The real-time vehicular traffic system is an integral part of the urban vehicular traffic system, which provides effective traffic signal control for a large multifaceted traffic network and is a highly challenging distributed control problem. Coordinating vehicular traffic enables the network model to deliver an efficient service flow. Consider that there are four lanes of vehicular traffic in this situation, allowing parallel vehicle movements to occur without causing an accident. In this instance, the vehicular system's control parameters are time and vehicle volume. In this work, vehicular traffic flow is examined, and an algorithm to estimate vehicle waiting time in each direction is estimated. The effectiveness of the proposed vehicle traffic signal distribution control system by comparing the experimental results with a real-time vehicular traffic system is verified. This is also illustrated numerically.
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http://dx.doi.org/10.3390/s23156819 | DOI Listing |
Environ Pollut
January 2025
University of Southern California, Department of Civil and Environmental Engineering, Los Angeles, CA, USA. Electronic address:
Airborne particulate matter (PM) in urban environments poses significant health risks by penetrating the respiratory system, with concern over lung-deposited surface area (LDSA) as an indicator of particle exposure. This study aimed to investigate the diurnal trends and sources of LDSA, particle number concentration (PNC), elemental carbon (EC), and organic carbon (OC) concentrations in Los Angeles across different seasons to provide a comprehensive understanding of the contributions from primary and secondary sources of ultrafine particles (UFPs). Hourly measurements of PNC and LDSA were conducted using the DiSCmini and Scanning Mobility Particle Sizer (SMPS), while OC and EC concentrations were measured using the Sunset Lab EC/OC Monitor.
View Article and Find Full Text PDFSci Rep
December 2024
Faculty of Engineering and Technology, Multimedia University, Melaka, Malaysia.
Vehicle-to-everything (V2X) communication has many benefits. It improves fuel efficiency, road safety, and traffic management. But it raises privacy and security concerns.
View Article and Find Full Text PDFSci Rep
December 2024
Department of Computer Science, College of Education for Pure Sciences, University of Basrah, Basrah, Iraq.
Vehicular Ad-hoc Networks (VANETs) are growing into more desirable targets for malicious individuals due to the quick rise in the number of automated vehicles around the roadside. Secure data transfer is necessary for VANETs to preserve the integrity of the entire network. Federated learning (FL) is often suggested as a safe technique for exchanging data among VANETs, however, its capacity to protect private information is constrained.
View Article and Find Full Text PDFEnviron Pollut
December 2024
Department of Metallurgical and Materials Engineering, Ondokuz Mayıs University, 55200, Samsun, Turkey.
Road-associated microplastics, originating from tire wear and fragmented litter, are significant contributors to microplastic pollution. This study examines the characteristics of these particles within a university, focusing on their size, shape, color, and polymer composition. Suspended microplastics were collected using portable active samplers for PM and results have shown that PM concentrations peaked on Thursdays and declined, reaching their lowest levels on Sundays, with overall weekend measurements indicating reduced concentrations compared to weekdays.
View Article and Find Full Text PDFEnviron Sci Pollut Res Int
January 2025
Departamento de Química, ICEx, Universidade Federal de Minas Gerais, Avenida Antônio Carlos, Belo Horizonte, MG, 6627, 370901, Brazil.
The development of methods for determining volatile and semi-volatile organic compounds in public spaces has become necessary to identify potential health and environmental risks. This study presents a practical methodology for sampling, extracting, detecting, and identifying these compounds in a vehicular traffic region in Belo Horizonte, Brazil. The methodology uses direct-immersion solid phase microextraction (DI-SPME) and static headspace (SHS) to extract SVOCs/VOCs.
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