Výsledky vyhľadávania - "Modeling and Control of Traffic Flow Systems"

Ensemble Learning-based Algorithms for Traffic Flow Prediction in Smart Traffic Systems

Autori: Anas Saleh Alkarim Abdullah AL-Malaise AL-Ghamdi Mahmoud Ragab

Zdroj: Engineering, Technology & Applied Science Research. 14:13090-13094

Predmety: 0209 industrial biotechnology, Artificial intelligence, Social Sciences, Understanding Attitudes Towards Public Transport and Private Car, Transportation, Traffic flow (computer networking), 02 engineering and technology, Traffic Flow Prediction and Forecasting, Building and Construction, 15. Life on land, Computer science, 7. Clean energy, 3. Good health, Algorithm, Engineering, Control and Systems Engineering, Computer security, 13. Climate action, Ensemble learning, Physical Sciences, Machine learning, 11. Sustainability, 0202 electrical engineering, electronic engineering, information engineering, Modeling and Control of Traffic Flow Systems

Multi-objective Optimization Framework for Trade-Off Among Pedestrian Delays and Vehicular Emissions at Signal-Controlled Intersections

Autori: Görkem Akyol Sadullah Göncü Mehmet Ali Silgu a ďalší

Prispievatelia: Görkem Akyol Sadullah Göncü Mehmet Ali Silgu a ďalší

Zdroj: Arabian Journal for Science and Engineering. 49:14117-14130

Predmety: Traffic Optimal Signal Setting, Traffic signal control, FOS: Mechanical engineering, Social Sciences, Traffic Signal Control, Estimating Vehicle Fuel Consumption and Emissions, Transportation, 02 engineering and technology, Traffic control model, 7. Clean energy, Environmental science, Real-time computing, Traffic signal, Engineering, Machine learning, 0502 economics and business, 11. Sustainability, 0202 electrical engineering, electronic engineering, information engineering, Traffic optimal signal setting, Multi-Objective Optimization, 05 social sciences, Traffic Control Model, Understanding Attitudes Towards Public Transport and Private Car, Pedestrian, Transport engineering, Computer science, Programming language, Multi-objective optimization, Signal timing, Control and Systems Engineering, 13. Climate action, SIGNAL (programming language), Automotive Engineering, Physical Sciences, Modeling and Control of Traffic Flow Systems

Popis súboru: application/pdf

Prístupová URL adresa: https://hdl.handle.net/11772/19646

Enhancing Road Safety and Cybersecurity in Traffic Management Systems: Leveraging the Potential of Reinforcement Learning

Autori: Ishita Agarwal Ashmi Singh A. Agarwal a ďalší

Zdroj: IEEE Access, Vol 12, Pp 9963-9975 (2024)

Predmety: reinforcement learning, Artificial intelligence, Traffic Signal Control, Cyber security, 7. Clean energy, Intelligent Transportation Systems, Engineering, Computer security, Reinforcement learning, 11. Sustainability, Risk analysis (engineering), Business, Intelligent transportation system, 4. Education, Traffic Flow Prediction and Forecasting, Building and Construction, Transport engineering, traffic management systems, Reinforcement Learning, Computer science, TK1-9971, Integration of Cyber, Physical, and Social Systems, Control and Systems Engineering, 13. Climate action, Physical Sciences, Electrical engineering. Electronics. Nuclear engineering, road safety, Modeling and Control of Traffic Flow Systems

Prístupová URL adresa: https://doaj.org/article/c7be3ae1bc5840a6838fd9ae40dc77c8

Micro-Simulation Insights into the Safety and Operational Benefits of Autonomous Vehicles

Autori: Nalin Kumar Sekar Vinayak Malaghan Digvijay S. Pawar

Zdroj: Journal of Intelligent and Connected Vehicles, Vol 6, Iss 4, Pp 202-210 (2023)

