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Tae-Jung Kwon

University of Alberta Engineering Research Chair

University of Alberta

Canada

Research Interests

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Dr. Tae-Jung Kwon is an Associate Professor at the University of Alberta, Canada. His research areas include artificial intelligence applications in winter road maintenance, traffic signal optimization, and the safety assessment of road weather information systems. Recent publications focus on leveraging explainable AI for road condition monitoring and the optimization of snowplow routes under real-world conditions.

Articles (16)

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2026

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2022

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2021

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2021

Collaborators (3)

Mingjian Wu

McGill University

CANADA

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Jaho Seo

Associate Professor

Ontario Tech University

CANADA

View details

Stephen Wong

Assistant Professor

University of Alberta

CANADA

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Tae-Jung Kwon

Research Interests

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About

Articles (16)

Safety impacts of road weather information systems: A state-wide cost effectiveness case study

Multimodal deep learning framework for traffic volume estimation: a city-scale case study in Edmonton, Alberta

Naturalistic Experiment for Surface Transportation: A Study of Snowplow Lighting under Winter Conditions

From Opacity to Clarity: Employing Explainable AI to Interpret CNN Predictions on Winter Road Conditions

Advancing winter road maintenance: An AI-driven web platform for real-time road condition monitoring and spatial analysis

Safety Impact Assessment of Optimal RWIS Networks—An Empirical Examination

Strategic Planning for Equitable RWIS Implementation: A Comprehensive Study Incorporating a Multi-variable Semivariogram Model

An Automatic Architecture Designing Approach of Convolutional Neural Networks for Road Surface Conditions Image Recognition: Tradeoff between Accuracy and Efficiency

An Interactive Traffic Signal Optimization Approach with Dynamic Variable Guidance Lane Control

Forecasting short-term road surface temperatures considering forecasting horizon and geographical attributes – an ANN-based approach

Investigating the Effect of Network Traffic Signal Timing Strategy with Dynamic Variable Guidance Lanes

Optimization of Snowplow Routes for Real-World Conditions

Spatial Mapping of Winter Road Surface Conditions via Hybrid Geostatistical Techniques

Exploring the associations between winter maintenance operations, weather variables, surface condition, and road safety: A path analysis approach

Lessons learned from the large-scale application of Driver Feedback Signs in an urban city

Optimizing snowplow routes using all-new perspectives: Road users and winter road maintenance operators

Collaborators (3)

Mingjian Wu

Jaho Seo

Stephen Wong

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