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A CONCEPT FOR NATURALISTIC DATA COLLECTION FOR VULNERABLE ROAD USERS USING A SMARTPHONE-BASED PLATFORM

机译:使用基于智能手机的平台的易受攻击道路用户的自然数据收集概念

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This paper presents a smartphone-based platform for large-scale, low-cost, long-term naturalistic data collection aimed at vulnerable road users (VRUs). The approach taken is to collect naturalistic movement data from VRUs based on information from the embedded sensors in high-end smartphones. The Smartphone application, LogYard, developed in the current study, allows the recording of high quality data (tri-axial acceleration and rotation at 100 Hz plus GPS position and velocity each second). This way, large data quantities from ATV drivers' movements during daily use in different use cases, can be transferred from a large number of users and accumulated in a cloud-based server for off-line analysis. Apart from the description on how data is recorded and managed in the smartphone-based platform, also a procedure on how to include participants to studies and how private integrity issues and informed consent can be handled from a distance is presented. By means of the presented smartphone based platform, large number of participants taking part in several parallel on-going studies can be easily administered. This makes the platform a powerful tool to use in large-scale, low-cost, long-term studies providing data from large groups of study participants. The information made available this way can be used to develop automatic crash notification (ACN) systems directed to VRUs based on identifying movements outside what is "normal" for bicyclists, mopedists, motorcyclists and ATV users.
机译:本文介绍了基于智能手机的大型平台,用于大规模,低成本,长期自然主义数据集合,旨在脆弱的道路使用者(VRU)。采取的方法是根据高端智能手机中的嵌入式传感器的信息来收集来自VRU的自然主义运动数据。智能手机应用程序,Logyard在当前的研究中开发,允许记录高质量数据(在100 Hz加上GPS位置和速度下的三轴加速度和旋转,每个秒钟)。这样,来自ATV驱动程序在日常使用过程中的大量数据量在不同用例中,可以从大量用户传输,并在基于云的服务器中累积进行离线分析。除了关于如何在基于智能手机的平台中记录和管理数据的描述之外,还提供了如何将参与者与学习以及私人完整性问题和知情同意如何处理的过程,也可以从距离处理。通过呈现所呈现的智能手机的平台,可以轻松地管理大量参与者参加了几项平行的正在进行的研究。这使得该平台成为大规模,低成本,长期研究的强大工具,提供来自大型学习参与者的数据。以这种方式提供的信息可用于开发针对VRU的自动碰撞通知(ACN)系统,根据骑自行车,摩托车,摩托车手和ATV用户的“正常”以外的识别动作。

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