Q-Motion: A Multi-Sensor Micro-EV Dataset for Urban Mobility

Published: 13 July 2026| Version 1 | DOI: 10.17632/p5376m6xfc.1
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Description

This dataset comprises multimodal time-series sensor data recorded on a Citroën Ami light electric quadricycle (L6e category) in Matosinhos, Portugal, across four collection dates (July 2024, March 2025, May 2025, and July 2025). The dataset includes 81 driving sessions totaling 233 km and 12.9 hours of urban driving, conducted by 5 drivers with 1–2 occupants (55–166 kg total occupant weight). Ground truth annotations are provided for driving behaviour, tire pressure, and occupant weight. The dataset includes synchronized sensor data from: - ROS 2 vehicle-mounted sensors: IMU/Bosch BMI323 (180–200 Hz), GNSS (1 Hz), CAN bus — motor/powertrain and vehicle status (4–20 Hz) - Smartphone-based system (SMC/Google Pixel 6): IMU (500 Hz), magnetometer (100 Hz), and GNSS (1 Hz) for redundant measurements Three experimental scenarios were conducted: - Baseline (32 sessions, 94.5 km): Standard urban driving under controlled reference conditions - Aggressive Driving (19 sessions, 66.1 km): Intentional maneuvers including sudden accelerations, hard braking, sharp curves, zig-zags, and speed bumps - Tire Pressure Variation (30 sessions, 72.3 km): Normal driving with systematically varied tire pressures (1.5–2.6 bar), including single-wheel configurations The dataset is organized as follows: - data/original_data/ — Raw sensor recordings (CSV), organized by date and scenario - data/processed_data/ — Vehicle-aligned IMU, semantic labels, gravity-compensated signals, and automated annotations - auxiliary_files/ — Collection guidelines, IMU rotation matrices, and Time-Tracker event annotations - documentation/ — Acquisition protocol, processing pipeline, quality report, and ground-truth labeling notes This dataset supports research in aggressive driving detection, tire pressure monitoring, electric vehicle dynamics, fleet management, shared mobility systems, and multimodal sensor fusion.

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Institutions

Categories

Global Positioning System, Urban Mobility, Vehicle Dynamics, Automotive Sensor, Electric Vehicles, Inertial Fusion, Vehicle Mobility, Electric Motor

Funders

  • European Union under the NextGenerationEU, through a grant of the Portuguese Republic’s Recovery and Resilience Plan (PRR) Partnership Agreement, within the scope of the project BE.NEUTRAL – Agenda da Mobilidade para a neutralidade carbónica das cidades.
    Grant ID: Project ref. nr. 35 - C644874240-00000016

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