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Destination Area: Intelligent Infrastructure for Human-Centered Communities (IIHCC)

Permanent URI for this collection

https://hdl.handle.net/10919/79980
IIHCC focuses its attention on the ways that people interact with one another and with their environment. Interest areas in this DA include smart, healthy, and sustainable cities and communities; transportation systems; human safety, health, and wellness; integrated energy systems; network science and engineering; public policy; and cyber-physical systems. The initial focus for IIHCC will be on four themes: Ubiquitous Mobility: The location-agnostic promise of new communication and information technologies Automated Vehicle Systems: vehicles that can transit safely and efficiently through our communities independent of a human operator Smart Design and Construction: an intelligent, integrated, adaptable, responsive, and sustainable human-centric built environment Energy: the underlying innovations that will be required in the production, distribution, and consumption of energy to realize such a system

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Browsing Destination Area: Intelligent Infrastructure for Human-Centered Communities (IIHCC) by Author "Ahn, Kyoungho"

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    AERIS : Eco-Vehicle Speed Control at Signalized Intersections Using I2V Communication
    Rakha, Hesham A.; Kamalanathsharma, Raj Kishore; Ahn, Kyoungho (United States. Joint Program Office for Intelligent Transportation Systems, 2012-06)
    This report concentrates on a velocity advisory tool, or decision support system, for vehicles approaching an intersection using communication capabilities between the infrastructure and vehicles. The system uses available signal change information, vehicle characteristics, lead vehicle characteristics, and intersection features to compute the fuel-optimal vehicle trajectory. The proposed system involves a complex optimization logic incorporating roadway characteristics, lead vehicle information, vehicle acceleration capabilities and microscopic fuel consumption models to generate a fuel-optimal speed profile. The research also develops a MATLAB application in order to demonstrate the potential of an in-vehicle application of such a technology.
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    Predictive Eco-Cruise Control (ECC) System: Model Development, Modeling and Potential Benefits
    Rakha, Hesham A.; Ahn, Kyoungho; Park, Sangjun (United States. Department of Transportation. Research and Innovative Technology Administration, 2013-02-19)
    The research develops a reference model of a predictive eco-cruise control (ECC) system that intelligently modulates vehicle speed within a pre-set speed range to minimize vehicle fuel consumption levels using roadway topographic information. The study includes five basic tasks: (a) develop a vehicle powertrain model that can be easily implemented within eco-driving tools, (b) develop a simple fuel consumption model that computes instantaneous vehicle fuel consumption levels based on power exerted, (c) evaluate manual driving and conventional cruise control (CC) driving using field-collected data, (d) develop a predictive ECC system that uses the developed vehicle powertrain and fuel consumption models, and (e) evaluate the potential benefits of the proposed predictive ECC system on a pre-trip and fleet-aggregate basis. This study develops a predictive ECC system that can save fuel and reduce CO2 emissions using road topography information. The performance of the system is tested by simulating a vehicle trip on a section of Interstate 81 in the state of Virginia. The results demonstrate fuel savings of up to 15 percent with execution times within real time. The study found that the implementation of the predictive ECC system could help achieving better fuel economy and air quality.