Due to the everchanging dynamics of traffic situation, managing real-time traffic congestion with great efficiency is exceedingly challenging. Deep Reinforcement Learning (DRL) in intelligent Transportation System (IT...
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Due to the everchanging dynamics of traffic situation, managing real-time traffic congestion with great efficiency is exceedingly challenging. Deep Reinforcement Learning (DRL) in intelligent Transportation System (ITS) under the concept of Edge computing is an approach that determines the optimal traffic signal strategy for dealing with traffic congestion. Optimizing traffic signal with a DRL agent involves transmitting state information collected by edge devices. However, network congestion, device malfunctions, and transmission delays often impede the transmission of information. Consequently, the decision-making capacity of the agent suffers from inadequate information, leading to decreased efficacy. To mitigate this issue, the study proposes two distinct masking methods on input states. A single DRL agent deals with these masked inputs from the environment through the Edge devices. In order to train the agent, the DRL algorithm Proximal Policy Optimization (PPO) is implemented in five different neural network models including the state-of-the-art Transformer network which can accurately model spatial dependence and capture the persistence of sequential data. To validate the feasibility of the agent, simulation experiments are conducted in hypothetical road network and real-time road map. The experiments utilize waiting time, fuel consumption, and CO2 emission as key simulation metrics due to their significant impact on traffic congestion. However, the main goal is to alleviate traffic congestion by minimizing waiting time. Results demonstrate substantial reductions in waiting times for both networks, with reductions of 26.35% and 26.31% observed for the two masking strategies in the hypothetical scenario, and decreases of 5.86% and 6.86% recorded for the real-time road map, highlighting significant improvements in congestion alleviation efforts.
LearnLytics is a cutting-edge educational web platform designed to revolutionize the way students and educators engage in the learning *** platform, which emphasizes individualized learning, providing a variety of cou...
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The proceedings contain 49 papers. The special focus in this conference is on Frontiers of intelligentcomputing: Theory and Applications. The topics include: Nepali Word Spelling Correction Using Ensemble Learning Te...
ISBN:
(纸本)9789819601462
The proceedings contain 49 papers. The special focus in this conference is on Frontiers of intelligentcomputing: Theory and Applications. The topics include: Nepali Word Spelling Correction Using Ensemble Learning Technique;the Impact of Information Security Policies and Innovations in Digital Technology on the Transformation of Healthcare in Developing Nations: A Literature Review;integrating Multi-omics and Clinical Narratives for Predictive Modeling: Genomics, Transcriptomics, Proteomics, and Medical Texts in Disease Analysis;a Comprehensive Survey of Fake Review Detection Technology;a Hybrid intelligent Decision Support System for Automating Financial Credit Evaluation;Advancing Taxation in the New Era: Enhancing Tax Ratios with the Core Tax Administration System (CTAS);Enabling Grid Stability: Harnessing μPMU Data for Data-Driven Analysis of Grid Frequency Events;machine Learning Techniques to Detect Fake News on Social Media: A Systematic Review;cutting-Edge Technology-Based Social Enterprises in India for Sustainable, Inclusive Healthcare;enhancing Telugu Sarcasm Classification Models with Word Embeddings in Imbalanced Datasets;capital Punishment: Analyzing Trends in the United States (1976–2016);exploring the Technostress Issue Among Indonesian Young Entrepreneurs;Teaching Computer Science Using Cloud-Based IDE with Perspectives in Inclusivity;Comparison of Data Encryption Standard (DES) and Advanced Encryption Standard (AES) in Security Issues of Cloud computing: A Literature Review;enhancing Corporate and Factory Training Through Game Development: A Comparative Review;usability of intelligent System in Implementing Tutoring Lesson in Education: A Literature Review;performance Efficiency of Cloud computing—A Literature Review;decentralized Finance (DeFi) Wallets: A Review of its Efficiency, Usability, and Effectiveness;Social Networks on WEB 3.0.
Blockchain-Enabled Supply Chain Management with Role-Based Access control and AES Encryption will use blockchain technology in order to enable safe, transparent, and decentralized supply chain management. Using smart ...
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Aiming at the problem of large output voltage fluctuation of the four-switch Buck-Boost (FSBB) converter when switching between Buck and Boost modes, this paper proposes an improved three-mode double-closed-loop contr...
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作者：
Nirmala, P.
