"Transit Data 2026 Special Call: AI and Data Analytics for Efficient and Reliable Transit"

Call for Papers-"Transit Data 2026 Special Call: AI and Data Analytics for Efficient and Reliable Transit"

Journal: Journal of Public Transportation

Publisher: Elsevier

Submission Deadline: 30 Sep 2026

Key Requirements:

• TransitData 2026 scope alignment mandatory

• VSI article type selection CRITICAL during submission

• Practitioner case studies + real-world deployments prioritized

Overview

Automated transit data revolution enables AI-driven efficiency, reliability, equity through strategic planning, operations control, predictive maintenance. Translates GTFS/TIDES/TODS data into actionable insights addressing crowding, incidents, disruptions, service restoration. First issue showcasing practitioner-led deployments + methodological innovations (data fusion/OD inference/causal evaluation) for transit agencies worldwide.

Key Research Themes

AI/Analytics Applications:

• Strategic/service planning + performance measurement

• Operations control + incident management/restoration

Automated Data Methodologies:

• Demand/customer behavior modeling

• Data fusion + OD inference + causal evaluation

Equity & Market Insights:

• Fare policy optimization + equity analysis

• Disruption/special-event impact assessment

Technical & Organizational:

• GTFS/TIDES standards + visualization tools

• Data governance + organizational adoption challenges

Submission Instructions

1. Access EVISE Submission System
2. Register/Login (new users create EVISE account)
3. Submission opens 20 June 2026
4. CRITICAL: Select 'VSI: TransitData2026' Article Type dropdown
5. Format strictly per Author Guidelines
6. Originality: Manuscripts not under review elsewhere

Timeline: Opens 20 Jun 2026 | Closes 30 Sep 2026

Guest Editor Team

• Prof. Amer Shalaby, University of Toronto, Canada

• Assoc. Prof. Saeid Saidi, University of Calgary, Canada

• Senior Advisor Brendon Hemily, Transit Analytics Lab, University of Toronto, Canada

Why This Issue Matters

Transit agencies lose $50B annually to inefficiencies addressable by AI data analytics. 20% citation advantage accelerates practitioner adoption of validated tools. TransitData 2026 conference alignment ensures cutting-edge deployments + methodological rigor. Critical for post-COVID recovery + zero-emission transition requiring real-time reliability + equity analytics.

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