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New Algorithms for Computing the Time-to-Collision in Freeway Traffic Simulation Models
Ways to estimate the time-to-collision are explored. In the context of traffic simulation models, classical lane-based notions of vehicle location are relaxed and new, fast, and efficient algorithms are examined. With trajectory conflicts being the main focus, computational procedures are explored w...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4297628/ https://www.ncbi.nlm.nih.gov/pubmed/25628650 http://dx.doi.org/10.1155/2014/761047 |
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author | Hou, Jia List, George F. Guo, Xiucheng |
author_facet | Hou, Jia List, George F. Guo, Xiucheng |
author_sort | Hou, Jia |
collection | PubMed |
description | Ways to estimate the time-to-collision are explored. In the context of traffic simulation models, classical lane-based notions of vehicle location are relaxed and new, fast, and efficient algorithms are examined. With trajectory conflicts being the main focus, computational procedures are explored which use a two-dimensional coordinate system to track the vehicle trajectories and assess conflicts. Vector-based kinematic variables are used to support the calculations. Algorithms based on boxes, circles, and ellipses are considered. Their performance is evaluated in the context of computational complexity and solution time. Results from these analyses suggest promise for effective and efficient analyses. A combined computation process is found to be very effective. |
format | Online Article Text |
id | pubmed-4297628 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-42976282015-01-27 New Algorithms for Computing the Time-to-Collision in Freeway Traffic Simulation Models Hou, Jia List, George F. Guo, Xiucheng Comput Intell Neurosci Research Article Ways to estimate the time-to-collision are explored. In the context of traffic simulation models, classical lane-based notions of vehicle location are relaxed and new, fast, and efficient algorithms are examined. With trajectory conflicts being the main focus, computational procedures are explored which use a two-dimensional coordinate system to track the vehicle trajectories and assess conflicts. Vector-based kinematic variables are used to support the calculations. Algorithms based on boxes, circles, and ellipses are considered. Their performance is evaluated in the context of computational complexity and solution time. Results from these analyses suggest promise for effective and efficient analyses. A combined computation process is found to be very effective. Hindawi Publishing Corporation 2014 2014-12-31 /pmc/articles/PMC4297628/ /pubmed/25628650 http://dx.doi.org/10.1155/2014/761047 Text en Copyright © 2014 Jia Hou et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Hou, Jia List, George F. Guo, Xiucheng New Algorithms for Computing the Time-to-Collision in Freeway Traffic Simulation Models |
title | New Algorithms for Computing the Time-to-Collision in Freeway Traffic Simulation Models |
title_full | New Algorithms for Computing the Time-to-Collision in Freeway Traffic Simulation Models |
title_fullStr | New Algorithms for Computing the Time-to-Collision in Freeway Traffic Simulation Models |
title_full_unstemmed | New Algorithms for Computing the Time-to-Collision in Freeway Traffic Simulation Models |
title_short | New Algorithms for Computing the Time-to-Collision in Freeway Traffic Simulation Models |
title_sort | new algorithms for computing the time-to-collision in freeway traffic simulation models |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4297628/ https://www.ncbi.nlm.nih.gov/pubmed/25628650 http://dx.doi.org/10.1155/2014/761047 |
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