9:00am-12pm, October 21, 2022
Room Augusta H, The Western Peachtree Plaza in Atlanta, Georgia, USA

3rd Workshop on Data-driven Intelligent Transportation (DIT 2022)

Held in conjunction with CIKM 2022

Traffic is the pulse of the city. Transportation systems can involve humans, vehicles, shipments, information technology, and the physical infrastructure, all interacting in complex ways. Intelligent transportation enables the city to function in a more efficient and effective way. A wide range of city data become increasingly available, such as taxi trips, surveillance camera data, human mobility data from mobile phones or location-based services, events from social media, car accident reports, bike-sharing information, Points-Of-Interest, traffic sensors, public transportation data, and many more. This abundance of data poses a grand challenge to the CIKM research community: How to utilize such data toward city intelligence, across various transportation tasks?

The 3rd workshop of "Data-driven Intelligent Transportation" welcomes articles and presentations in the areas of transportation systems, data mining, and artificial intelligence, conveying new advances and developments in theory, modeling, simulation, testing, and case studies, as well as large-scale deployment.

This workshop would like to bring together the researchers to share the exciting data-driven techniques to solve transportation problems.

Topics of interest include but not limited to:

  •     - Data mining techniques for transportation: traffic forecasting, travel time estimation, traffic estimation, semantic mobility data understanding, data visualization, and interactive design
  •     - Intelligent control and planning in transportation: traffic signal control, autonomous driving, vehicle dispatching, route planning, public transportation management, including air, road, and rail traffic management
  •     - Open datasets, benchmarks and demonstrations in transportation
  •     - Security, privacy, and safety issues in transportation systems
  •     - Support systems for drivers, pedestrians, bike riders, policymakers and other parties
  •     - Public policy, and regulatory and societal issues in transportation systems
  •     - Intelligent transportation systems integration into existing road infrastructure

This year we will have paper submissions, invited papers and invited talks.

All the accepted papers will be included in the ERA special issue “Data-driven Intelligent Transportation”. For more information, please find it here. In particular, this workshop would like to call for research papers sharing the experiences from the real data and real-world practice. We do not require technical innovations (using existing data mining techniques is totally acceptable).


This year, we will have 2 invited talks and 6 paper presentations.

Opening Remarks

Invited Talk: Experience of Location Sensing and Correction for Last-mile Delivery

Speaker: Yu Yang (Lehigh University)

Coffee Break and Poster Session

Virtual Invited Talk: Data-driven Prediction and Planning for Autonomous Driving

Speaker: Stefano V. Albrecht (University of Edinburgh)

Paper Presentations

Invited talks


Dr. Stefano V. Albrecht

University of Edinburgh

Data-driven Prediction and Planning for Autonomous Driving

Speaker: Stefano V. Albrecht

Five AI is a leading startup company in the autonomous driving sector in the UK, specialising in the development of a complete self-driving stack (perception, prediction, planning, control, testing & verification). The company was recently acquired by Bosch and is now part of the largest L4 self-driving team in Europe. In this talk, I will present some of Five AI's recent research in data-driven motion prediction and planning for autonomous driving, with a focus on creating robust, interpretable and verifiable systems. All research papers can be found here

Bio: Dr. Stefano V. Albrecht is Assistant Professor in Artificial Intelligence in the School of Informatics at the University of Edinburgh. He leads the Autonomous Agents Research Group which specialises in developing machine learning algorithms for autonomous systems control, with a particular focus on deep reinforcement learning and multi-agent interaction. He is a Royal Society Industry Fellow working with UK-based company Five AI to research and develop AI technologies for autonomous driving. His research in these areas has been published in the top AI/ML/robotics conferences and journals, including NeurIPS, ICML, ICLR, IJCAI, AAAI, UAI, AAMAS, AIJ, JAIR, ICRA, IROS, T-RO. Previously, Dr. Albrecht was a postdoctoral fellow at the University of Texas at Austin where he was supported by a Humboldt Foundation fellowship. He obtained PhD and MSc degrees in Artificial Intelligence from the University of Edinburgh, and a BSc degree in Computer Science from Technical University of Darmstadt.

