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On the k nearest-neighbor path distance from the typical intersection in the Manhattan Poisson line Cox process
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Koufos, Konstantinos, Dhillon, Harpreet S., Dianati, Mehrdad and Dettmann, Carl P. (2023) On the k nearest-neighbor path distance from the typical intersection in the Manhattan Poisson line Cox process. IEEE Transactions on Mobile Computing, 22 (3). pp. 1659-1671. doi:10.1109/TMC.2021.3108067 ISSN 1536-1233.
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WRAP-k-nearest-neighbor-path-distance-typical-intersection-Koufos-2021.pdf - Accepted Version - Requires a PDF viewer. Download (2043Kb) | Preview |
Official URL: http://doi.org/10.1109/TMC.2021.3108067
Abstract
In this paper we calculate the exact cumulative distribution function (CDF) of the path distance (L1 norm) between a randomly selected intersection and the k-th nearest node of the Cox point process driven by the Manhattan Poisson line process. The CDF is expressed as a sum over the integer partition function p(k) , which allows us to numerically evaluate the CDF in a simple manner. The distance distributions can be used to study the k-coverage of broadcast signals in intelligent transportation systems (ITS) transmitted from a \ac{RSU} that is located at an intersection. They can also be insightful for network dimensioning in urban vehicle-to-everything (V2X) systems, because they can yield the exact distribution of network load within a cell, provided that the \ac{RSU} is located at an intersection. Finally, they can find useful applications in other branches of science like spatial databases, emergency response planning, and districting. We corroborate the applicability of the distance distribution model using the map of an urban area.
| Item Type: | Journal Article | |||||||||
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| Subjects: | Q Science > QA Mathematics T Technology > TE Highway engineering. Roads and pavements |
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| Divisions: | Faculty of Science, Engineering and Medicine > Engineering > WMG (Formerly the Warwick Manufacturing Group) | |||||||||
| Library of Congress Subject Headings (LCSH): | Vehicular ad hoc networks (Computer networks), Intelligent transportation systems, Intelligent transportation systems -- Mathematical models | |||||||||
| Journal or Publication Title: | IEEE Transactions on Mobile Computing | |||||||||
| Publisher: | IEEE | |||||||||
| ISSN: | 1536-1233 | |||||||||
| Official Date: | 1 March 2023 | |||||||||
| Dates: |
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| Volume: | 22 | |||||||||
| Number: | 3 | |||||||||
| Page Range: | pp. 1659-1671 | |||||||||
| DOI: | 10.1109/TMC.2021.3108067 | |||||||||
| Status: | Peer Reviewed | |||||||||
| Publication Status: | Published | |||||||||
| Reuse Statement (publisher, data, author rights): | © 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | |||||||||
| Access rights to Published version: | Restricted or Subscription Access | |||||||||
| Date of first compliant deposit: | 14 September 2021 | |||||||||
| Date of first compliant Open Access: | 16 September 2021 | |||||||||
| RIOXX Funder/Project Grant: |
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