Organized By
- Indian Institute of Technology Kanpur, India
- Indian Institute of Technology Tirupati, India
- Technical University Dresden, Germany
- Technion-Israel Institute of Technology, Israel
SUPPORTED BY
Understanding traffic flow dynamics is crucial for optimizing transportation systems, minimizing congestion, and improving safety. It has applications ranging from innovative driver-assistance systems to intelligent traffic management, including the detection of traffic jams and short-term traffic forecasting for dynamic navigation aids.
This workshop aims to provide a comprehensive understanding of traffic flow dynamics by integrating three main components such as data, models and methods. The workshop will highlight the application of these models and methods necessary to address modern transportation challenges.
In this workshop, internationally and nationally acclaimed researchers will cover various topics on traffic flow dynamics in both ordered and disordered traffic.
Collection and processing of traffic data, interpretation of traffic patterns and behaviors from data.
Approaches and models that mathematically describe traffic flow behaviour from macroscopic models (e.g., fluid-dynamic models) to microscopic models (e.g., car-following models), calibration and validation of models.
Methods for traffic management and optimization, including control strategies, and congestion mitigation techniques.
| Reinforcement Learning in Transportation |
Speaker: Prof. Ostap Okhrin Technical University Dresden, Germany |
| Including Perceptions in Driver / Transport User Models |
Speaker: Prof. Partha Chakroborty Indian Institute of Technology Kanpur, India |
| Self-organization Phenomena - From Biological Systems to Traffic Flow |
Speaker: Prof. Andreas Schadschneider University of Cologne, Germany |
| Discovering the Optimal Relationship Hypothesis of Car-following Behaviors with Neural Network-based Symbolic Regression |
Speaker: Prof. Dong Ngoduy Monash University, Australia |
| First-order Macroscopic Model for Disordered Traffic |
Speaker: Dr. Venkatesan Kanagaraj Indian Institute of Technology Kanpur, India |
| Obtaining Longer Trajectory Data for Disordered Traffic using a Swarm of Unmanned Aerial Vehicles |
Speaker: Dr. Gowri Asaithambi Indian Institute of Technology Tirupati, India |
| Intelligent Agent Model for Disordered Traffic Conditions |
Speaker: Dr. Martin Trieber Technical University Dresden, Germany |
| A Model Uncertainty Assessment Framework to Guide Car-following Model Development: Theory and Application to 800 IDM Variants |
Speaker: Prof. Vincenzo Punzo University of Naples Federico II, Italy |
| Flow Modeling for Traffic Management Applications |
Speaker: Prof. Tomer Toledo Techion-Israel Institute of Technology, Israel |
| Traffic State Estimation using Physics-informed Deep Learning Models |
Speaker: Dr. Venkatesan Kanagaraj Indian Institute of Technology Kanpur, India |
| Investigation of High-speed Social Force Model under Disordered Traffic Conditions |
Speaker: Dr. Gowri Asaithambi Indian Institute of Technology Tirupati, India |
Andreas Schadschneider has obtained his Ph.D. in 1991 working in theoretical solid-state physics. He is currently professor at the Institute for Theoretical Physics and the Institute for Physics Education of the University of Cologne. His main research interests are related to understand the fundamental physics underlying all kinds of traffic systems (vehicles, pedestrians, biological systems).
Dong Ngoduy received a Ph.D. degree in traffic flow theory from the Technical University of Delft (TU Delft), The Netherlands, in 2006. From 2006 to 2020, he worked as a Research Fellow and an Associate Professor at the University of Leeds, U.K., and the University of Canterbury, New Zealand. He is currently the Head of Transport Engineering and an Associate Professor at Monash University, Australia. He has co-authored over 150 journal articles and conference papers in the field. He conducts research on connected and autonomous vehicles, traffic flow theory and simulation, applications of AI and machine learning to transportation, and network optimization. He has also been a member of several journal editorial boards in the field, the Peer Review College of the U.K. Research Council (EPSRC) and the Detailed Assessor of the Australian Research Council (ARC).