Predmety: Astronomy, Trajectory, FOS: Mechanical engineering, Automotive engineering, Crash, 7. Clean energy, Driver Assistance Systems, driving logics and safety impacts, Engineering, Implications of Shared Autonomous Vehicle Services, VisSim, 11. Sustainability, Microsimulation, Motor vehicles. Aeronautics. Astronautics, Physics, Traffic simulation, TL1-4050, Transport engineering, Autonomous Vehicle Adoption, Computer science, Programming language, Collision Avoidance, Geotechnical engineering, Control and Systems Engineering, Electrical engineering, Physical Sciences, Automotive Engineering, Market penetration, automated vehicles, driving behavior, penetration rates, Autonomous Vehicle Technology and Safety Systems, Modeling and Control of Traffic Flow Systems, Penetration rate, Simulation, Microscopic Simulation

Popis súboru: pdf

Prístupová URL adresa: https://doaj.org/article/a0a0c045ad4d40c6ba2bc8e527cbb633

BiLSTM- and GNN-Based Spatiotemporal Traffic Flow Forecasting with Correlated Weather Data

Autori: Abdullah Alourani Farzeen Ashfaq N. Z. Jhanjhi a ďalší

Zdroj: Journal of Advanced Transportation, Vol 2023 (2023)

Predmety: Artificial neural network, Artificial intelligence, Social Sciences, Traffic Assignment, Transportation, Traffic flow (computer networking), 02 engineering and technology, Graph, Intelligent Transportation Systems, Engineering, Theoretical computer science, Computer security, 11. Sustainability, 0502 economics and business, 0202 electrical engineering, electronic engineering, information engineering, FOS: Mathematics, Data mining, HE1-9990, TA1001-1280, Urban Traffic, 05 social sciences, Statistics, Understanding Attitudes Towards Public Transport and Private Car, Traffic Flow Prediction and Forecasting, Building and Construction, Transport engineering, Computer science, Transportation engineering, Control and Systems Engineering, Physical Sciences, Mean squared error, Modeling and Control of Traffic Flow Systems, Traffic Flow, Short-Term Forecasting, Transportation and communications, Traffic volume, Mathematics

Popis súboru: text/xhtml

Prístupová URL adresa: https://doaj.org/article/043924aa18f64ecb99a2eac0eb35fc40

Sustainable Hydrodynamic of Artificial Neural Networks and Logistic Regression Model to Lane Change Serious Conflict at Unsignalized Intersection on Malaysia’s Federal Route

Autori: Fajaruddin Mustakim Mohammad Nazir Ahmad Rabiah Abdul Kadir a ďalší

Zdroj: Journal of BioMed Research and Reports. 2:1-16

Predmety: Artificial neural network, Artificial intelligence, Logistic regression, Traffic Flow Prediction and Forecasting, Building and Construction, Transport engineering, 15. Life on land, Reinforcement Learning, Computer science, 7. Clean energy, 12. Responsible consumption, Engineering, Control and Systems Engineering, 13. Climate action, Physical Sciences, Machine learning, 11. Sustainability, Intersection (aeronautics), Modeling and Control of Traffic Flow Systems

Safe, Efficient, and Comfortable Reinforcement-Learning-Based Car-Following for AVs with an Analytic Safety Guarantee and Dynamic Target Speed

Autori: Omar ElSamadisy Tianyu Shi Ilia Smirnov a ďalší

Zdroj: Transportation Research Record: Journal of the Transportation Research Board. 2678:643-661

Predmety: 0301 basic medicine, Artificial intelligence, Crash Prediction Models, Economics, Acceleration, FOS: Mechanical engineering, Control (management), Automotive engineering, Crash, 03 medical and health sciences, Engineering, 0502 economics and business, Reinforcement learning, Control theory (sociology), Microeconomics, Analysis of Traffic Safety and Driver Behavior, Classical mechanics, Constraint (computer-aided design), Safety, Risk, Reliability and Quality, Biology, Cooperative Adaptive Cruise Control, Physics, 05 social sciences, Controller (irrigation), Urban Driving, Jerk, Reinforcement Learning, Computer science, Mechanical engineering, Agronomy, Programming language, Collision Avoidance, Control and Systems Engineering, Cruise control, Headway, Physical Sciences, Automotive Engineering, Maximization, Autonomous Vehicle Technology and Safety Systems, Modeling and Control of Traffic Flow Systems, Simulation

