An Improved Roadside Parking Space Occupancy Detection Method Based on Magnetic Sensors and Wireless Signal Strength

Lou, Liangliang; Zhang, Jinyi; Jin, Yanliang

doi:10.3390/s19102348

Cited by 21 publications

(8 citation statements)

References 23 publications

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“…Proprioceptive sensors detect the state of a system. The information from magnetic sensors and magnetometers covers the orientation estimation in combination with other on-board inertial measurement units, e.g., accelerometers and gyroscopes [ 50 ]. Sensing data from smartphones and ML algorithms are used to detect vehicle user status, i.e., inside or outside the vehicle, while parking occupancy is detected via a combination of infrared detectors, and distance sensors [ 52 ].…”

Section: Technologies In Vehicles-to-everything Communicationmentioning

confidence: 99%

Towards Autonomous Driving: Technologies and Data for Vehicles-to-Everything Communication

Ušinskis,

Makulavičius,

Petkevičius

et al. 2024

Sensors

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Autonomous systems are becoming increasingly relevant in our everyday life. The transportation field is no exception and the smart cities concept raises new tasks and challenges for the development of autonomous systems development which has been progressively researched in literature. One of the main challenges is communication between different traffic objects. For instance, a mobile robot system can work as a standalone autonomous system reacting to a static environment and avoiding obstacles to reach a target. Nevertheless, more intensive communication and decision making is needed when additional dynamic objects and other autonomous systems are present in the same working environment. Traffic is a complicated environment consisting of vehicles, pedestrians, and various infrastructure elements. To apply autonomous systems in this kind of environment it is important to integrate object localization and to guarantee functional and trustworthy communication between each element. To achieve this, various sensors, communication standards, and equipment are integrated via the application of sensor fusion and AI machine learning methods. In this work review of vehicular communication systems is presented. The main focus is the researched sensors, communication standards, devices, machine learning methods, and vehicular-related data to find existing gaps for future vehicular communication system development. In the end, discussion and conclusions are presented.

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Section: Technologies In Vehicles-to-everything Communicationmentioning

confidence: 99%

Towards Autonomous Driving: Technologies and Data for Vehicles-to-Everything Communication

Ušinskis,

Makulavičius,

Petkevičius

et al. 2024

Sensors

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“…From the sensing functionality perspective, recent work in the area of parking occupancy detection can be divided into three categories: wireless sensor network (WSN) solution [12], [14], [34], [26]- [33], moving sensor solution [35], [36], [45], [37]- [44], and vision-based solution [12], [13], [22]- [25], [14]- [21].…”

Section: Literature Reviewmentioning

confidence: 99%

A Smart, Efficient, and Reliable Parking Surveillance System With Edge Artificial Intelligence on IoT Devices

Zhuang

et al. 2021

IEEE Trans. Intell. Transport. Syst.

144

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Cloud computing has been a main-stream computing service for years. Recently, with the rapid development in urbanization, massive video surveillance data are produced at an unprecedented speed. A traditional solution to deal with the big data would require a large amount of computing and storage resources. With the advances in Internet of things (IoT), artificial intelligence, and communication technologies, edge computing offers a new solution to the problem by processing all or part of the data locally at the edge of a surveillance system.In this study, we investigate the feasibility of using edge computing for smart parking surveillance tasks, specifically, parking occupancy detection using the real-time video feed. The system processing pipeline is carefully designed with the consideration of flexibility, online surveillance, data transmission, detection accuracy, and system reliability. It enables artificial intelligence at the edge by implementing an enhanced single shot multibox detector (SSD). A few more algorithms are developed either locally at the edge of the system or on the centralized data server targeting optimal system efficiency and accuracy. Thorough field tests were conducted in the Angle Lake parking garage for three months. The experimental results are promising that the final detection method achieves over 95% accuracy in real-world scenarios with high efficiency and reliability. The proposed smart parking surveillance system is a critical component of smart cities and can be a solid foundation for future applications in intelligent transportation systems.

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“…One of them is the image processing technique and video detection, which are used in many areas [20][21][22][23]. Sensors mounted in surfaces have also been used to recognize the occupancy of parking spaces [24][25][26]. The Global System for Mobile (GSM) and radio-frequency identification (RFID) systems have also been used in parking areas [27][28][29].…”

Section: Literature Reviewmentioning

confidence: 99%

Drivers’ Subjective Assessment of the Ease of Finding a Vacant Parking Space in an Area Equipped with Vehicle Detection Devices

Kurek

Macioszek

2022

Sensors

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The growing traffic on city streets leads to traffic disruptions, lowering the level of road safety, as well as the problem of finding a vacant parking space. Drivers looking for a vacant parking space on the street generate so-called search traffic. Paid parking zones are introduced to increase the availability of parking spaces for more drivers in many cities around the world. The development in the technology and information sector has contributed to the development of systems guiding drivers to vacant parking spaces. This article aims to analyze drivers’ subjective assessment of the ease of finding a vacant parking space in an area equipped with vehicle detection devices. Data from the Municipal Roads Authority in Gliwice (Poland) were obtained for the study, covering the use of parking spaces in the paid parking zone covered by dynamic parking information. Moreover, a survey was conducted among users of the paid parking zone in Gliwice. The answers of the respondents were used to build a logit model that allows determining the probability of a driver’s positive subjective assessment of the ease of finding a vacant parking space in an area equipped with vehicle detection devices. The results from the model allow the characterization of drivers who positively assess the ease of finding a vacant parking space in the area equipped with vehicle detection devices. In addition, it is possible to reach a group of drivers who negatively assessed the ease of finding a vacant parking space to learn about the factors that may cause them to change their assessment to a positive one. The research results allow city authorities to better manage parking spaces equipped with vehicle detection devices in the paid parking zone. This may change the negative assessment of the ease of finding a vacant parking space into a positive one.

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An Improved Roadside Parking Space Occupancy Detection Method Based on Magnetic Sensors and Wireless Signal Strength

Cited by 21 publications

References 23 publications

Towards Autonomous Driving: Technologies and Data for Vehicles-to-Everything Communication

Towards Autonomous Driving: Technologies and Data for Vehicles-to-Everything Communication

A Smart, Efficient, and Reliable Parking Surveillance System With Edge Artificial Intelligence on IoT Devices

Drivers’ Subjective Assessment of the Ease of Finding a Vacant Parking Space in an Area Equipped with Vehicle Detection Devices

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