| Description |
1 online resource (12 pages) : color illustrations. |
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text txt rdacontent |
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computer c rdamedia |
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online resource cr rdacarrier |
| Series |
NREL/CP ; 5400-81978 |
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Conference paper (National Renewable Energy Laboratory (U.S.)) ; 5400-81978.
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| Note |
"Presented at the ASCE International Conference on Transportation & Development, Seattle, Washington, May 31-June 3, 2022"--Cover. |
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In scope of the U.S. Government Publishing Office Cataloging and Indexing Program (C&I) and Federal Depository Library Program (FDLP). |
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"June 2022." |
| Bibliography |
Includes bibliographical references (pages 11-12). |
| Funding |
DE-AC36-08GO28308 |
| Note |
Description based on online resource; title from PDF title page (NREL, viewed October 21, 2022). |
| Summary |
This paper puts forth a system architecture for an infrastructure-based cooperative perception (CP) fusion engine, to provide a complete state-space digital representation, with measurable accuracy, to support a wide-range of applications. The architecture includes the inputs, functional flow, data standardization recommendations, outputs and supported applications. The CP engine addresses critical needs with respect to accelerating the benefits of automation through intelligent roadway infrastructure (IRI), that complements and accelerates connected and automated vehicle (CAV) technology. that the CP acquires and fuses information from sensors (radar, LiDAR, and cameras), and CAVs to intelligently perceive roadway traffic states of all moving objects, create a complete three-dimensional digital representation of that state-space, and communicate it to downstream application such as intelligent signal control, safety and energy applications, and cooperate driving applications for CAVs as examples. The IRI approach, as opposed to a vehicle centric approach, is found to be more scalable in that it can deployed to the roughly 300,000 signalized intersections more readily than the over 300 million vehicles in the US, and accrues early-stage benefits equitable to all roadway users addressing safety, equity, fuel efficiency, and GHG reduction. |
| Subject |
Traffic engineering -- United States -- Computer simulation.
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Technique de la circulation -- États-Unis -- Simulation par ordinateur.
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Traffic engineering -- Computer simulation
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United States https://id.oclc.org/worldcat/entity/E39PBJtxgQXMWqmjMjjwXRHgrq
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| Indexed Term |
data fusion |
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infrastructure to infrastructure |
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intelligent roadway infrastructure |
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track fusion |
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traffic control |
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vehicle to infrastructure |
| Added Author |
National Renewable Energy Laboratory (U.S.), issuing body.
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| Standard No. |
1871534 OSTI ID |
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0000-0002-3955-9608 |
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0000-0003-4415-7694 |
| Gpo Item No. |
0430-P-04 (online) |
| Sudoc No. |
E 9.17:NREL/CP-5400-81978 |
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