Multi-Agent and Fuzzy Inference-Based Framework for Traffic Light Optimization

Autori: Abdelouafi Ikidid Abdelaziz El Fazziki Mohamed Sadgal

Zdroj: Re-Unir. Archivo Institucional de la Universidad Internacional de La Rioja
Universidad Internacional de La Rioja (UNIR)
International Journal of Interactive Multimedia and Artificial Intelligence, Vol 8, Iss 2, Pp 88-97 (2023)

Predmety: Technology, Artificial intelligence, coordination, communications, Social Sciences, Traffic Assignment, Transportation, 02 engineering and technology, Real-time computing, Traffic signal, Engineering, 0202 electrical engineering, electronic engineering, information engineering, traffic, IJIMAI, Understanding Attitudes Towards Public Transport and Private Car, Traffic Flow Prediction and Forecasting, Building and Construction, Transport engineering, Computer science, Throughput, Distributed computing, agents, Programming language, Fuzzy logic, Control and Systems Engineering, SIGNAL (programming language), Physical Sciences, Telecommunications, Wireless, fuzzy logic, Intersection (aeronautics), Modeling and Control of Traffic Flow Systems, Traffic Flow

Prístupová URL adresa: https://doaj.org/article/eadaedce3da64c449d3c164f50e67600
https://reunir.unir.net/handle/123456789/14325

Intelligent Four-Way Crossroad Safety Management For Autonomous, Non-Autonomous and VIP Vehicles

Autori: Awad Bin Naeem Abdul Majid Soomro Abhishek Bhuva a ďalší

Zdroj: 2023 IEEE International Conference on Emerging Trends in Engineering, Sciences and Technology (ICES&T). :1-6

Predmety: Urban Driving, FOS: Mechanical engineering, Traffic Flow Prediction and Forecasting, Building and Construction, Transport engineering, 15. Life on land, Automotive engineering, Computer science, 7. Clean energy, Real-time computing, Intelligent Transportation Systems, Driver Assistance Systems, Collision Avoidance, Engineering, Operations management, Control and Systems Engineering, Physical Sciences, Automotive Engineering, 11. Sustainability, Autonomous Vehicle Technology and Safety Systems, Intersection (aeronautics), Intelligent transportation system, Modeling and Control of Traffic Flow Systems, Lane Detection, Scheduling (production processes)

Intelligent Driver Model-Based Vehicular Ad Hoc Network Communication in Real-Time Using 5G New Radio Wireless Networks

Autori: Rashid Ali Ran Liu Anand Nayyar a ďalší

Zdroj: IEEE Access, Vol 11, Pp 4956-4971 (2023)

Predmety: fifth generation, intelligent driver model, Flexibility (engineering), Vehicle-to-vehicle, FOS: Mechanical engineering, Vehicular Ad Hoc Networks, 02 engineering and technology, Quantum mechanics, 7. Clean energy, Intelligent Transportation Systems, Internet of Vehicles, Engineering, Vehicular communication systems, Connected Vehicles, 11. Sustainability, FOS: Electrical engineering, electronic engineering, information engineering, FOS: Mathematics, 0202 electrical engineering, electronic engineering, information engineering, Civil engineering, vehicle-to-vehicle, Electrical and Electronic Engineering, Intelligent transportation system, Communications system, Wireless network, Computer network, 9. Industry and infrastructure, Physics, Statistics, VANET Security, Wireless ad hoc network, Power (physics), Vehicular ad hoc network, Computer science, TK1-9971, 3. Good health, internet of vehicles, Reliability (semiconductor), SUMO, Control and Systems Engineering, Physical Sciences, Automotive Engineering, Wireless, Telecommunications, Vehicular Ad Hoc Networks and Communications, Electrical engineering. Electronics. Nuclear engineering, Autonomous Vehicle Technology and Safety Systems, Modeling and Control of Traffic Flow Systems, FOS: Civil engineering, Mathematics

Prístupová URL adresa: https://doaj.org/article/68439182a8b8420fa4a3207cae45d611

Fuzzy logic-based vehicle safety estimation using V2V communications and on-board embedded ROS-based architecture for safe traffic management system in hail city

Autori: Ismail Ben Abdallah Yassine Bouteraa Saleh Mobayen a ďalší

Zdroj: Electronic Research Archive, Vol 31, Iss 8, Pp 5083-5103 (2023)

