收集手机传感器与视频数据，构建多模态道路分析数据集
RoadSens-4M: A Multimodal Smartphone & Camera Dataset for Holistic Road-way Analysis
- 通过手机应用采集多传感器数据融合地理与天气信息
- 包含车辆速度、加速度等10+类数据及道路视频影像
- 适合智能交通、城市规划与道路安全研究者使用
为提升道路安全与基础设施质量，需持续监测路面凹凸、坑洼等问题。智能手机内置多种传感器为道路状况评估提供了低成本、便捷的途径，但进展缓慢主要受限于高质量、标准化数据集的缺乏。本文介绍一款基于移动应用构建的新数据集，可采集GPS、加速度计、陀螺仪、磁力计、重力传感器及方向传感器等多源数据。该数据集是少数将地理信息系统（GIS）数据、气象信息与道路视频同步整合的多模态数据集，提供包含车辆速度、加速度、旋转速率、磁场强度等关键参数的完整记录，并结合视觉与空间上下文，实现对道路问题的全景式分析。其目标是支持交通管理优化、基础设施建设、道路安全改善与城市规划决策。数据集将公开发布，推动智能交通系统领域的研究与创新。
原文摘要 · Abstract (English)
It's important to monitor road issues such as bumps and potholes to enhance safety and improve road conditions. Smartphones are equipped with various built-in sensors that offer a cost-effective and straightforward way to assess road quality. However, progress in this area has been slow due to the lack of high-quality, standardized datasets. This paper discusses a new dataset created by a mobile app that collects sensor data from devices like GPS, accelerometers, gyroscopes, magnetometers, gravity sensors, and orientation sensors. This dataset is one of the few that integrates Geographic Information System (GIS) data with weather information and video footage of road conditions, providing a comprehensive understanding of road issues with geographic context. The dataset allows for a clearer analysis of road conditions by compiling essential data, including vehicle speed, acceleration, rotation rates, and magnetic field intensity, along with the visual and spatial context provided by GIS, weather, and video data. Its goal is to provide funding for initiatives that enhance traffic management, infrastructure development, road safety, and urban planning. Additionally, the dataset will be publicly accessible to promote further research and innovation in smart transportation systems.
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