Dynamic Street-Parking Optimisation

Pazos, Nuria; Müller, Michael; Favre-Bulle, M.; Brandt-Dit-Grieurin, K.; Husser, O.; Aeberli, Marco; Ouerhani, Nabil

doi:10.1109/aina.2016.171

Cited by 11 publications

(7 citation statements)

References 3 publications

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“…OGSi, a bridge between cloud and user tiers, provides an environment that modularizes web applications by registering or moving in the execution context of the bundle. Pazos et al [111] adopted a central IoT platform Stemys.io to manage all the OSGi-enabled gateways and sensors. In addition, MQTT broker is installed on a central server in order to deal with drivers' parking demands by publishing/subscribing messaging paradigm.…”

Section: Parking System Deploymentmentioning

confidence: 99%

A Survey of Smart Parking Solutions

Lin

Rivano

Mouël

2017

IEEE Trans. Intell. Transport. Syst.

430

185

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Section: Parking System Deploymentmentioning

confidence: 99%

A Survey of Smart Parking Solutions

Lin

Rivano

Mouël

2017

IEEE Trans. Intell. Transport. Syst.

430

185

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“…Metode lain dalam melakukan pendeteksian dikembangkan dalam bentuk citra visual, semisal pada Semi-Autonomous Parking Measurement System (SAPOMS) [5] yang melakukan akuisisi lahan parkir menggunakan citra visual beserta splicing image mobil yang terparkir pada zona parkir yang dipergunakan. Bentuk akuisisi citra memberikan kemudahan dalam akuisisi dan rekognisi secara visual, serta pada sistem tersebut penggunaan Raspberry Pi sebagai pemroses utama menghasilkan cost yang lebih efisien dalam jangka panjang baik pada perawatan dan pengembangan.…”

Section: Pendahuluanunclassified

Validasi Kendaraan Pada Sistem Parkir Cerdas Berbasis Pengenalan Citra Menggunakan Raspberry Pi 3

Amrullah,

Saputro Anggoro

2023

smartcomp

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Solusi parkir cerdas dalam mengatasi permasalahan lahan parkir telah dikembangan baik dari bentuk sistem informasi hingga terintegrasi. Pada ketersediaan zona parkir, beberapa solusi parkir cerdas, menggunakan bentuk implementasi sensor ultrasonik, infrared, dan pengenalan citra. Permasalahan yang terjadi pada kendaraan yang akan parkir pada zona parkir adalah validasi objek kendaraan parkir, sehingga akan sangat dimungkinkan objek bukan kendaraan dianggap sebagai kendaraan yang akan parkir. Pada penelitian ini akan dikembangkan mekanisme pendeteksian dan validasi dini pada kendaraan yang akan parkir pada suatu zona parkir cerdas berbasis pengenalan citra kendaraan menggunakan peralatan Microcontroller dengan tipe ESP32-Cam dan Raspberry Pi 3 sebagai server pada sistem parkir cerdas. Pada hasil pengujian yang didapatkan, kendaraan ataupun objek dapat terdeteksi dengan baik melalui akuisisi citra pada sisi belakang kendaraan yang akan terparkir dengan bentuk output validasi pada lokasi parkir menggunakan buzzer sebagai output hasil validasi dan pengarah jarak tepi zona parkir dengan kendaraan yang terdeteksi dan tervalidasi dengan tingkat akurasi sebesar 87% dan waktu validasi rata-rata 22 detik dengan menggunakan metode CNN pada framework YOLO v3.

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“…This online reservation system showed that the overall cost is lower compared to other parking strategies. Pazos, Müller et al in [ 23 ] proposed a mobile guidance software called SmartPark that helps drivers find the “optimal” parking spot. This depends on the available data of the parking systems, as well as other sensors.…”

Section: Related Workmentioning

confidence: 99%

A Balanced Algorithm for In-City Parking Allocation: A Case Study of Al Madinah City

Abdeen

Nemer

Sheltami

2021

Sensors

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Parking in heavily populated areas has been considered one of the main challenges in the transportation systems for the past two decades given the limited parking resources, especially in city centres. Drivers often waste long periods of time hunting for an empty parking spot, which causes congestion and consumes energy during the process. Thus, finding an optimal parking spot depends on several factors such as street traffic congestion, trip distance/time, the availability of a parking spot, the waiting time on the lot gate, and the parking fees. Designing a parking spot allocation algorithm that takes those factors into account is crucial for an efficient and high-availability parking service. We propose a smart routing and parking algorithm to allocate an optimal parking space given the aforementioned limiting factors. This algorithm supports choosing the appropriate travel route and parking lot while considering the real-time street traffic and candidate parking lots. A multi-objective function is introduced, with varying weights of the five factors to produce the optimal parking spot with the least congested route while achieving a balanced utilization for candidate parking lots and a balanced traffic distribution. A queueing model is also developed to investigate the availability rate in candidate parking lots while considering the arrival rate, departure rate, and the lot capacity. To evaluate the performance of the proposed algorithm, simulation scenarios have been performed for different cases of high and low traffic intensity rates. We have tested the algorithm on in-city parking facility in the city of Al Madinah as a case study. The results show that the proposed algorithm is effective in achieving a balanced utilization of the parking lots, reducing traffic congestion rates on all routes to candidate parking lots, and minimizing the driving time to the assigned parking spot. Additionally, the proposed algorithm outperforms the MADM algorithm in terms of the selected three metrics for the five periods.

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Dynamic Street-Parking Optimisation

Cited by 11 publications

References 3 publications

A Survey of Smart Parking Solutions

A Survey of Smart Parking Solutions

Validasi Kendaraan Pada Sistem Parkir Cerdas Berbasis Pengenalan Citra Menggunakan Raspberry Pi 3

A Balanced Algorithm for In-City Parking Allocation: A Case Study of Al Madinah City

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