Freight transport will be one of the hardest sectors to decarbonise, mainly because of the demand for freight movement is expected to rise steeply over the next few decades and because of its heavy dependence on fossil fuels. This presentation will examine current CO2 trends and forecasts for the freight sector and consider what can be done to achieve deep reductions both in its carbon intensity and total emissions. Measures include shifting freight to lower carbon modes, improving vehicle loading and fuel efficiency, repowering with biofuels and low carbon electricity, shortening supply lines and decelerating transport services. The presentation will focus on the mitigation of freight-related emissions, but also consider the need to adapt logistics systems to climate change thereby reducing the vulnerability of freight deliveries to extreme weather.
Alan McKinnon is Professor of Logistics in the Kühne Logistics University in Hamburg. A graduate of the universities of Aberdeen, British Columbia and London, he has been researching and teaching in freight transport / logistics for over 35 years, has published extensively in journals and books and been an adviser to several governments, parliamentary committees and international organisations, including the OECD, the World Bank, World Economic Forum, European Commission and UNCTAD. He was a lead author of the transport chapter in latest Assessment Report of the Intergovernmental Panel on Climate Change.
In the next decades a major change in the personal-mobility model is expected, in particular in urban and metropolitan areas. The main driver of this change will be the need of a drastic reduction of traffic, CO2 emissions and pollutant emissions, and the attempt to achieve a significant reduction of accidents and fatalities related to mobility. To this purpose, the electrification of vehicles, the car-sharing ownership model, and the robotization of the driver will be the main trends. A fundamental question still remains open: to which extent the virtual mobility of people will replace the traditional “physical” mobility, and how this will affect goods mobility.
Sergio M. Savaresi was born in Manerbio, Italy, on 1968. He received the M.Sc. in Electrical Engineering (Politecnico di Milano, 1992), the Ph.D. in Systems and Control Engineering (Politecnico di Milano, 1996), and the M.Sc. in Applied Mathematics (Catholic University, Brescia, 2000). After the Ph.D. he worked as management consultant at McKinsey&Co, Milan Office. He is Full Professor in Automatic Control at Politecnico di Milano since 2006 . He is Deputy Director and Chair of the Systems&Control Section of Department of Electronics and Computer Sciences, Politecnico di Milano. He is Associate Editor of: IEEE Transactions on Control System Technology; European Journal of Control; IET Transactions on Control Theory and Applications; Control Engineering Practice; International Journal of Vehicle Systems Modelling and Testing. He is also Member of the Editorial Board of the IEEE CSS. He is author of more than 500 scientific publications. His main interests are in the areas of vehicles control, automotive systems, data analysis and system identification, non-linear control theory, and control applications. He is cofounder and partner of five spin-off companies.
Data Mining and Big Data are to research fields in a dramatic effervescence these days. The exponentially growing abundance of data coming from all kinds or processes is yielding volumes of information that surpass the capacity of the traditional model consisting of data bases in a standalone computer. Instead, in almost every engineering field, this data sourcing explosion is creating an urgent need of automatic systems to extract useful knowledge in a pragmatic and convenient time frame. Big Data is devoted to cope with gigantic volumes of Data, for storing it in a hardware/software infrastructure aiming at efficiency (speed of use, easy of access), consistency and security. However, the trend, as the pace of data production is growing in such an accelerated way, the trend is to try to extract knowledge from data streams on the fly, as they are produced, instead of storing all of that information. That is the so called Data Stream Mining model, a quite new paradigm which is gaining more and more importance these days.
Dr. Sanchez-Medina earned his Engineering Master Degree at the Telecommunications Faculty on 2002, and his PhD at the Computer Science Department on 2008. His PhD dissertation versed on the use of Genetic Algorithms, Parallel Computing and Cellular Automata based Traffic Microsimulation to optimize the Traffic Lights Programming within an Urban Traffic Network. His research interests include mainly the application of Evolutionary Computation, Data mining and Parallel Computing to Intelligent Transportation Systems. He has a wide experience on the development of traffic models and simulation platforms. In the last years he has devoted himself to the application of his knowledge on Machine Learning to Data Mining with some publications on that. Javier Sanchez-Medina has been volunteering for several years at many international conferences related to Intelligent Transportation, Computer Science, Evolutionary Computation, etc. He is reviewer for some Transportation related journals. He is also very active as a volunteer of the IEEE ITS Society. Since 2010, we has served for the IEEE ITS Society organizing the TBMO 2010 Workshop at ITSC2010, co-organizing the "Travel Behavior Research: Bounded Rationality and Behavioral Response" Special Session at ITSC2011, being Publications Chair at the IEEE FISTS2011, Registration Chair at the IEEE ITSC2012, Workshops and Tutorials Chair for IEEE ITSC 2013, Panels Chair at IEEE VTC2013-Fall, Program co-Chair at IEEE ITSC2014, program co-Chair at IEEE ITSC2016, publicity chair at IEEE IV2016, program chair at IEEE ICVES 2017, co-program chair at IEEE ITSC2018 and General Chair at IEEE ITSC2015. He served as EiC of the ITS Podcast (2013-2016) and EiC of the ITS Newsletter (2014-2016) and Vice-president of the IEEE ITSS’s Spanish chapter (2014-2016). In 2016 he organized the IEEE Summer School on Smart Mobility. Since 2017 he is President of the IEEE ITSS's Spanish Chapter and Vice President for Technical Activities at the IEEE ITS Society. He has widely published his research with more than 30 international conference articles and more than 15 international journal articles.