analysis & Result 41
4.1. Trend in Quantum Computing and Autonomous Electric Vehicles 41
4.1.1. Market Trend 45
4.1.2. Technology Trend 73
4.1.3. The Status and Development of QC and AEV Industries 100
4.2. Forecasting Quantum Computing and Autonomous Electric Vehicles 104
4.2.1. Time Series Forecast and Predictive Clustering Analysis (RNN-LSTM) 104
4.2.2. Qualitative Trend Analysis (PEST) 115
4.2.3. Technology Roadmap in Corporate Level 120
4.2.4. Strategic Planning Technology Roadmap 124
4.2.5. Technology Roadmap 131
4.3. Future Outlook and Strategic Recommendations 142
5. Conclusions 144
References 148
Appendix 162
