Abstract

Despite a chaotic history and the fact that the discipline has existed since the 1950s, "Artificial Intelligence" made a huge come back in the last decade. But as it stands, this "Artificial Intelligence" brings its share of unrealistic promises worthy of the best Hollywood films, allowing a few charlatans to make us believe that the machines could one day take power and reduce us to almost nothing. But above all, to make us run the risk of abandoning all research in this field and threatening advances in disciplines such as machine learning or deep learning, while they are still in their infancy and will still bring much more to humanity...

Biography

As CTO and Senior Vice President of Innovation for Samsung Electronics, Dr. Luc JULIA ledthe company’s vision and strategy for the Internet of Things and is now focusing on making these machines smarter. Previously, Luc co-directed Siri (the voice assistant that he co-created) at Apple, was Chief Technologist at Hewlett-Packardand cofounded a number of start-ups in the Silicon Valley, including ORB Networks, where he invented “place shifting”. He began his career at SRI International, where he founded the Computer Human Interaction Center and was involved in the creation of Nuance Communications, now the world leader in speech recognition. Luc holds degrees in Mathematics and Computer Science from the University Pierre et Marie Curie in Paris and earned a Ph.D. in Computer Science at the Ecole Nationale Supérieure des Télécommunications de Paris. He is now a member of the National Academy of Technologies of France. He is the bestselling author of the book “There is no such thing as Artificial Intelligence”, holds dozens of patents and is recognized as one of the top 100 most influential French developers in the digital world.

Abstract

Railway transport will grow considerably over the next 10 to 20 years as the sustainable alternative for the accessibility of cities and (inter)national mobility. Railway capacity and performance must therefore increase significantly which must be facilitated by digitalization and automation. The four pillars of this digital transformation are automated railway timetabling, automatic train operation, intelligent railway traffic management and radio-based railway signalling. Accurate timetabling models are needed to provide conflict-free train paths to the railway traffic management systems. Connected driver advisory systems or automatic train operation then use train trajectory optimization algorithms for punctual and energy-efficient driving, while the connection to the railway traffic management systems must guarantee coordinated route setting and proactive rescheduling regarding disturbances and disruptions. In addition, replacing conventional fixed-block signalling systems by moving block signalling will allow trains to follow much closer at an absolute braking distance, while train-to-train communication will further revolutionize railway operations by enabling virtually coupled train sets in which trains can operate in a platoon at a relative braking distance coordinated by a master train. The main challenge is to integrate all these components to achieve a resilient railway traffic system. 

Biography

Prof. Dr. Rob M.P. Goverde is Professor of Railway Traffic Management & Operations and Director of the Digital Rail Traffic Lab at Delft University of Technology, and chairs the Railway Systems theme of the TU Delft Transport Institute. He has an MSc in Mathematics from Utrecht University (1993), a Professional Doctorate in Engineering (PDEng) in Mathematical Modelling and Decision Support from Delft University of Technology (1996), and a PhD in Railway Transport from Delft University of Technology (2005). He cooperated in many international research projects including the EU projects ON-TIME, MOVINGRAIL (coordinator), RAILS, and PERFORMINGRAIL. His research interests include railway timetable optimization, railway traffic and disruption management, automatic train operation, train control and railway signalling. He is Editor-in-Chief of the Journal of Rail Transport Planning & Management, Associate Editor of the IEEE Transactions on Intelligent Transportation Systems, board member of the International Association of Railway Operations Research (IAROR), and Fellow of the Institution of Railway Signal Engineers (FIRSE).  

Abstract

Human mobility in congested city centers is a complex dynamical system with high density of population, many transport modes to compete for limited available space and many operators that try to efficiently manage different parts of this system. New emerging modes of transportation, such as ride-hailing and on-demand services, and new technologies, such as autonomous vehicles, create additional opportunities, but also more complexity. The new era of sharing information and ‘big data world’ has raised our expectation to make mobility more predictable and controllable through a better utilization of existing resources and capacity. The primary motivation of this talk is to study the spatiotemporal relation of congested links in large networks, develop new advancements in the Macroscopic Fundamental Diagram, observe congestion propagation from a macroscopic perspective, identify the effect of multimodal interactions in network capacity and finally design network-level control strategies to improve multimodal mobility. Investigating the clustering problem over time help us reveal the hidden information during the process of congestion formation and dissolution. In this framework, we will be able to chase where congestion originates and how traffic management systems affect its formation and the time it finishes. Different control strategies are developed based on principles of optimization control theory.

Biography

Prof. Nikolas Geroliminis is an Associate Professor at EPFL and the head of the Urban Transport Systems Laboratory (LUTS). Before joining EPFL he was an Assistant Professor on the faculty of the Department of Civil Engineering at the University of Minnesota. He has a diploma in Civil Engineering from the National Technical University of Athens (NTUA) and a MSc and Ph.D. in civil engineering from University of California, Berkeley. His research interests focus primarily on urban transportation systems, traffic flow theory and control, public transportation and on-demand transport, car sharing, Optimization and Large Scale Networks. He is a recipient of the ERC Starting Grant METAFERW: Modeling and controlling traffic congestion and propagation in large-scale urban multimodal networks. Among his recent initiatives is the creation of an open-science large-scale dataset of naturalistic urban trajectories of half a million vehicles that have been collected by one-of-a-kind experiment by a swarm of drones (https://open-traffic.epfl.ch). Among other editorial responsibilities, he is currently the Editor-In-Chief of Transportation Research part C: Emerging Technologies.