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2 articles

Deriving Knowledge from E-Scooter Riders’ Feedback at Pilot Study Stage: Case for a City in Ontario, Canada

Seun Daniel Oluwajana, Olubunmi Philip Oluwajana, Temitope Elizabeth Oguntelure, Crystal Mingyue Wang, Soha Saiyed

Transportation Development Research · 12-25 · 10.55121/tdr.v2i2.301

This paper examines the sentiments and opinions of e-scooter riders in Windsor, Ontario, highlighting key issues and concerns they have expressed. It involved text mining of feedback collected over a six-month pilot program (May to October 2021) using dictionary-based analysis. Analysis of monthly word frequencies in rider feedb

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AI-Based Train Localization Using Railway Infrastructure Object Detection

Vladimir A. Fedorov

Transportation Development Research · 1-11 · 10.55121/tdr.v2i2.379

This paper presents an Artificial Intelligence (AI)-based approach to train localization through the detection of railway infrastructure objects using convolutional neural networks. The proposed system identifies key visual landmarks such as traffic lights, level crossings, tunnels, bridges, and passenger platforms directly from

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