IoT in Traffic Management: Review of Existing Methods of Road Traffic Regulation

Elkin, Dmitry; Vyatkin, Valeriy

doi:10.1007/978-3-030-51974-2_50

Cited by 14 publications

(8 citation statements)

References 30 publications

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“…It belongs to a kind of moving target detection, so before moving vehicle detection, this research first analyzes and researches moving target detection. At present, the detection algorithms for moving targets mainly include optical flow method, frame difference method, and background difference method [18].…”

Section: Research On Algorithms Of Vehicle Motion Track Detection On Expresswaymentioning

confidence: 99%

[Retracted] Anomaly Detection of Highway Vehicle Trajectory under the Internet of Things Converged with 5G Technology

Ke-tao

2021

Complexity

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The gradual increase in the density of highway vehicles and traffic flow makes the abnormal driving state of vehicles an indispensable tool for assisting traffic dispatch. Intelligent transportation systems can detect and track vehicles in real time, acquire characteristics such as vehicle traffic, vehicle speed, vehicle flow density, and vehicle trajectory, and further perform advanced tasks such as vehicle trajectory. The detection of abnormal vehicle trajectory is an important content of vehicle trajectory understanding. And the development of the Internet of Things (IoT) and 5G technology has led to a continuous increase in the rate of data information circulation. The “Internet of Vehicles” generated based on the practice of 5G communication technology constitutes a vehicle abnormal trajectory detection system, which has very high feasibility and safety and stability. Therefore, this research is aimed at the needs of preventing major accidents and forensic analysis during highway vehicles. Based on the integration of the Internet of Things 5G communication technology, a trajectorial anomaly detection of highway vehicle trajectory based on the integration of the Internet of Things 5G is proposed. By accurately sensing unsafe events at the perception layer, network layer, and application layer, the vehicle driving trajectory state is divided into several simple semantic representations. The semantic representation is analyzed, and then the moving target detection and moving target tracking algorithms needed to extract the vehicle trajectory are introduced. Through video detection and tracking of moving vehicle targets, the driving trajectory of the vehicle is obtained, and the movement characteristics of the vehicle in each frame of image are extracted. According to the relationship between the trajectory of the vehicle and the lane line, the vehicle trajectory analysis is realized, and then it is judged whether the vehicle has abnormal trajectory. Compared with the traditional method of manually detecting the driving condition of the vehicle, the abnormal trajectory detection of the vehicle based on the integration of the Internet of Things and 5G can quickly detect the abnormal trajectory of the vehicle in the traffic monitoring video.

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Section: Research On Algorithms Of Vehicle Motion Track Detection On Expresswaymentioning

confidence: 99%

[Retracted] Anomaly Detection of Highway Vehicle Trajectory under the Internet of Things Converged with 5G Technology

Ke-tao

2021

Complexity

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“…In paper [27], an intelligent traffic management system (ITMS) was presented to prioritize emergency vehicles by merging the concepts of VANET and IoT to improve ambulance flow in metropolitan areas. It demonstrates a way to detect and prevent traffic signal hacking, which is a fairly prevalent problem nowadays.…”

Section: Literature Reviewmentioning

confidence: 99%

Real-Time Security Health and Privacy Monitoring for Saudi Highways Using Cutting-Edge Technologies

2022

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Kingdom of Saudi Arabia (KSA) highways hold the record for having the straightest, longest highways in the world. Since the country’s major population centers are dispersed across the country and due to the country’s geography, which includes valleys, deserts, and mountains, among other landscapes, these highways connect the many cities of the kingdom and neighboring nations. However, it is still challenging to provide emergency assistance in a timely way in the case of accidents, such as first aid, medical aid, police protection, etc. The transport ministry is actively working on improvements and safety features for the drivers. This research proposes a CET (cutting-edge technologies)-based model named the real-time security, health, and privacy monitoring model for passenger safety (RTSHPMP) for securing the traveler’s safety and privacy besides medical and legal help. The vehicle will be equipped with IoT-based front-back cameras to collect real-time data and share it with the cloud using 5G network. The local and national trusted authorities (TAs) will monitor the collected cloud data and inform the government machinery (police, first aid, fire brigade, hospitals) in the case of an accident. In addition, the data collected through other vehicles on the road at the time of the incident will help supply evidence linked to the accident. The RTSHPMP was evaluated with the help of a case study, and the results show that it provides an efficient and secure mechanism for traveler safety on Saudi highways at the time of need.

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“…One of the commonly applied solutions for traffic management to support emergency vehicles is the application of IoT [22]. IoT provides a rational solution to the urban traffic congestion problem.…”

Section: Literature Reviewmentioning

confidence: 99%

A Distributed Emergency Vehicle Transit System Using Artificial Intelligence of Things (DEVeTS-AIoT)

Mahmud

Hussain

Sarwar

et al. 2022

Wireless Communications and Mobile Computing

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The advent of the 4th industrial revolution has realized smart environments composed of cloud and fog. These have been improved to enable intelligence at the fog, where numerous, inexpensive devices communicate with each other and provide computation capabilities to solve domain-specific problems in a distributed fashion. One of these domains is smart traffic flow with a focus on emergency vehicle (EV) transit. The increase in traffic congestion in third-world countries is a hindrance in EV transit to save human lives. This paper proposes an Artificial Intelligence of Things– (AIoT–) based, distributed, EV transit system developed on Raspberry PI as a rule-based system with minimal sensors. The sensors include an infrared sensor to detect emergency light and directional microphones to detect siren. The departure direction of the EV is shared with adjacent intersections to further reduce the transit time.

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IoT in Traffic Management: Review of Existing Methods of Road Traffic Regulation

Cited by 14 publications

References 30 publications

[Retracted] Anomaly Detection of Highway Vehicle Trajectory under the Internet of Things Converged with 5G Technology

[Retracted] Anomaly Detection of Highway Vehicle Trajectory under the Internet of Things Converged with 5G Technology

Real-Time Security Health and Privacy Monitoring for Saudi Highways Using Cutting-Edge Technologies

A Distributed Emergency Vehicle Transit System Using Artificial Intelligence of Things (DEVeTS-AIoT)

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