29,455 research outputs found
FLORIDA\u27S DOWNTOWNS: THE KEY TO SMART GROWTH, URBAN REVITALIZATION, AND GREEN SPACE PRESERVATION
This article reviews Florida\u27s growth management system, which has spurred suburban development, and its negative impact on Florida\u27s cities. As Florida\u27s governor and legislature have turned their focus to this issue, this article evaluates policy recommendations to limit Florida\u27s suburban sprawl and invigorate its urban centers
Yellowstone County/City of Billings Growth Policy Health Impact Assessment
Analyzes the potential impact of community growth and the built environment on residents' health, emergency preparedness, nutrition, pedestrian safety and traffic, and physical activity as a way to make health part of the decision-making process
An Online Decision-Theoretic Pipeline for Responder Dispatch
The problem of dispatching emergency responders to service traffic accidents,
fire, distress calls and crimes plagues urban areas across the globe. While
such problems have been extensively looked at, most approaches are offline.
Such methodologies fail to capture the dynamically changing environments under
which critical emergency response occurs, and therefore, fail to be implemented
in practice. Any holistic approach towards creating a pipeline for effective
emergency response must also look at other challenges that it subsumes -
predicting when and where incidents happen and understanding the changing
environmental dynamics. We describe a system that collectively deals with all
these problems in an online manner, meaning that the models get updated with
streaming data sources. We highlight why such an approach is crucial to the
effectiveness of emergency response, and present an algorithmic framework that
can compute promising actions for a given decision-theoretic model for
responder dispatch. We argue that carefully crafted heuristic measures can
balance the trade-off between computational time and the quality of solutions
achieved and highlight why such an approach is more scalable and tractable than
traditional approaches. We also present an online mechanism for incident
prediction, as well as an approach based on recurrent neural networks for
learning and predicting environmental features that affect responder dispatch.
We compare our methodology with prior state-of-the-art and existing dispatch
strategies in the field, which show that our approach results in a reduction in
response time with a drastic reduction in computational time.Comment: Appeared in ICCPS 201
Quantify resilience enhancement of UTS through exploiting connect community and internet of everything emerging technologies
This work aims at investigating and quantifying the Urban Transport System
(UTS) resilience enhancement enabled by the adoption of emerging technology
such as Internet of Everything (IoE) and the new trend of the Connected
Community (CC). A conceptual extension of Functional Resonance Analysis Method
(FRAM) and its formalization have been proposed and used to model UTS
complexity. The scope is to identify the system functions and their
interdependencies with a particular focus on those that have a relation and
impact on people and communities. Network analysis techniques have been applied
to the FRAM model to identify and estimate the most critical community-related
functions. The notion of Variability Rate (VR) has been defined as the amount
of output variability generated by an upstream function that can be
tolerated/absorbed by a downstream function, without significantly increasing
of its subsequent output variability. A fuzzy based quantification of the VR on
expert judgment has been developed when quantitative data are not available.
Our approach has been applied to a critical scenario (water bomb/flash
flooding) considering two cases: when UTS has CC and IoE implemented or not.
The results show a remarkable VR enhancement if CC and IoE are deploye
A Framework for Integrating Transportation Into Smart Cities
In recent years, economic, environmental, and political forces have quickly given rise to “Smart Cities” -- an array of strategies that can transform transportation in cities. Using a multi-method approach to research and develop a framework for smart cities, this study provides a framework that can be employed to: Understand what a smart city is and how to replicate smart city successes; The role of pilot projects, metrics, and evaluations to test, implement, and replicate strategies; and Understand the role of shared micromobility, big data, and other key issues impacting communities.
This research provides recommendations for policy and professional practice as it relates to integrating transportation into smart cities
VANET Applications: Hot Use Cases
Current challenges of car manufacturers are to make roads safe, to achieve
free flowing traffic with few congestions, and to reduce pollution by an
effective fuel use. To reach these goals, many improvements are performed
in-car, but more and more approaches rely on connected cars with communication
capabilities between cars, with an infrastructure, or with IoT devices.
Monitoring and coordinating vehicles allow then to compute intelligent ways of
transportation. Connected cars have introduced a new way of thinking cars - not
only as a mean for a driver to go from A to B, but as smart cars - a user
extension like the smartphone today. In this report, we introduce concepts and
specific vocabulary in order to classify current innovations or ideas on the
emerging topic of smart car. We present a graphical categorization showing this
evolution in function of the societal evolution. Different perspectives are
adopted: a vehicle-centric view, a vehicle-network view, and a user-centric
view; described by simple and complex use-cases and illustrated by a list of
emerging and current projects from the academic and industrial worlds. We
identified an empty space in innovation between the user and his car:
paradoxically even if they are both in interaction, they are separated through
different application uses. Future challenge is to interlace social concerns of
the user within an intelligent and efficient driving
Multiagent Intelligent System of Convergent Sensor Data Processing for the Smart&Safe Road
The results of monitoring and analyzing traffic accidents, fixed by an intelligent monitoring system with photoradar complexes, are considered. The system works with a network of distributed photoradar vehicle detectors for road accidents, video surveillance cameras, vehicle information and communication systems, built-in car navigation equipment and mobile communication equipment. A multiagent approach developed to address the tasks of sensor data collecting and processing. The system functionality is implemented by several agents that perform data collecting, cleaning, clustering, comparing time series, retrieving data for visualization, preparing charts and reports, performing spatial and intellectual analysis, etc. Convergent approach is the convergence of cloud, fog and mobile data processing technologies. The diagnostic system is necessary for remote maintenance of photoradar equipment. The structure of the neural network is adapted to the diagnosing problems and forecasting. The tasks of intellectual analysis and forecasting traffic accidents are solved. The hybrid fuzzy neural network is synthesized. Because of the comparison of time series of traffic accidents and time series of meteorological factors, the presence of factors to become determinants for an abnormal change in the traffic situation in controlled areas is established
Human Computer Interactions in Next-Generation of Aircraft Smart Navigation Management Systems: Task Analysis and Architecture under an Agent-Oriented Methodological Approach
The limited efficiency of current air traffic systems will require a next-generation of Smart Air Traffic System (SATS) that relies on current technological advances. This challenge means a transition toward a new navigation and air-traffic procedures paradigm, where pilots and air traffic controllers perform and coordinate their activities according to new roles and technological supports. The design of new Human-Computer Interactions (HCI) for performing these activities is a key element of SATS. However efforts for developing such tools need to be inspired on a parallel characterization of hypothetical air traffic scenarios compatible with current ones. This paper is focused on airborne HCI into SATS where cockpit inputs came from aircraft navigation systems, surrounding traffic situation, controllers' indications, etc. So the HCI is intended to enhance situation awareness and decision-making through pilot cockpit. This work approach considers SATS as a system distributed on a large-scale with uncertainty in a dynamic environment. Therefore, a multi-agent systems based approach is well suited for modeling such an environment. We demonstrate that current methodologies for designing multi-agent systems are a useful tool to characterize HCI. We specifically illustrate how the selected methodological approach provides enough guidelines to obtain a cockpit HCI design that complies with future SATS specifications.This work was supported in part by Projects MINECO TEC2011-28626-C02-01/02, by program CENIT-ATLANTIDA (cofinanced by Indra and Boeing R&TE), and by ULPGC Precompetitive Research Project (ULPGC Own Program).Publicad
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