Vanet‐TSMA: A traffic safety management approach for smart road transportation in vehicular ad hoc networks

Kaul, Ajay; Altaf, Insha

doi:10.1002/dac.5132

Cited by 14 publications

(8 citation statements)

References 98 publications

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“…The authors of [27] present the Vanet-TSMA approach, which focuses on traffic safety management in VANETs for smart road transportation. The study analyzes the trend of road traffic accidents in India.…”

Section: Related Workmentioning

confidence: 99%

Enhancing Urban Traffic Management Through Real-Time Anomaly Detection and Load Balancing

Driss Laanaoui,

Lachgar,

Mohamed

et al. 2024

IEEE Access

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Efficient traffic management has become a major concern within the framework of smart city projects. However, the increasing complexity of data exchanges and the growing importance of big data makes this task more challenging. Vehicular ad hoc networks (VANETs) face various challenges, including the management of massive data generated by different entities in their environment. In this context, a proposal is put forth for a real-time anomaly detection system with parallel data processing, thereby speeding up data processing. This approach accurately computes vehicle density for each section at any given time, enabling precise traffic management and the provision of information to vehicles regarding traffic density and the safest route to their destination. Furthermore, a machine learning-based prediction system has been developed to mitigate congestion problems and reduce accident risks. Simulations demonstrate that the proposed solution effectively addresses transportation issues while maintaining low latency and high precision.INDEX TERMS Urban traffic management; real-time anomaly detection; intelligent transportation systems; traffic density prediction

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Section: Related Workmentioning

confidence: 99%

Enhancing Urban Traffic Management Through Real-Time Anomaly Detection and Load Balancing

Driss Laanaoui,

Lachgar,

Mohamed

et al. 2024

IEEE Access

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“…Environmental monitoring encompasses both natural and man-made environments, indoors and outdoors. There are various methods of monitoring, such as sensor-based monitoring on the ground, field sampling analysis in laboratories, and aerial and satellite remote sensing [18]. Diverse challenges remain for environmental monitoring nodes.…”

Section: A Wsn Applicationsmentioning

confidence: 99%

An In-depth Analysis of Uneven Clustering Techniques in Wireless Sensor Networks

Zhang¹

2023

IJACSA

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The low-cost and convenient feature of Wireless Sensor Networks (WSNs) has made them popular in many sectors over the last decade. The WSNs are now widely used as a result of recent advancements in low-power communication and being energy-efficient. The WSNs typically use batteries to power sensor nodes. The finite stored energy in batteries and the hassle of battery replacement have led to a critical focus on energy efficiency for WSNs. Clustering and data aggregation are the most efficient methods to address the energy concerns of WSNs. This paper comprehensively reviews several uneven clustering methods and compares the various uneven clustering algorithms. The methods are described in terms of their goals, attributes, categories, advantages and disadvantages. Probabilistic clustering is used when there is a need of simplicity and speed. As a result, this study compared all these types of protocols based on their clustering properties, CHs properties, and on the type of clustering process; and current research gap effective techniques are also addressed.

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“…This technological advancement has paved the way for enhanced safety, efficiency, and sustainability in transportation operations. The deployment of 5G technology marked a significant milestone in the evolution of VANETs, providing faster data rates, reduced latency, and improved connectivity [3,4]. However, as the demands of intelligent transportation continue to grow, the limitations of 5G are becoming apparent, propelling researchers and industries to explore the transformative potential of 6G technology.…”

Section: Introductionmentioning

confidence: 99%

Transforming Vehicular Networks: How 6G can Revolutionize Intelligent Transportation?

Aghaei Anvigh,

Khavan,

Pourghebleh

2024

Sci. Eng. Technol.

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Vehicular Ad-hoc Networks (VANETs) have enabled intelligent transportation systems by facilitating communication between vehicles and roadside infrastructure. However, the current 5G and 4G networks that support VANETs have certain limitations that hinder the full potential of VANET applications. These limitations include constraints in bandwidth, latency, connectivity, and security. The upcoming 6G network is expected to revolutionize VANETs by introducing several advancements. 6G will provide ultra-fast communication with significantly reduced latency, enabling real-time and high-bandwidth data exchange between vehicles. The network will also offer highly reliable and secure connectivity, ensuring the integrity and privacy of VANET communications. Precise localization and sensing capabilities will be enhanced in 6G-based VANETs, enabling accurate positioning of vehicles and improved situational awareness. This will facilitate collision avoidance, traffic management, and cooperative driving applications. Moreover, integrating edge computing in 6G networks will bring computing resources closer to the edge, lowering response times and facilitating faster decision-making in time-critical scenarios. This paper explores the key features and capabilities of 6G technology and how it can revolutionize intelligent transportation, addressing challenges and opportunities for adopting 6G in VANETs.

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Vanet‐TSMA: A traffic safety management approach for smart road transportation in vehicular ad hoc networks

Cited by 14 publications

References 98 publications

Enhancing Urban Traffic Management Through Real-Time Anomaly Detection and Load Balancing

Enhancing Urban Traffic Management Through Real-Time Anomaly Detection and Load Balancing

An In-depth Analysis of Uneven Clustering Techniques in Wireless Sensor Networks

Transforming Vehicular Networks: How 6G can Revolutionize Intelligent Transportation?

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