Gowri Asaithambi is currently an Associate Professor in the Department of Civil and Environmental Engineering at IIT Tirupati. She received her Ph.D. from the Indian Institute of Technology Madras in 2011. Her research focuses on traffic flow modeling and simulation, traffic operations and management, and intelligent transportation systems. She has co-authored over 75 journal articles and conference papers in these fields and serves on the editorial board of Transportation Letters, a journal published by Taylor and Francis.
Martin Treiber received his Ph.D. from the University of Bayreuth, Germany, in 1996. He worked as a research scientist at the University of Stuttgart, Germany, from 1996 to 2000. Since 2000, he has been a senior research scientist at the Technical University Dresden, Germany. His research interests include traffic data analysis and simulation, traffic flow models including those for human and automated driving, bicycle and pedestrian traffic. He has published two highly acclaimed books: one in German (Verkehrsdynamik und -Simulation, Springer, 2010) and one in English (Traffic Flow Dynamics, Springer, 2013), both of which are widely used by post-graduate students at universities around the world.
Ostap Okhrin is a Professor of Econometrics and Statistics, especially in Transportation, at the Institute of Transport and Economics, Technical University Dresden, Germany. He has co-authored nearly 100 publications in the field of mathematical and applied statistics, econometrics, and reinforcement learning, with applications to finance, economics and autonomous driving.
Partha Chakroborty obtained his Ph.D. in 1993, specializing in traffic flow. He is currently a Professor at IIT Kanpur. His research interest includes traffic flow and transit systems, two widely different areas. Of late he divides his time between devising methods to incorporate perception in driver models and developing optimum substitution models arising in transit routing.
Dr. Tomer Toledo is a Full Professor at the Faculty of Civil and Environmental Engineering and the Transportation Research Institute at the Technion – Israel Institute of Technology. He holds a Ph.D. in Transportation Systems from MIT in 2003. He has held visiting professor positions at MIT and Northeastern University and is an Adjunct Professor at the Indian Institute of Technology Kanpur. His research is in the areas of traffic modeling and simulation, intelligent transportation systems, driving and travel behavior, dynamic traffic management systems and transportation network analysis. He currently serves as an Associate Editor for Transportation Science and a Handling Editor for Transportation Research Record. He has authored over 90 journal papers and more than a hundred conference papers and presentations.
Venkatesan Kanagaraj is currently an Assistant Professor in the Department of Civil and Environmental Engineering at IIT Kanpur. He completed a post-doctoral fellowship at the Technion-Israel Institute of Technology, Israel, in 2015. From 2015 to 2019, he served as a Humboldt Fellow and Marie-Curie Fellow at the Technical University of Dresden, Germany. His primary research interests include traffic flow theory, crowd dynamics, and connected and autonomous vehicles.
Vincenzo Punzo is currently full professor at the University of Naples Federico II, where he teaches Road traffic control
and Smart and electric mobility
. He is a recipient of a senior researcher grant on Intelligent Transportation Systems and e-Mobility at the European Commission Joint Research Centre, from 2011 to 2013. His research interests include traffic flow theory and simulation under uncertainty in road systems. In particular, trajectory data analysis and reconstruction methodologies, calibration, validation and string stability of car-following models in mixed and heterogeneous traffic. His scientific record includes more than 30 top-journal papers with 2300+ citations in Scopus, and scientific awards like the TRB's Greenshields Prize
.
| IITK Faculty | 2500 Rs. |
| Non-IITK Faculty | workshop fee + 18% GST = 2950 Rs. |
| IITK Students | 1200 Rs. |
| Non-IITK Students | workshop fee + 18% GST = 1416 Rs. |
| Personnel from Industries/ R&D Organizations | workshop fee + 18% GST = 4130 Rs. |
Step 1: Pay the Fees through SBI Collect according to your category.
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| Course Code | 51 |
| Course Title | Traffic Flow Dynamics |
| Course Duration | 17-18 October 2024 |