[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-126689-en":3,"doc-seo-126689-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},126689,962084925636,"Olivia Brown","https://ap-avatar.wpscdn.com/davatar_994ba38a5ba835b3df7d355c54d3ed8d",8,"Research & Report","PMLC - Predictions of Mobility and Transmission in a Lane-Based Cluster VANET Validated on Machine Learning","VANET is a large-scale communication network requiring precise protocols and routing to support vehicles and roadside infrastructure. The proposed PMLC protocol is designed for lane-based road environments using cluster routing, forming clusters and electing leaders through multilayer estimations. Vehicle movement and data-transfer behavior are quantified from collected simulation data, and accurate values are derived using machine learning. A neural network processes inputs, selects an appropriate leader, and forwards data to the destination, with protocol execution illustrated graphically.","PMLC-Predictions of Mobility and Transmission ina Lane-Based Cluster VANET Validated on  \nMachine Learning  \nRadha Krishna Karne1, Dr. T. K. Sreeja2  \n1Electronics and Communication Engineering Noorul Islam Centre for Higher Education,  \nKumaracoil, Kanyakumari, TamilNadu, India  \n[krk.wgl@gmail.com](krk.wgl@gmail.com)  \n2Electronics and Communication Engineering Noorul Islam Centre for Higher Education,  \nKumaracoil, Kanyakumari, TamilNadu, India  \n[sreejaeng07@gmail.com](sreejaeng07@gmail.com)  \nAbstract—VANET refers to a massive network system, to communicate with each vehicle or infrastructure a precision protocol, an advanced view and routing system is required. This means of communication should be appropriate for all kind of vehicles. In this proposed PMLC protocol, which was built on cluster routing in a lane-based road environment. The network requires optimal solutions to form the cluster and choose its leader. All road environment characteristics are chosen, and multilayer estimations are generated to obtain specific deviations and variations, which are calculated based on data transfer and vehicle movement, and exact values are found using the machine learning system. The neural network processes the inputs, selects the required leader, and sends the data to the destination. At the end of this explanation, the execution of this protocol is depicted graphically.  \nKeywords-VANET; Cluster Routing; Lane-Based Road; Leader Election; Neural Optimization; Machine Learning Process  \nI. INTRODUCTION  \nThe wireless connections made by vehicles are very subtle. The speed of vehicles on the roads varies from very fast to very slow. As well as they will travel very quickly from one vehicle to another near or in a different direction. So, their contact time will be very short. In this scenario the protocol also requires a proper network setup to send the data over the wireless connection. Roads are divided into two, three or four lanes when traveling on national highways. Thus, they require proper routing to share data on the roads. That network will erode very quickly. You need to find it and update the routing again. This method is applicable to all types of vehicles traveling on the roads. Vehicles can communicate directly with each other, or they can communicate with road side units in an infrastructural manner. In this infrastructure, the road side unit connects to the internet server through the gateway and adds information or receives the information and gives it to the vehicles. This creates VANET connections as shown in Figure.1 .  \nIn this network, data is collected by simulation and the data is processed by a machine learning system and its performance is tested. This allows to determine the quality of the network. The data should be initially evaluated through the training set, then convert another to a testing set to determine the correctness of the data. If the correctness is low, select the parameters needed  \nto create the network again, repeat iteratively this process to get more precision.  \nIn proposed, the VANET framework is developed in the form of traffic with the model of vehicles traveling on the roads. The design explains how to optimize the wireless communication systems required on the roads and how to transmit data and regulate difficulties. Every vehicle in the network has some features. The cluster is formed in the network by those features. Leaders are selected in each cluster. The cluster network is constantly updated at regular intervals. It involves cluster forming, merging, cluster switching, selecting a new leader, and stabilizing the network connection. This allows data transfer on the VANET to take place over a short period of time.  \nFigure.1 VANET Communication  \nIn this VANET proposal, the vehicle adhoc network is developed as well as the path selection is based on a clustering system. The data transmitted in it is optimized and provided by the machine learning system. The parameters for","cbCaib6E0qY685Aq","https://ap.wps.com/l/cbCaib6E0qY685Aq","pdf",307996,1,7,"English","en",105,"# Introduction\n# Related Work","[{\"question\":\"What problem does the PMLC protocol address in VANETs?\",\"answer\":\"It addresses the need for optimal cluster formation and routing in lane-based road environments, including selecting an effective cluster leader for data transmission.\"},{\"question\":\"How is leader selection performed in the proposed method?\",\"answer\":\"Noise levels in the communication channel of neighboring vehicles are detected, and neighbors with higher noise are excluded from the leader election so the chosen leader can broadcast with minimal data loss.\"},{\"question\":\"How does machine learning contribute to mobility and transmission prediction?\",\"answer\":\"Simulation data is evaluated using training and testing sets, and multilayer estimations are used to compute deviations and variations. A neural network then uses these inputs to predict and support data forwarding decisions.\"}]","PMLC - Predictions of Mobility and Transmission in a Lane-Based Cluster VANET Validated on Machine Learning | PDF",1785934239,18,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"pmlc-predictions-of-mobility-and-transmission-in-a-lane-based-cluster-vanet-validated-on-machine-learning","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/pmlc-predictions-of-mobility-and-transmission-in-a-lane-based-cluster-vanet-validated-on-machine-learning/126689/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-05",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"What problem does the PMLC protocol address in VANETs?","Question",{"text":75,"@type":76},"It addresses the need for optimal cluster formation and routing in lane-based road environments, including selecting an effective cluster leader for data transmission.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How is leader selection performed in the proposed method?",{"text":80,"@type":76},"Noise levels in the communication channel of neighboring vehicles are detected, and neighbors with higher noise are excluded from the leader election so the chosen leader can broadcast with minimal data loss.",{"name":82,"@type":73,"acceptedAnswer":83},"How does machine learning contribute to mobility and transmission prediction?",{"text":84,"@type":76},"Simulation data is evaluated using training and testing sets, and multilayer estimations are used to compute deviations and variations. 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