Saveetha School of Engineering Department of Electronics and Communication Engineering Chennai India
In the absence of a permanent infrastructure, the networks are utilized for temporary events, military operations, and disaster recovery. A Blockchain-Enabled intelligent Vehicle Communication systems: Trust Bit Rewar...
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ISBN:
(纸本)9798331509675
In the absence of a permanent infrastructure, the networks are utilized for temporary events, military operations, and disaster recovery. A Blockchain-Enabled intelligent Vehicle Communication systems: Trust Bit Rewards and Clustering for Autonomous Vehicles (BIVC-CA), an algorithm designed to ensure secure communication between devices and optimize efficient routing in intelligent vehicle systems, is also used to provide quick emergency response. Using blockchain, each vehicle is given its own Bit Trust ID to track its past data and calculate its trust levels. This system ensures transparency and trust between vehicles through cryptographic processes such as key generation, secure message encryption, and message verification, which improve overall communication security. It also includes an Emergency Vehicle Communication System (EUC) that uses OBU devices and sensors to detect collisions and send GSM-based rescue messages, greatly improving road safety and the efficiency of emergency operations. The road-based clustering model optimizes route selection considering traffic conditions and distances and organizes vehicles into clusters to ensure effective communication and coordination. Using the path distance algorithm, clustering is achieved by computing the similarity of routes and grouping accordingly for efficient route management with minimal network congestion. In addition, the model introduces a comprehensive network architecture that integrates vehicle cloud technology and blockchain technology, enabling intelligent vehicles to make quick decisions based on real-time data. With these integrated components, the BIVC-CA model provides a reliable framework for secure data transmission, intelligent routing, and rapid emergency response. This framework will ultimately improve the efficiency of intelligent vehicle systems and contribute to the development of advanced vehicle networks and smarter transportation solutions. We calculated the results with routing expe
This paper examines the adaptive prescribed-time dynamic surface control (PTDSC) problem for uncertain nonlinear systems with unknown control gains and time-varying parameter uncertainties. The spatiotemporal transfor...
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The proceedings contain 49 papers. The special focus in this conference is on Frontiers of intelligentcomputing: Theory and Applications. The topics include: Nepali Word Spelling Correction Using Ensemble Learning Te...
ISBN:
(纸本)9789819601424
The proceedings contain 49 papers. The special focus in this conference is on Frontiers of intelligentcomputing: Theory and Applications. The topics include: Nepali Word Spelling Correction Using Ensemble Learning Technique;the Impact of Information Security Policies and Innovations in Digital Technology on the Transformation of Healthcare in Developing Nations: A Literature Review;integrating Multi-omics and Clinical Narratives for Predictive Modeling: Genomics, Transcriptomics, Proteomics, and Medical Texts in Disease Analysis;a Comprehensive Survey of Fake Review Detection Technology;a Hybrid intelligent Decision Support System for Automating Financial Credit Evaluation;Advancing Taxation in the New Era: Enhancing Tax Ratios with the Core Tax Administration System (CTAS);Enabling Grid Stability: Harnessing μPMU Data for Data-Driven Analysis of Grid Frequency Events;machine Learning Techniques to Detect Fake News on Social Media: A Systematic Review;cutting-Edge Technology-Based Social Enterprises in India for Sustainable, Inclusive Healthcare;enhancing Telugu Sarcasm Classification Models with Word Embeddings in Imbalanced Datasets;capital Punishment: Analyzing Trends in the United States (1976–2016);exploring the Technostress Issue Among Indonesian Young Entrepreneurs;Teaching Computer Science Using Cloud-Based IDE with Perspectives in Inclusivity;Comparison of Data Encryption Standard (DES) and Advanced Encryption Standard (AES) in Security Issues of Cloud computing: A Literature Review;enhancing Corporate and Factory Training Through Game Development: A Comparative Review;usability of intelligent System in Implementing Tutoring Lesson in Education: A Literature Review;performance Efficiency of Cloud computing—A Literature Review;decentralized Finance (DeFi) Wallets: A Review of its Efficiency, Usability, and Effectiveness;Social Networks on WEB 3.0.
This article investigates the application of multi-stage gains in iterative learning control for stochastic system with fading channels. In stochastic systems containing channel fading, the effect of randomness on lea...
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Biometric authentication offers enhanced security and user convenience. However, variations in biometric sample quality and changes in biometric traits over time present significant challenges to maintaining accurate ...
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