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<p>This paper presents a dataset based on Bluetooth Low Energy (BLE) and the use of smartphones for vehicle localization and tracking. An antenna system formed by eight directive panel antennas forming a crossed array is mounted on an electronic toll collection (ETC) gateway, at a height of 4.75 m, facing downwards illuminating a two-lane road. The system was first calibrated in an 8 m × 8 m area below the gateway, measuring the RSSI (Received Signal Strength Indicator) data captured by a smartphone. Then, a second set of data is constructed from different performed tests, in which the RSSI is acquired from a smartphone inside a vehicle which passes below the gateway conducting Stop&amp;Go and 20 Km/h tests. As a validation of the dataset, a benchmark analysis for data visualization and localization/tracking is included, where three different algorithms (amplitude-monopulse comparison, MUltiple SIgnal Classification, and fingerprinting) used the calibrated data to track the location of the smartphone inside the vehicle in the different performed tests.</p>

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An electronic toll collection gateway BLE RSSI dataset for localization of smartphones in vehicular scenarios

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年3月6日

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  • Alejandro Gil-Martínez,
  • Alejandro Rabadán-Parra,
  • David Cañete-Rebenaque,
  • José Luis Gómez-Tornero

摘要

This paper presents a dataset based on Bluetooth Low Energy (BLE) and the use of smartphones for vehicle localization and tracking. An antenna system formed by eight directive panel antennas forming a crossed array is mounted on an electronic toll collection (ETC) gateway, at a height of 4.75 m, facing downwards illuminating a two-lane road. The system was first calibrated in an 8 m × 8 m area below the gateway, measuring the RSSI (Received Signal Strength Indicator) data captured by a smartphone. Then, a second set of data is constructed from different performed tests, in which the RSSI is acquired from a smartphone inside a vehicle which passes below the gateway conducting Stop&Go and 20 Km/h tests. As a validation of the dataset, a benchmark analysis for data visualization and localization/tracking is included, where three different algorithms (amplitude-monopulse comparison, MUltiple SIgnal Classification, and fingerprinting) used the calibrated data to track the location of the smartphone inside the vehicle in the different performed tests.