Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/310751
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DC Field | Value | Language |
---|---|---|
dc.coverage.spatial | ||
dc.date.accessioned | 2021-01-06T09:25:15Z | - |
dc.date.available | 2021-01-06T09:25:15Z | - |
dc.identifier.uri | http://hdl.handle.net/10603/310751 | - |
dc.description.abstract | A highway street vehicle crash or impact happens when a newlinevehicle slams into another vehicle or a fixed framework or a walker in newlinea thruway street. This may make harm the foundation, passing and newlinedamage to individuals at times. A few variables are the main drivers newlineof these mishaps, for example, poor vehicle plan, over speed, parkway newlinestreet configuration, experience or expertise of the driver, annoyance newlineand street condition. The Mishap counteractive action is a required newlineproactive procedure in arranging, planning and acting in order to stop newlineor stay away from a mishap before it happens. The main objective of newlinethis proposal is to develop security applications in VANET and newlineimplement the efficient communication between the vehicles by newlinereducing the real time complications using DNN. newline The vehicles running in different environments can be newlinecommunicating each other using some architectures and protocols. newlineThe communication can be possible with vehicle to vehicle (V2V) or newlinevehicle to some pre erected infrastructures (V2I). This work proposes newlinethe Zone Hierarchical Link State protocol (ZHLS) with gate flooding, newlinewhich is the sub classification of topology based hybrid routing newlineprotocol which implements the hybrid architecture of both V2V and newlineV2I in the Intelligent VANET. The proposed architecture is controlled newlineand operated by the Deep Neural Network (DNN) and the outcomes newlineof the proposal are simulated with MATLAB. newlineThe Intelligent Transport Systems (ITS) for improving the road newlinesafety on highways shares the information about traffic conditions to newlineother vehicles. A self-arranging MAC is attempted and it permits newlinevehicles to identify collision warning way before passing information. newlineThe Vehicles gets the channel by TDMA access. The simulation newlineresults shows the proposed methodologies can considerably decrease newlinethe packet loss and delay in collision warning system in high newlinecollisions situations. Finally the current methodologies customizing newlinethe channel access probabilities in vehicular ad hoc network. The NS2 newlinesimulation output denote the reduction of traffic crash possibilities, newlinethus it has vast advantages in other non-ideal systems. newline newline | |
dc.format.extent | ||
dc.language | English | |
dc.relation | ||
dc.rights | university | |
dc.title | Improving Safety on Highways by Customizing Vehicular Adhoc Networks | |
dc.title.alternative | ||
dc.creator.researcher | VENKATESAN, M | |
dc.subject.keyword | Engineering | |
dc.subject.keyword | Engineering and Technology | |
dc.subject.keyword | Engineering Electrical and Electronic | |
dc.description.note | ||
dc.contributor.guide | SELVAKUMAR RAJA, S | |
dc.publisher.place | Chennai | |
dc.publisher.university | Bharath University | |
dc.publisher.institution | Department of Electronics and Communication Engineering | |
dc.date.registered | ||
dc.date.completed | 2019 | |
dc.date.awarded | ||
dc.format.dimensions | ||
dc.format.accompanyingmaterial | DVD | |
dc.source.university | University | |
dc.type.degree | Ph.D. | |
Appears in Departments: | Department of Electronics and Communication Engineering |
Files in This Item:
File | Description | Size | Format | |
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80_recommendation.pdf | Attached File | 186.37 kB | Adobe PDF | View/Open |
certificate.pdf | 367.78 kB | Adobe PDF | View/Open | |
chapter 1.pdf | 460.85 kB | Adobe PDF | View/Open | |
chapter 2.pdf | 335.8 kB | Adobe PDF | View/Open | |
chapter 3.pdf | 879.24 kB | Adobe PDF | View/Open | |
chapter 4.pdf | 628.34 kB | Adobe PDF | View/Open | |
chapter 5.pdf | 567.31 kB | Adobe PDF | View/Open | |
chapter 6.pdf | 316.51 kB | Adobe PDF | View/Open | |
chapter 7.pdf | 1.52 MB | Adobe PDF | View/Open | |
chapter 8.pdf | 86.59 kB | Adobe PDF | View/Open | |
preliminary pages.pdf | 215.45 kB | Adobe PDF | View/Open | |
references.pdf | 188.65 kB | Adobe PDF | View/Open | |
title page.pdf | 106.69 kB | Adobe PDF | View/Open |
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