181 citations · 287 across the 11 of their papers we have counts for
11 papers
A Real-time Evaluation Framework for Pedestrian's Potential Risk at Non-Signalized Intersections Based on Predicted Post-Encroachment Time
Tengfeng Lin, Zhixiong Jin, Seongjin Choi +1
Addressing pedestrian safety at intersections is one of the paramount concerns in the field of transportation research, driven by the urgency of reducing traffic-related injuries a…
A Framework for Pedestrian Sub-classification and Arrival Time Prediction at Signalized Intersection Using Preprocessed Lidar Data
Tengfeng Lin, Zhixiong Jin, Seongjin Choi +1
The mortality rate for pedestrians using wheelchairs was 36% higher than the overall population pedestrian mortality rate. However, there is no data to clarify the pedestrians' cat…
Transformer-based Map Matching Model with Limited Ground-Truth Data using Transfer-Learning Approach
Zhixiong Jin, Jiwon Kim, Hwasoo Yeo +1
In many spatial trajectory-based applications, it is necessary to map raw trajectory data points onto road networks in digital maps, which is commonly referred to as a map-matching…
Analyzing vehicle pedestrian interactions combining data cube structure and predictive collision risk estimation model
Byeongjoon Noh, Hansaem Park, Hwasoo Yeo
Traffic accidents are a threat to human lives, particularly pedestrians causing premature deaths. Therefore, it is necessary to devise systems to prevent accidents in advance and r…
Automated Object Behavioral Feature Extraction for Potential Risk Analysis based on Video Sensor
Byeongjoon Noh, Dongho Ka, Wonjun Noh +1
Pedestrians are exposed to risk of death or serious injuries on roads, especially unsignalized crosswalks, for a variety of reasons. To date, an extensive variety of studies have r…
Vision based Pedestrian Potential Risk Analysis based on Automated Behavior Feature Extraction for Smart and Safe City
Byeongjoon Noh, Dongho Ka, David Lee +1
Despite recent advances in vehicle safety technologies, road traffic accidents still pose a severe threat to human lives and have become a leading cause of premature deaths. In par…
A novel method of predictive collision risk area estimation for proactive pedestrian accident prevention system in urban surveillance infrastructure
Byeongjoon Noh, Hwasoo Yeo
Road traffic accidents, especially vehicle pedestrian collisions in crosswalk, globally pose a severe threat to human lives and have become a leading cause of premature deaths. In…
A Real-Time Predictive Pedestrian Collision Warning Service for Cooperative Intelligent Transportation Systems Using 3D Pose Estimation
Ue-Hwan Kim, Dongho Ka, Hwasoo Yeo +1
Minimizing traffic accidents between vehicles and pedestrians is one of the primary research goals in intelligent transportation systems. To achieve the goal, pedestrian orientatio…
TrajGAIL: Generating Urban Vehicle Trajectories using Generative Adversarial Imitation Learning
Seongjin Choi, Jiwon Kim, Hwasoo Yeo
Recently, an abundant amount of urban vehicle trajectory data has been collected in road networks. Many studies have used machine learning algorithms to analyze patterns in vehicle…
Traffic Data Imputation using Deep Convolutional Neural Networks
Ouafa Benkraouda, Bilal Thonnam Thodi, Hwasoo Yeo +2
We propose a statistical learning-based traffic speed estimation method that uses sparse vehicle trajectory information. Using a convolutional encoder-decoder based architecture, w…
Attention-based Recurrent Neural Network for Urban Vehicle Trajectory Prediction
Seongjin Choi, Jiwon Kim, Hwasoo Yeo
With the increasing deployment of diverse positioning devices and location-based services, a huge amount of spatial and temporal information has been collected and accumulated as t…