PHVA: A Position Based High Speed Vehicle Detection Algorithm for Detecting High Speed Vehicles using Vehicular Cloud

Nayak, Rajendra Prasad; Sethi, Srinivas; Bhoi, Sourav Kumar

doi:10.1109/icit.2018.00054

Cited by 11 publications

(6 citation statements)

References 12 publications

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“…In [15], a speedometer using XBee is used to record the vehicle's speed to compare with the network of Master XBees. e method in [16] uses Road Side Units (RSUs) in a Vehicular Ad Hoc Network (VANET) for estimating vehicular speed. Using information from nearby several RSUs, the speed of the vehicle can be estimated.…”

Section: Existing Speed-limit Traffic Violation Recording Systemsmentioning

confidence: 99%

“…e work in [23] uses Arduino and GPRS to send traffic violation data to the Cloud for processing. In [16], the traffic violation is computed and recorded in the Cloud from the data sent by Road Side Units. In [15], when speed-limit violation is detected (even after warning), the information regarding the vehicle registration number is transmitted to the master XBee installed specifically for the task.…”

Section: Existing Speed-limit Traffic Violation Recording Systemsmentioning

confidence: 99%

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Autonomous Real-Time Speed-Limit Violation Detection and Reporting Systems Based on the Internet of Vehicles (IoV)

Mohamed

Parvez

Al-Shalfan

et al. 2021

Journal of Advanced Transportation

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Over-/underspeeding is one of the leading causes of road accidents. Traditional systems of detecting and reporting speed-limit violations are not suitable for smart cities. Even the sophisticated conventional systems that use cameras or RFIDs for automating speed-limit violations have several drawbacks, including cost, complexity, reliability, and maintenance. In this paper, we present two systems based on the Internet of Vehicles (IoV) to automatically detect speed-limit violations and autonomously report the committed violations to the authorities. Our systems require no extra hardware or equipment: only the On-Board Unit (OBU), the Road Side Unit (RSU), and the Cloud Server software have to be updated to have a fully functioning system as long as the IoV infrastructure is deployed. One of the systems will be installed on the OBU. A second alternative system design is to use Cloud Servers (CSs) and the IoV beacons that are sent from the vehicles. Additionally, unlike the existing systems installed in specific locations, all roads in the smart cities and highways will be fully monitored. Adaptive fine calculation according to new dynamic policies can be easily integrated into the proposed system. Furthermore, the proposed system can accurately operate in all weather conditions. Moreover, it allows the dynamic adjustment of the speed limits according to the current weather conditions. We have validated the proposed system by building a prototype system that effectively and accurately detects and reports over-/underspeed traffic violations alongside any road.

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Section: Existing Speed-limit Traffic Violation Recording Systemsmentioning

confidence: 99%

Section: Existing Speed-limit Traffic Violation Recording Systemsmentioning

confidence: 99%

Autonomous Real-Time Speed-Limit Violation Detection and Reporting Systems Based on the Internet of Vehicles (IoV)

Mohamed

Parvez

Al-Shalfan

et al. 2021

Journal of Advanced Transportation

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show abstract

“…The proposed method considers acceleration and deceleration as well as the other kinematic parameters to obtain more accurate results. Nayak et al [189] proposed a position-based high-speed vehicle detection algorithm in VANET. The proposed algorithm determines the driving lane of a vehicle and detects speed violations based on the permitted speed in that lane.…”

Section: Mobility Parameters Of Vehiclesmentioning

confidence: 99%

A Review on Vehicle Classification and Potential Use of Smart Vehicle-Assisted Techniques

Shokravi

Bakhary

et al. 2020

Sensors

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Vehicle classification (VC) is an underlying approach in an intelligent transportation system and is widely used in various applications like the monitoring of traffic flow, automated parking systems, and security enforcement. The existing VC methods generally have a local nature and can classify the vehicles if the target vehicle passes through fixed sensors, passes through the short-range coverage monitoring area, or a hybrid of these methods. Using global positioning system (GPS) can provide reliable global information regarding kinematic characteristics; however, the methods lack information about the physical parameter of vehicles. Furthermore, in the available studies, smartphone or portable GPS apparatuses are used as the source of the extraction vehicle’s kinematic characteristics, which are not dependable for the tracking and classification of vehicles in real time. To deal with the limitation of the available VC methods, potential global methods to identify physical and kinematic characteristics in real time states are investigated. Vehicular Ad Hoc Networks (VANETs) are networks of intelligent interconnected vehicles that can provide traffic parameters such as type, velocity, direction, and position of each vehicle in a real time manner. In this study, VANETs are introduced for VC and their capabilities, which can be used for the above purpose, are presented from the available literature. To the best of the authors’ knowledge, this is the first study that introduces VANETs for VC purposes. Finally, a comparison is conducted that shows that VANETs outperform the conventional techniques.

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“…In order to detect high speed vehicles in the Vehicle Ad Hoc Network, Nayak et al propose a Position Based Algorithm for High Speed Car Detection (PHVA), using a vehicle cloud server, used as computing as a service [12] A crucial step for traffic safety applications is the automated regulation of vehicle speed by sensing speed sign labels from speed boards on the roadside. In addition, the driver will be notified of the changes in the speed limit with an alarm message [13].…”

Section: Rahmaniar Et Al Introduced a New And Efficient Techniquementioning

confidence: 99%

Moving Object Detection and Speed Estimation by Digital Image Processing

Khasim¹,

Anilkumar²,

Vamshi³

et al. 2022

J. Phys.: Conf. Ser.

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Intelligent network systems and security surveillance are used for smart city development. Manual and heritage technology is used in surveillance systems to detect speeds higher than usual in developing countries. This process can be automated with ease by leveraging the potential of image processing. Moving object detection is one of the essential tasks in image processing because of its prominent role in many real-world applications. Vehicle speed detection can be achieved by employing image and video processing methods. In this work, a unique approach is proposed for moving object detection and speed estimation based on an integrated approach in video sequence frames as opposed to the most commonly used RADAR and LIDAR devices for traffic law enforcement. Video data is collected and analyzed for speed in real-time without any sensor calibrations,thereby it removes any external hardware dependency requirements. Moving vehicles are segmented out by using frame-subtraction and masking techniques. The proposed algorithm tracks the time taken by the car to cover a predetermined fixed distance in order to calculate its speed.

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PHVA: A Position Based High Speed Vehicle Detection Algorithm for Detecting High Speed Vehicles using Vehicular Cloud

Cited by 11 publications

References 12 publications

Autonomous Real-Time Speed-Limit Violation Detection and Reporting Systems Based on the Internet of Vehicles (IoV)

Autonomous Real-Time Speed-Limit Violation Detection and Reporting Systems Based on the Internet of Vehicles (IoV)

A Review on Vehicle Classification and Potential Use of Smart Vehicle-Assisted Techniques

Moving Object Detection and Speed Estimation by Digital Image Processing

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