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Evaluating the Effect of Roadside Parking on a Dual-Direction Urban Street
Published on: January 20, 2023
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Cellular Automata-Based Application for Driver Assistance in Indoor Parking Areas
Cándido Caballero-Gil1, Pino Caballero-Gil2, Jezabel Molina-Gil3
1Department of Computer Engineering and Systems, University of La Laguna, La Laguna 38271, Tenerife, Spain. ccabgil@ull.es.
Sensors (Basel, Switzerland)
|November 18, 2016
Summary
This study introduces an adaptive smart parking system using smartphones and the Internet of Things to predict available spaces. The system reduces the time and energy drivers spend searching for parking.
Area of Science:
- Computer Science
- Electrical Engineering
- Transportation Systems
Background:
- Increasing urbanization leads to parking scarcity in indoor facilities.
- Smartphones and the Internet of Things (IoT) offer new opportunities for intelligent transportation systems.
Purpose of the Study:
- To propose an adaptive recommendation mechanism for smart parking.
- To develop a system that forecasts available indoor parking spaces using smartphone data and IoT.
Main Methods:
- A centralized system forecasts parking availability.
- A low-cost mobile application collects real-time and predicted occupancy data.
- Bidirectional data flow between centralized and distributed (smartphone) systems.
- Utilizes Quick Response (QR) codes, Near Field Communication (NFC), and Bluetooth Low Energy (BLE) beacons for indoor positioning.
Main Results:
- The proposed system effectively forecasts available indoor parking spaces.
- Demonstrated reduction in time and energy costs for drivers seeking parking.
- Validated through computer simulations and real-world experimentation.
Conclusions:
- The adaptive recommendation mechanism enhances the efficiency of finding parking in indoor facilities.
- Integration of smartphone data and IoT improves parking management.
- The system offers a practical solution for drivers to locate available parking spaces.
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