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Room: Symposion @Toyota Auditorium
Time : 9:15am-11:00am, October 6th (Thursday)
Urban OS as a social ICT platform to realize sustainable city with citizen participation
Hiroto Yasuura, Vice President of Kyushu University
Recent rapid progress of information technology such as analysis of big data and open data, Internet of Things (IoT) and Artificial Intelligence (AI) will enable us to collect variety of societal data, utilize them publicly and privately, and reorganize social infrastructure. Collected big data by IoT with trillion sensors are analyzed by advanced analysis technologies including deep learning. Open data enables people to use publicly disclosed societal information in government sectors.
Upon this movement, citizens can utilize variety of societal data, use open license software and applications for analysis, and create collaborative applications. If everyone can access any information of city, citizens themselves can create solutions for their immediate problems locally and directly. A part of social services are replaced by citizen’s agile activities and we can reduce local government’s cost. This is one of the ways to sustainable city and society with small government.
Three social and technological trends are required to realize the sustainable society;
1) Everyone actively participates in social solution development.
2) Society allows mixed utilization of cross-domain data.
3) People change acceptability of sharing their data and belongs.
Analysis of cross-domain data such as people’s movements and energy let us understand social activity precisely. Observation of dynamics of the real world let us understand overhead and waste of activities in the city. Using the shared data, everyone can propose solutions of common problems by sharing resources and goods.
In Kyushu University Center of Innovation (COI) program, Urban Operating System (Urban OS) as a social ICT platform is proposed. Urban OS collects and provides cross- domain data in public. In the COI project, traffic and energy domain research are in progress as examples of actual applications. Research objective is to create a convenient and smart traffic control system, and an advanced analysis system for energy prediction and high level balancing using cross-domain data. In this presentation, a concept and research activities on Urban OS are introduced and a future vision of sustainable city is proposed.
Stop wasting time and fuel in traffic jams
Berthold K. P. Horn, Professor of MIT, General Chair of UV2016
An urban commuter in the USA spends 38 hours stuck in traffic per annum on average, and wastes 72 liters of fuel, which adds 172 kgs of CO2 to the atmosphere (according to the Texas A&M Transportation Institute). Overall, in the USA alone, the costs of congestion are estimated to be around $121 billion per annum ($820 per commuter), with 11 billion liters of fuel wasted, and 25.4 billion kgs of extra CO2 emitted. Speed variability inherent in traffic flow instabilities also increases the risk of collisions.
Stop-and-go traffic is a common form of congestion (as are so-called “phantom traffic jams”). It is well known that sequences of “car following” vehicles—whether controlled by humans or some form of automation, such as adaptive cruise control—are inherently unstable. There are hundreds of papers explaining this, going back all the way to the 1930s.
Bilateral control can suppress traffic flow instabilities. Bilateral control differs from “car following” and adaptive cruise control in that, counter-intuitively, it uses information about the following vehicle (as well as about the leading vehicle). Stability can be demonstrated using simulation or mathematical analysis.
A physical analog of a sequence of vehicles using bilateral control is a chain of masses connected by springs and dampers—a system which is inherently stable, since it lacks an external energy source. To further understand bilateral control and its capacity to suppress instabilities, it is useful to move from a microscopic view (interaction of individual vehicles) to a macroscopic view (densities and flow rates). This leads to a damped non-linear wave equation that governs traffic under bilateral control. The equation allows us to determine the speed of propagation of disturbances, as well as their rate of decay, and suggests improved control strategies.
Instabilities presently occur at high traffic densities. So one attempt at improving matters in the past has been to limit density, by, for example, controlling highway entrances. But this comes at the cost of reducing the potential throughput. Bilateral control has the potential to increase throughput of highways by up to a factor of two, because it can operate stable at higher densities. Other benefits include reduced travel times and calmer nerves.
Implementation of bilateral control requires only a modest additions to existing adaptive cruise control systems: namely adding sensors in the rear to those that already exist in front of the vehicle. The sensors can be of various types, including radar and machine vision, anything that can be used to estimate the distance and relative speed of the leading vehicle and the following vehicle.
One impediment to rapid deployment is the fact that the full benefit of the system will only be apparent when a significant fraction of vehicles use bilateral control. So it is imperative that implementations of adaptive cruise control make the small additions needed to enable bilateral control. It may also be necessary for agencies in charge of transportation to mandate its use.
Smart City Standardization Progress in China
LV Weifeng, Dean of Beihang University
A smart city comprises a huge number of information systems deployed across the city. Different systems have different stakeholders, domains and usage contexts. As such to have a standard system for smart city is essential to maintain interoperability among different information systems to ensure event awareness. This talk will present China’s strategy and current progress in smart city standardization.
Special Session: Future Talk -- Backcasting from Future Society
Room: Symposion @Toyota Auditorium
Time : 11:20am-12:20pm, October 6th (Thursday)
Brain Network Analysis for Revealing Neural Circuits that Govern Human Cognitive Process from MRI Datasets: Background, Meth- ods & Applications
Zhishun Wang (Professor of Columbia University)