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 September 2026

Introduction

This Special Issue invites research and practice that translate automated transit data into more efficient, reliable, and equitable service. It is linked to the TransitData 2026 conference and welcomes submissions spanning the full spectrum of transit data applications — from strategic planning and performance measurement to operations control, predictive maintenance, and service restoration.

Practitioner-led case studies, real-world deployments, lessons learned, and decision-ready tools from agencies and industry are especially welcome.

Scope & Significance

As public transit agencies increasingly deploy automated data collection systems — including smart cards, GPS, automated passenger counters, and real-time sensors — there is an urgent need to translate these data streams into actionable insights for planning, operations, and policy. This Special Issue provides a dedicated platform for research and practice that advances the state of the art in AI and data analytics for transit — bridging methodological innovation with real-world operational impact.

List of Topic Areas

Manuscripts are invited on themes including, but not limited to:

1. The use of advanced data analytics and artificial intelligence in public transit

2. Applications using automated data to enhance strategic and service planning

3. Performance measurement, fare policy, market research, and equity analysis using automated transit data

4. Applications using automated data to assist in operations control, incident management, and service restoration

5. Understanding demand, customer behavior, and normal patterns of travel using automated data

6. Response to service disruptions and special-event impacts — data-driven insights

7. Crowding management and predictive maintenance using transit data

8. Methodological challenges in using automated transit data — data fusion, OD inference, causal evaluation, bias, representativeness, and validation

9. New technologies and approaches for transit data collection

10. Visualization tools for transit data analysis and decision-making

11. Organizational challenges related to data management and governance

12. Transit automated data specifications and their use — GTFS, TIDES, TODS

13. LLMs and text data applications in transit analytics

14. Benchmarking and validation frameworks for transit AI models

15. Other emerging topics in transit data, AI, and analytics

Guest Editors

Prof. Amer Shalaby University of Toronto, Toronto, Canada

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

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

Key Deadlines

Manuscript Submission Opens: 20 June 2026 Manuscript Submission Deadline: 30 September 2026

Submission Guidelines

Submit your manuscript via the Journal of Public Transportation online submission system:

https://submit.elsevier.com/JPUBTR

When submitting, select Article Type:

"VSI: TransitData2026"

to ensure the submission is correctly grouped under this Special Issue for the review process.

All submissions must be original and must not be under review elsewhere at the time of submission. All articles will be reviewed by no fewer than two independent experts.

Why Publish in This Special Issue?

• Special Issue articles are downloaded twice as often within the first 24 months compared to regular issue articles

• Special Issue articles attract 20% more citations in the first 24 months

• Articles are published together on ScienceDirect — easy for researchers to discover your work

• All articles reviewed by no fewer than two independent experts

About the Journal

The Journal of Public Transportation, published by Elsevier, is a fully open access peer-reviewed journal with a CiteScore of 3.2 and Impact Factor of 3.7. It is dedicated to advancing research on public transportation systems — providing an international platform for interdisciplinary scholarship exploring transit planning, operations, policy, user behavior, data analytics, and the role of public transport in sustainable and equitable urban development worldwide.

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