Predmety: Artificial intelligence, robot operating system, FOS: Mechanical engineering, Vehicular Ad Hoc Networks, Real-time computing, Visual arts, Intelligent Transportation Systems, Internet of Vehicles, Engineering, Architecture, 11. Sustainability, QA1-939, FOS: Electrical engineering, electronic engineering, information engineering, Electrical and Electronic Engineering, Embedded system, T57-57.97, Computer network, Applied mathematics. Quantitative methods, Urban Driving, safety estimation, Path (computing), Computer science, Fuzzy logic, v2v, Control and Systems Engineering, Automotive Engineering, Physical Sciences, real-time system, Vehicular Ad Hoc Networks and Communications, fuzzy logic, Autonomous Vehicle Technology and Safety Systems, V2X Communications, Classifier (UML), Modeling and Control of Traffic Flow Systems, Mathematics, FOS: Civil engineering, Art

Prístupová URL adresa: https://doaj.org/article/1b761eb82900468c8177bc93a84e6cc9

Lane Detection in Autonomous Vehicles: A Systematic Review

Autori: Noor Jannah Zakaria Mohd Ibrahim Shapiai Rasli Abd Ghani a ďalší

Zdroj: IEEE Access, Vol 11, Pp 3729-3765 (2023)

Predmety: geometric modelling, Artificial intelligence, FOS: Mechanical engineering, Lane departure warning system, 02 engineering and technology, Lane detection, Driver Assistance Systems, Autonomous Driving, Automation, Engineering, Segmentation, 11. Sustainability, 0202 electrical engineering, electronic engineering, information engineering, Intelligent transportation system, 05 social sciences, systematic literature review, Warning system, Mechanical engineering, 3. Good health, Collision Avoidance, Advanced driver assistance systems, machine learning, Physical Sciences, Telecommunications, Deep Learning in Computer Vision and Image Recognition, Electrical engineering. Electronics. Nuclear engineering, Computer Vision and Pattern Recognition, Object detection, Control (management), T Technology (General), Machine learning, 0502 economics and business, Software engineering, autonomous vehicle, Urban Driving, deep learning, Deep learning, Transport engineering, 15. Life on land, Computer science, TK1-9971, Control and Systems Engineering, Cruise control, Implementation, Automotive Engineering, Computer Science, Autonomous Vehicle Technology and Safety Systems, Modeling and Control of Traffic Flow Systems, Lane Detection

Popis súboru: application/pdf

Prístupová URL adresa: https://doaj.org/article/e414fe71b9844807910d301405ac3aee

Toward Learning Human-Like, Safe and Comfortable Car-Following Policies With a Novel Deep Reinforcement Learning Approach

Autori: M. Ugur Yavas Tufan Kumbasar Nazım Kemal Üre

Zdroj: IEEE Access, Vol 11, Pp 16843-16854 (2023)

Predmety: reinforcement learning, Artificial intelligence, Social Psychology, FOS: Mechanical engineering, Social Sciences, 7. Clean energy, Driver Assistance Systems, Engineering, Human Interaction with Automation Systems, Reinforcement learning, 11. Sustainability, 0502 economics and business, Psychology, 14. Life underwater, Cooperative Adaptive Cruise Control, Driver Behavior, Human–computer interaction, 4. Education, 05 social sciences, deep learning, Driver Distraction, Reinforcement Learning, Computer science, advanced driving assistance systems, TK1-9971, Adaptive cruise control, FOS: Psychology, naturalistic driving, Control and Systems Engineering, 13. Climate action, Physical Sciences, Automotive Engineering, Electrical engineering. Electronics. Nuclear engineering, Autonomous Vehicle Technology and Safety Systems, Modeling and Control of Traffic Flow Systems

Prístupová URL adresa: https://doaj.org/article/b5a59a614b494475ba90104bae18adb6

Analyzing the effect of fixed and moving bottlenecks on traffic flow and car accidents in a two-lane cellular automaton model

