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News
News
Upcoming Events:
April 1-4, 2025 - Investigating Departure Time Flexibility in Urban Rail: The Impact of Travel Time, Departure Hours, and Trip Type - 11th International Conference on Railway Operations Modelling and Analysis, RailDresden 2025
April 1-4, 2025 - A Spatial-Based Method of Railway Track Gauge Measurement Based on Lidar Data - 11th International Conference on Railway Operations Modelling and Analysis, RailDresden 2025
April 1-4, 2025 - Railway Track Gauge Measurement Based on LiDAR and Camera - 11th International Conference on Railway Operations Modelling and Analysis, RailDresden 2025
Presentations:
Jan 6, 2025 - How Much Can Passengers Deviate from Their Commuting Schedule? A Flexibility Analysis of Passengers’ Departure Time - Convention Center, Hall A - 8:00AM - 9:45AM - 2025 TRB Annual Meeting
April 10, 2024 - Automated Sensing Data Analysis for Railway Track Gauge Monitoring and Defect Detection - Canadian & Cold Regions Rail Research Conference 2024
Research
Research
We tackle the challenge of managing and analyzing the large volumes of data generated by infrastructure systems using advanced tools such as SmartCard, GPR, LiDAR, high-speed cameras, and environmental sensors. The goal is to enhance data collection, storage, and integration techniques from diverse sources, ensuring more efficient demand management, infrastructure investments and supporting timely, informed decision-making.
Research Objectives
To develop multidimensional anomaly detection and pattern recognition algorithms for visble and invisible defects and early warning system.
To establish lightweight sensing algorithms such as computer vision algorithms to interpret image and video data, LiDar data for 3D reconstructing, IMU for dynamic motions, etc.
To develop short-term and long-term predictive maintenance models for dynamic maintenance schedules and risk mitigation plan.
Research Goals and Benefits
Develop intelligent transportation infrastructure monitoring and predictive maintenance algorithms
Enhance rail safety, efficiency, and infrastructure resilience.
Enable data-driven decision-making for cost-effective capital investments.
Promote climate resilience, and reliable multimodality transport in Rail, Road, Air, and more.
Team
Team
Yili (Kelly) Tang, Ph.D., P.Eng
Assistant Professor
Tanjian Wei
Ph.D.
Postdoctoral associate in Western
Suryakant Buchunde
PhD research student
Duha Abdallah
MESc research student
Zelin Zhang
MESc research student
Industrial partners
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