V2V‐based method for the detection of road traffic congestion

Wang, Runmin; Xu, Zhijie; Zhao, Xiangmo; Hu, Jinchao

doi:10.1049/iet-its.2018.5177

Cited by 62 publications

(26 citation statements)

References 24 publications

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“…In the future, EVT could be applied to data coming from road segment observations, employing information obtained with new ITS technologies, thanks to vehicle-to-vehicle or vehicle-toinfrastructure communications, which are being more and more utilised in the field of transport [42][43][44].…”

Section: Resultsmentioning

confidence: 99%

Large‐scale road safety evaluation using extreme value theory

Orsini

Gecchele²,

Gastaldi

et al. 2020

IET Intelligent Transport Systems

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Section: Resultsmentioning

confidence: 99%

Large‐scale road safety evaluation using extreme value theory

Orsini

Gecchele²,

Gastaldi

et al. 2020

IET Intelligent Transport Systems

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“…The problem with such approaches is that the computing process to assign the new alternative path to each vehicle is too long in high density; thus, the vehicle may have reached the congested area. The proposed system was also shown to detect road traffic congestion levels periodically using fuzzy logic and V2V communication [8]. When traffic congestion is detected, validation messages containing relevant information (vehicle ID, position coordinates, driving speed, driving direction, and time stamp) are exchanged among vehicles to determine the traffic congestion level.…”

Section: Speedmentioning

confidence: 99%

Detection of Road Traffic Congestion Using V2V Communication Based on IoT

Abood

Taher

Ghani

2021

eijs

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Intelligent Transportation Systems (ITS) have been developed to improve the efficiency and safety of road transport by using new technologies for communication. Vehicle to Vehicle (V2V) and Vehicle to Infrastructure (V2I) are a subset of ITS widely used to solve different issues associated with transportation in cities. Road traffic congestion is still the most significant problem that causes important economic and productivity damages, as well as increasing environmental effects. This paper introduces an early traffic congestion alert system in a vehicular network, using the internet of things (IoT) and fuzzy logic, for optimizing the traffic and increasing the flow. The proposed system detects critical driving conditions, or any emergency situation blocking the road, and broadcasts remote warnings to the following vehicles. Since not all vehicles are equipped with new technologies, Liquid Crystal Display (LCD) fixed on the roads displays the alert to warn the other vehicles which have neither communication nor sensors. The system was designed with Raspberry Pi 3 Model B equipped with sensors and GPS module to emulate real-world vehicles. The results and observations collected during the experiments showed that the proposed system is able to monitor the road conditions, detect the emergency situation, and broadcast a warning message to the approaching vehicles.

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“…The measurement-based congestion detection technique senses communication channels and measures parameters such as the number of messages in the queue, channel usage level, and channel occupancy time [36][37][38][39][40]. The congestion detection component measures the channel usage level periodically to detect any congestion situation.…”

Section: Measurement-based Congestion Detection Technique Eventdrivementioning

confidence: 99%

A survey on congestion detection and control in connected vehicles

2020

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The dynamic nature of vehicular ad hoc network (VANET) induced by frequent topology changes and node mobility, imposes critical challenges for vehicular communications. Aggravated by the high volume of information dissemination among vehicles over limited bandwidth, the topological dynamics of VANET causes congestion in the communication channel, which is the primary cause of problems such as message drop, delay, and degraded quality of service. To mitigate these problems, congestion detection, and control techniques are needed to be incorporated in a vehicular network. Congestion control approaches can be either open-loop or closed loop based on pre-congestion or post congestion strategies. We present a general architecture of vehicular communication in urban and highway environment as well as a state-of-the-art survey of recent congestion detection and control techniques. We also identify the drawbacks of existing approaches and classify them according to different hierarchical schemes. Through an extensive literature review, we recommend solution approaches and future directions for handling congestion in vehicular communications.

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V2V‐based method for the detection of road traffic congestion

Cited by 62 publications

References 24 publications

Large‐scale road safety evaluation using extreme value theory

Large‐scale road safety evaluation using extreme value theory

Detection of Road Traffic Congestion Using V2V Communication Based on IoT

A survey on congestion detection and control in connected vehicles

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