Autori: A. Laarej azeddine Karakhi N. Lakouari a ďalší

Zdroj: Journal of Applied Engineering Science. 21:1179-1191

Predmety: Collision, Artificial intelligence, Travel time, Social Sciences, Transportation, Traffic flow (computer networking), Control (management), Mechanics, 7. Clean energy, Bottleneck, Real-time computing, Database, Engineering, Computer security, 11. Sustainability, Theory and Applications of Cellular Automata, Control theory (sociology), Embedded system, Cellular automaton, Computer network, Diagram, Physics, Understanding Attitudes Towards Public Transport and Private Car, Transport engineering, Computer science, Algorithm, Computational Theory and Mathematics, Control and Systems Engineering, 13. Climate action, Physical Sciences, Computer Science, Vehicle Dynamics Model, Modeling and Control of Traffic Flow Systems, Flow (mathematics), Simulation

InTAS - The Ingolstadt Traffic Scenario for SUMO

Autori: Silas Lobo Stefan Neumeier Evelio Fernández a ďalší

Zdroj: SUMO Conference Proceedings, Vol 1 (2022)

Predmety: FOS: Computer and information sciences, VANET, FOS: Mechanical engineering, Vehicular Ad Hoc Networks, 02 engineering and technology, Real-time computing, Intelligent Transportation Systems, Computer Science - Networking and Internet Architecture, Internet of Vehicles, realistic traffic scenario, traffic modelling, Engineering, Implications of Shared Autonomous Vehicle Services, Computer security, 0502 economics and business, 11. Sustainability, FOS: Electrical engineering, electronic engineering, information engineering, 0202 electrical engineering, electronic engineering, information engineering, Electrical and Electronic Engineering, Intelligent transportation system, HE1-9990, Road traffic, Networking and Internet Architecture (cs.NI), SAFER, Public Transit Integration, 05 social sciences, Transport engineering, Computer science, realistic traffic scenario, traffic modelling, VANET, SUMO, SUMO, Control and Systems Engineering, Physical Sciences, Automotive Engineering, V2X, Vehicular Ad Hoc Networks and Communications, Road traffic safety, Modeling and Control of Traffic Flow Systems, Transportation and communications, Simulation

Prístupová URL adresa: http://arxiv.org/abs/2011.11995
https://doaj.org/article/446df963590f46bea48c92a475a5f6fb

Lateral control for autonomous wheeled vehicles: A technical review

Autori: Kebbati, Yassine Aït Oufroukh, Naïma Ichalal, Dalil a ďalší

Prispievatelia: Kebbati, Yassine Aït Oufroukh, Naïma Ichalal, Dalil a ďalší

Zdroj: Asian Journal of Control. 25:2539-2563

Predmety: Optimization, [INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], Artificial intelligence, 0209 industrial biotechnology, [INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing, Vehicle Dynamics, FOS: Mechanical engineering, Control (management), [MATH] Mathematics [math], 02 engineering and technology, [INFO] Computer Science [cs], Engineering, Automated driving, Field (mathematics), 11. Sustainability, FOS: Mathematics, 0202 electrical engineering, electronic engineering, information engineering, Model-based control, Driver Assistance, Control engineering, Modeling, Urban Driving, Pure mathematics, Active Steering, Transport engineering, Computer science, Control and Systems Engineering, Advanced Vehicle Dynamics Control Systems, Path tracking, Automotive Engineering, Physical Sciences, Autonomous Vehicle Technology and Safety Systems, Modeling and Control of Traffic Flow Systems, Lane Detection, Mathematics

Popis súboru: application/pdf

Prístupová URL adresa: https://hal.science/hal-04371558v1
https://doi.org/10.1002/asjc.2980
https://hal.science/hal-04371558v1/document

A Fuzzy Logic-Based Smart Traffic Management Systems

Autori: Adel Abdallah Abdou Mohamed Hassan Farrag A. S. Tolba

Zdroj: Journal of Computer Science. 18:1085-1099

Predmety: Artificial intelligence, Internet of Things, Social Sciences, Traffic Assignment, Transportation, Traffic Signal Control, Traffic flow (computer networking), 02 engineering and technology, 7. Clean energy, Real-time computing, Intelligent Transportation Systems, Engineering, Congestion Pricing, 11. Sustainability, 0502 economics and business, 0202 electrical engineering, electronic engineering, information engineering, Embedded system, Smart city, Computer network, 05 social sciences, 1. No poverty, Understanding Attitudes Towards Public Transport and Private Car, Traffic Flow Prediction and Forecasting, Building and Construction, Transport engineering, Computer science, 3. Good health, Fuzzy logic, Fuzzy control system, Control and Systems Engineering, 13. Climate action, Physical Sciences, Modeling and Control of Traffic Flow Systems, Traffic Flow, Traffic congestion

