Routing protocols in Vehicular Adhoc Networks (VANETs): A comprehensive survey

Sohail, Muhammad; Latif, Zohaib; Javed, Shahzeb; Biswas, Sujit; Ajmal, Sahar; Iqbal, Umer; Raza, Mohsin; Khan, Abd Ullah

doi:10.1016/j.iot.2023.100837

Cited by 16 publications

(3 citation statements)

References 74 publications

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“…Suggest a method for fusion location [19]. This method uses a hierarchical optimization strategy to incorporate light intensity measurements, inertial navigation data, and geomagnetic data [20]. Numerous routing protocols, such as unicast, multicast, broadcast, etc., have been proposed in the literature that takes advantage of the topology of the network.…”

Section: Related Workmentioning

confidence: 99%

Increasing Efficiency and Reliability in Multicast Routing based V2V Communication for Direction-Aware Cooperative Collision Avoidance

V.,

Pramila. R

2024

Int. j. electr. comput. eng. syst. (Online)

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Mobile ad hoc networks (MANETs), which are a promising method for the intelligent transportation system, include vehicular ad hoc networks (VANETs) (ITS). Developing reliable and strong cooperative collision avoidance (CCA) strategy to mitigate the growing number of road fatalities each year is one of the main difficulties facing vehicular ad hoc networks (VANETs).A proper and successful routing method aids in the successful expansion of vehicular ad hoc networks. This study explains the architecture, interface layers, safety features, and implementation of a novel priority-based direction-aware collision avoidance system (P-DVCA). It distinguishes our study in the collision area of VANETs by accounting for realistic bi-directional traffic. The scheme begins with the development of dynamic clusters, which is difficult because of the bi-directional diverse traffic and the need to avoid collisions within and between clusters. The target node is sent an early warning message that includes the safe speed and the likelihood of a collision in order to notify it of an impending danger. To determine the least expensive, shortest one with the fewest hops between the source and the endpoint. A crucial problem with VANETs is the transmission of data from a source node to the base station. Cross-layer issues must be solved for a robust and stable collision avoidance programme to function properly in a VANET communication architecture. The results of the simulation show that the suggested scheme significantly outperforms CCM and C-RACCA in terms of cluster stability, fewer collisions, low latency, and low communication overhead. According to the findings, P-DVCA offers stable clustering, minimises network congestion, and lowers communication overhead and latency.

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Section: Related Workmentioning

confidence: 99%

Increasing Efficiency and Reliability in Multicast Routing based V2V Communication for Direction-Aware Cooperative Collision Avoidance

V.,

Pramila. R

2024

Int. j. electr. comput. eng. syst. (Online)

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“…A vehicle in VANET is provided with an On-Board Unit (OBU), a Global Positioning System (GPS), and radar, that establishes communication with other entities within the VANET [25].…”

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confidence: 99%

Secure AODV Routing Strategies in Smart Cities for Vehicular Communication

Fadhil,

Din,

Aripin

et al. 2024

JESA

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“…However, these automated vehicles are still not intelligent enough to rely completely on their power of decision making which increases the risk of financial losses and deaths 2 . A vehicle, during its visit over the road, requires a wide range of parameters for its successful operation which includes position of vehicle, direction of motion, speed, the time of joining the network, and expected time to stay within that network 3 . All these parameters help the vehicle to take decisions during its operation on the road.…”

Section: Introductionmentioning

confidence: 99%

Radar sensor based machine learning approach for precise vehicle position estimation

Sohail,

Khan,

Sandhu

et al. 2023

Sci Rep

Self Cite

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Estimating vehicles’ position precisely is essential in Vehicular Adhoc Networks (VANETs) for their safe, autonomous, and reliable operation. The conventional approaches used for vehicles’ position estimation, like Global Positioning System (GPS) and Global Navigation Satellite System (GNSS), pose significant data delays and data transmission errors, which render them ineffective in achieving precision in vehicles’ position estimation, especially under dynamic environments. Moreover, the existing radar-based approaches proposed for position estimation utilize the static values of range and azimuth, which make them inefficient in highly dynamic environments. In this paper, we propose a radar-based relative vehicle positioning estimation method. In the proposed method, the dynamic range and azimuth of a Frequency Modulated Continuous Wave radar is utilized to precisely estimate a vehicle’s position. In the position estimation process, the speed of the vehicle equipped with the radar sensor, called the reference vehicle, is considered such that a change in the vehicle’s speed changes the range and azimuth of the radar sensor. For relative position estimation, the distance and relative speed between the reference vehicle and a nearby vehicle are used. To this end, only those vehicles are considered that have a higher possibility of coming in contact with the reference vehicle. The data recorded by the radar sensor is subsequently utilized to calculate the precision and intersection Over Union (IOU) values. You Only Look Once (YOLO) version 4 is utilized to calculate precision and IOU values from the data captured using the radar sensor. The performance is evaluated under various real-time traffic scenarios in a MATLAB-based simulator. Results show that our proposed method achieves 80.0% precision in position estimation and obtains an IOU value up to 87.14%, thereby outperforming the state-of-the-art.

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Routing protocols in Vehicular Adhoc Networks (VANETs): A comprehensive survey

Cited by 16 publications

References 74 publications

Increasing Efficiency and Reliability in Multicast Routing based V2V Communication for Direction-Aware Cooperative Collision Avoidance

Increasing Efficiency and Reliability in Multicast Routing based V2V Communication for Direction-Aware Cooperative Collision Avoidance

Secure AODV Routing Strategies in Smart Cities for Vehicular Communication

Radar sensor based machine learning approach for precise vehicle position estimation

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