Dr. Yu Yang

Lehigh University

Longchao Da (New Jersey Institute OF Technology)

Experience of Location Sensing and Correction for Last-mile Delivery

Speaker: Yu Yang

Last-mile delivery is the last step in many real-world applications, such as grocery delivery and online shopping. This talk covers our research on systems and methods for location sensing and correction in the full life cycle of last-mile delivery. Based on the collaboration with real-world delivery platforms, we have deployed our systems and methods to work with more than 3 million workers at a national scale to enable efficient delivery of more than 3.9 billion orders. We will also discuss experience and insights working with real-world systems.

Bio: Yu Yang is an Assistant Professor in the Department of Computer Science and Engineering at Lehigh University. He is broadly interested in Cyber-Physical Systems, Cyber-Human Systems, and Data Science, with a focus on sensing, prediction, and decision-making for cross-domain urban systems such as transportation, communication, and payment, with applications to Smart Cities, Gig Economy, and Community Services. His research has been published in the top system and data science conferences such as SIGCOMM, NSDI, MobiCom, UbiComp, KDD, and ICDE.

Paper Presentations and Posters

- Time Delay Estimation of Traffic Congestion Based on Statistical Causality

YongKyung Oh (UNIST); Ji-In Kwak (UNIST); Sungil Kim (UNIST) [Paper Presentation Video]

- Cooperative Multi-agent Reinforcement Learning Applied to Multi-intersection Traffic Signal Control

James Ault (Texas A&M University); Guni Sharon (Texas A&M University)

- CrowdGAIL: A Spatial-Temporal Aware Method for Agent Navigation

Longchao Da (New Jersey Institute of Technology)

- Deep evidential learning in Diffusion Convolutional Recurrent Neural Network

Zhiyuan Feng (Xi'an Jiao Tong University); Kai Qi (Xi'an Jiao Tong University); Bin Shi (Xi'an Jiao Tong University) [Paper Presentation Video]

- Adaptive Graph Spatial-Temporal Transformer Network for Traffic Forecasting

Aosong Feng (Yale University); Leandros Tassiulas (Yale University)

- Jointly Contrastive Representation Learning on Road Network and Trajectory

Zhenyu Mao (SenseTime Research); Ziyue Li (University of Cologne); Dedong Li (SenseTime Research); Lei Bai (Shanghai AI Laboratory); Rui Zhao (SenseTime Research, Shanghai Jiao Tong University)


Call for Papers

Paper Submission Deadline: August 15, 2022, 11:59 PM AoE.August 22, 2022, 11:59 PM AoE.

This workshop follows the submission requirement by CIKM. All the accepted papers will be treated as invited papers to the "Special Issue: Data-driven Intelligent Transportation" published by Electronic Research Archive and waived the fees.


  •     - Long paper (up to 8 pages) and short paper (up to 4 pages). The page limit includes the bibliography and any possible appendices.
  •     - All papers must be formatted according to ACM sigconf template manuscript style, following the submission guidelines available at: https://www.acm.org/publications/proceedings-template.
  •     - Papers should be submitted in PDF format, electronically, using the CMT submission system.
  •     - All accepted papers will be included in the "Special Issue: Data-driven Intelligent Transportation" published by Electronic Research Archive. Therefore, papers must not have been accepted for publication elsewhere or be under review for another workshop, conferences or journals.


Contacts: dit.workshop.22@gmail.com


Hua Wei
New Jersey Institute of Technology


Guni Sheron
Texas A&M University


Cathy Wu


Sanjay Chawla
Qatar Computing Research Institute


Zhenhui (Jessie) Li
Yunqi Academy of Engineering