SMART TRAFFIC SIGNAL CONTROL SYSTEM FOR TWO INTER-DEPENDENT INTERSECTIONS IN AKURE, NIGERIA

Autori: AJIBESIN SAMSON PONNLE AKINLOLU OYEDEPO OLUGBENGA

Zdroj: Journal of Engineering Studies and Research, Vol 28, Iss 3 (2022)

Predmety: Technology, Artificial intelligence, Population, FOS: Mechanical engineering, Traffic Signal Control, Control (management), 7. Clean energy, Real-time computing, Visual Object Tracking and Person Re-identification, Intelligent Transportation Systems, Traffic signal control, Intersection, Smart transport systems, Computer Vision, Vehicle Detection, You Only Look Once (YOLO), Traffic signal, Engineering, Sociology, 11. Sustainability, Work (physics), Intelligent transportation system, Cooperative Adaptive Cruise Control, Traffic congestion reconstruction with Kerner's three-phase theory, Traffic optimization, Demography, Traffic Flow Prediction and Forecasting, Building and Construction, Transport engineering, Engineering (General). Civil engineering (General), Computer science, Mechanical engineering, FOS: Sociology, Programming language, Control and Systems Engineering, SIGNAL (programming language), Physical Sciences, Computer Science, Traffic system, Floating car data, Traffic wave, Computer Vision and Pattern Recognition, TA1-2040, Modeling and Control of Traffic Flow Systems, Traffic Flow, Traffic congestion, Simulation

Prístupová URL adresa: https://doaj.org/article/602367e8e5174006aac730864b7dafdb
https://doaj.org/article/1062f77760cd4b549df501bd49f28987

A Comprehensive Survey on the Application of Deep and Reinforcement Learning Approaches in Autonomous Driving

Autori: Badr Ben Elallid Nabil Benamar Abdelhakim Hafid a ďalší

Zdroj: Journal of King Saud University - Computer and Information Sciences. 34:7366-7390

Predmety: Artificial intelligence, FOS: Mechanical engineering, 02 engineering and technology, 7. Clean energy, Driver Assistance Systems, Intelligent Transportation Systems, Data science, Engineering, Connected Vehicles, Reinforcement learning, 11. Sustainability, 0502 economics and business, 0202 electrical engineering, electronic engineering, information engineering, 10. No inequality, Human–computer interaction, 05 social sciences, Urban Driving, Traffic Flow Prediction and Forecasting, Building and Construction, 15. Life on land, Reinforcement Learning, Computer science, 3. Good health, World Wide Web, Control and Systems Engineering, Automotive Engineering, Physical Sciences, Autonomous Vehicle Technology and Safety Systems, Open research, Modeling and Control of Traffic Flow Systems

Predicting vehicle travel time on city streets for trip preplanning and predicting heavy traffic for proactive control of street congestion

Autori: Samer Nofal

Zdroj: Sci Rep
Scientific Reports, Vol 14, Iss 1, Pp 1-21 (2024)

Predmety: Artificial intelligence, Travel time, Traffic control, Science, Social Sciences, Transportation, Control (management), 02 engineering and technology, Heavy traffic, Operations research, 7. Clean energy, Article, Intelligent Transportation Systems, Engineering, Congestion Pricing, Machine learning, 0502 economics and business, 11. Sustainability, 0202 electrical engineering, electronic engineering, information engineering, Urban Traffic, 05 social sciences, Understanding Attitudes Towards Public Transport and Private Car, Traffic Flow Prediction and Forecasting, Building and Construction, Transport engineering, 15. Life on land, Computer science, Traffic prediction, Time series traffic data, Control and Systems Engineering, 13. Climate action, Physical Sciences, Medicine, Modeling and Control of Traffic Flow Systems, Short-Term Forecasting, Traffic congestion, Probabilistic Forecasting

Prístupová URL adresa: https://pubmed.ncbi.nlm.nih.gov/38714884
https://doaj.org/article/9d1d72cfc84c41bd9dd5c7608ef86a80