Guest Editors
Prof. Dr. Juneyoung Park
Email: juneyoung@hanyang.ac.kr
Affiliation: Department of Transportation and Logistics Engineering, Department of Smart City Engineering, Hanyang University ERICA, Ansan (15588), Korea
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Research Interests: big data analytics in traffic safety, mixed-traffic environment simulation, advanced statistics, data mining applications
Prof. Dr. Jiho Yeo
Email: jihoyeo@gachon.ac.kr
Affiliation: Department of Smart City, Gachon University, City, Sungnam (13120), Korea
Homepage:
Research Interests: urban data analytics, transportation systems, mobility-on-demand, deep learning applications, smart cities, optimization algorithms, data-driven mobility research
Summary
Research using big data has been one of the most interesting ideas in various knowledge fields over the past decade. In particular, as the autonomous driving environment becomes full-fledged and multi-modal mobility exists on the road, the importance of research on mixed traffic driving environment based on real-time big data in transportation policy is increasing.
Therefore, cutting-edge transportation and mobility systems must be adapted to various road environments, and technologies that can process a large amount of diverse data must be considered to be utilized in various research and development. Furthermore, the development and application of big data threads utilizing data mining and computer-based learning technologies are becoming an important part of transportation and mobility systems, as the amount of data that can be collected and processed in various human activities.
In this context, this special issue aims to cover useful insights and application cases of advanced big data analytics methodologies in the fields of transportation, mobility, and autonomous vehicle environments. Application of new theories based on data and model-based methodologies and scientific inferences is also very welcome.
Topics of interest in this Special Issue include, but are not limited to::
- Data mining methodologies in transportation engineering research
- Multi-modal data fusion and applications
- AI concepts to enhance model performance and interpretability
- Algorithm development and applications in Vehicle Communication and Infrastructure Connectivity (V2X)
- Modeling and prediction of traffic conditions
- Mixed traffic (autonomous and human-driving vehicles) environment studies
- Transport dynamics and human behavior analysis
- Traffic safety and sustainable mobility
- Traffic simulation and driving simulator-based experiments
Keywords
smart transportation; big data mining; computer-based learning; autonomous vehicle; modeling and analytics
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