5 citations · 8 across the 5 of their papers we have counts for
7 papers
Design, Field Evaluation, and Traffic Analysis of a Competitive Autonomous Driving Model in a Congested Environment
Daegyu Lee, Hyunki Seong, Seungil Han +3
Recently, numerous studies have investigated cooperative traffic systems using the communication among vehicle-to-everything (V2X). Unfortunately, when multiple autonomous vehicles…
Risk Analysis of Unmanned Aerial System Operations in Urban Airspace Considering Spatiotemporal Population Dynamics
Soohwan Oh, Yoonjin Yoon, Seyun Kim
This study aims to estimate the fatality risk of Unmanned Aerial System (UAS) operations from a population perspective using high-resolution de facto population data. In doing so,…
Effective Urban Region Representation Learning Using Heterogeneous Urban Graph Attention Network (HUGAT)
Namwoo Kim, Yoonjin Yoon
Revealing the hidden patterns shaping the urban environment is essential to understand its dynamics and to make cities smarter. Recent studies have demonstrated that learning the r…
Running the COVID-19 marathon: the behavioral adaptations in mobility and facemask over 27 weeks of pandemic in Seoul, South Korea
Jungwoo Cho, Yuyol Shin, Seyun Kim +4
Battle with COVID-19 turned out to be a marathon, not a sprint, and behavioral adjustments have been unavoidable to stay viable. In this paper, we employ a data-centric approach to…
Short-term Traffic Prediction with Deep Neural Networks: A Survey
Kyungeun Lee, Moonjung Eo, Euna Jung +2
In modern transportation systems, an enormous amount of traffic data is generated every day. This has led to rapid progress in short-term traffic prediction (STTP), in which deep l…
The effect of adaptive mobility policy to the spread of COVID-19 in urban environment: intervention analysis of Seoul, South Korea
Yoonjin Yoon, Soohwan Oh, Jungwoo Cho +4
Although severe mobility restrictions are recognized as the key enabler to contain COVID-19, there has been few scientific studies to validate such approach, especially in urban co…