BEGIN:VCALENDAR VERSION:2.0 PRODID:-//Memento EPFL// BEGIN:VEVENT SUMMARY:Data analytics and simulation tools for urban mobility of the futu re DTSTART:20161014T121500 DTEND:20161014T131500 DTSTAMP:20260501T113110Z UID:9d4de94e2e9297ff4db2efa2f8f166c04dcfb8d0650cab3cd0ae35c1 CATEGORIES:Conferences - Seminars DESCRIPTION:Prof. Dr Justin Dauwels\, Associate Professor\, School of Elec trical and Electronic Engineering\, Nanyang Technological University (NTU) Singapore\nAn estimated 64% of all travel today is made within urban envi ronments. By 2050 the total amount of urban kilometres travelled worldwide is expected to triple\, with traffic congestion potentially bringing majo r cities to a standstill. In Singapore\, a small island with a population of 5.4 million\, there are approximately 1 million cars on the roads. At t he same time\, roads take up 12% of land space. With the limited land spac e in Singapore\, it is unrealistic to further increase the number of vehic les or add more roads.  To address these challenges\, the Singapore gover nment plans to implement an intelligent and adaptable transport system whi ch uses data to empower commuters and adjusts to their needs. Sensor netwo rks are being deployed that collect data from busy areas such as traffic j unctions\, bus stops and taxi queues\, then relay it back to the relevant agencies for analysis through data analytics and real-world applications.  Besides transportation systems powered by big data analytics\, driverles s vehicles are also a major focus so far for the Singapore government. Mor e than six kilometres of public roads have been opened this year for AV tr ials\, currently in use for trials with a small fleet of public self-drivi ng taxis. Various stakeholders are aiming for full-scale commercial auton omous taxi service in 2018 in Singapore.\n\n                                                            \n\nIt is within this context that our research group has developed various data analytics and simulation tools for transportation a pplications. In the seminar\, I will give an overview of our research effo rts.\n\nOver the last years\, we have been working towards scalable real-t ime algorithms for predicting traffic speed and travel time. The predictio n systems designed by our team is able to perform accurate real-time predi ctions in large networks consisting of 10\,000 – 100\,000 links\, by exp loiting the correlations in traffic data. The sensing and prediction can b e performed in a distributed fashion\, e.g.\, on smartphones\, as alternat ive to high-cost centralized systems. In recent work\, we are investigatin g the effect of rainfall and road incidents on road traffic\, in an attemp t to further improve traffic predictions by incorporating information abou t traffic incidents and weather. We are also working towards traffic-and w eather-aware online stochastic routing algorithms that are able to adapt t he routes of vehicles based on real-time information about the condition o f the transportation networks.\n\nBesides macro-scale data analytics\, our team is designing machine learning algorithms for micro-scale transportat ion applications. Specifically\, currently we are creating algorithms for scene understanding in urban and off-road scenarios. In collaboration with our local industry partner ST Engineering\, we are integrating these tech nologies into autonomous vehicles (AVs) for urban mobility and airport aut omation.\n\nIn parallel efforts\, we have created a simulation platform fo r exploring emerging transportation paradigms. One of these technologies i s vehicle-to-vehicle (V2V) and vehicle-to-infrastructure communications sy stems (V2X). Our simulation platform allows researchers to explore various use cases of V2V/V2X technologies at a high level of realism\, including smart traffic signals and vehicle platooning. As part of the recently esta blished Centre of Excellence for Testing and Research of Autonomous Vehicl es - NTU (CENTRAN)\, the team is currently incorporating realistic models of AVs into the simulation platform\, which will yield a sophisticated sim ulation tool for studying and testing AVs and designing the required infra structure for supporting AVs. This simulation tool will be instrumental fo r the certification of AVs to be deployed in Singapore. The tool will also allow us to simulate and design various approaches to collect\, communica te\, and analyse transportation data through networks of V2V/V2X enabled A Vs\, providing real-time macro-scale analytics about transportation networ ks.\n\nBio : Dr. Justin Dauwels is an Associate Professor with School of E lectrical and Electronic Engineering at the Nanyang Technological Universi ty (NTU) in Singapore. He serves as Deputy Director of the ST Engineering – NTU corporate lab\, which comprises 100+ PhD students\, research staff and engineers\, developing novel autonomous systems for airport operation s and transportation. He is also involved as project PI in the Centre of E xcellence for Testing and Research of Autonomous Vehicles - NTU (CENTRAN)\ , which will lead the development of testing requirements for such vehicle s\, and was launched by the Land Transport Authority (LTA) and JTC\, in pa rtnership with NTU. Moreover\, he serves as project PI in the BMW-NTU lab on Future Mobility\,\n\nand the NXP-NTU lab on vehicle-to-vehicle communic ations.\n\nHis research interests are in data analytics with applications to intelligent transportation systems\, autonomous systems\, and analysis of human behavior & physiology. He obtained the PhD degree in electrical e ngineering at the Swiss Polytechnical Institute of Technology (ETH) in Zur ich in December 2005. He was a postdoctoral fellow at the RIKEN Brain Scie nce Institute (2006-2007) and a research scientist at the Massachusetts In stitute of Technology (2008-2010). He has been a JSPS postdoctoral fellow (2007)\, a BAEF fellow (2008)\, a Henri-Benedictus Fellow of the King Baud ouin Foundation (2008)\, and a JSPS invited fellow (2010\, 2011). His rese arch on intelligent transportation systems has been featured by the BBC\, Straits Times\, Lianhe Zaobao\, Channel 5\, and numerous technology websit es. His research team has won several best paper awards at international c onferences. Besides his academic efforts\, the team of Dr. Justin Dauwels also collaborates intensely with local start-ups\, SMEs\, and agencies\, i n addition to MNCs\, in the field of data-driven transportation and logist ics. LOCATION:GCA331 http://plan.epfl.ch/?lang=fr&room=GCA331 STATUS:CONFIRMED END:VEVENT END:VCALENDAR