CI-Planning: DriveSense: A Community Resource for Large-Scale Smartphone-Based Traffic and Driving Activity Data

CI 规划：DriveSense：基于智能手机的大规模交通和驾驶活动数据的社区资源

• 批准号: 1405882
• 负责人: Tamer Nadeem
• 金额: $ 9.99万
• 依托单位: Old Dominion University Research Foundation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-08-01 至 2015-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1405882&HistoricalAwards=false
• 关键词: CI; Planning; DriveSense; Community; Resource

Today's smartphones contain a number of sensors (e.g., GPS, accelerometer, camera) that can be used to reveal driver activity and traffic patterns when carried in a vehicle. This project aims to gather a large-scale set of smartphone sensor data from volunteers while they are driving. The data set and the tools we will provide for analysis and access will have an impact on multiple areas of research, including data mining, vehicular networks, intelligent transportation systems, and traffic engineering. Our first step in gathering such valuable data is to determine the particular types of data, tools and scenarios that would be most valuable to the research community.We plan to develop the DriveSense platform, a collection of tools for large-scale traffic and driving activity data collection. This will be accomplished through a large-scale deployment of a free smartphone application to collect data from a wide range of individuals, locations, and driving situations. We divide the components of DriveSense into platform components (software, tools) and management components (recruitment, data management). This will provide a rich and complex data set for use by the research community. This will support transportation research on the fine-grained information about traffic and driving behaviors collected by various sensors of a driver's smartphone, as well as enabling advances in more general research into the analysis of complex, spatio-temporal data.The first step is to explore, develop, and validate specific components of the DriveSense platform in order to reduce risk involved before beginning full-scale development. More specifically, during this planning phase of the project, we will:i) Develop and validate several components of the front-end application that will run on smartphones to collect data. We will develop a prototype of the DriveSense App that collects data for the Android platform.ii) Hold a workshop to get feedback on research community interests and needs. The objective of the workshop is to bring together experts from several research communities spanning computer and communication networks, transportation systems, and data analytics to discuss community needs and interests, challenges to be addressed, tools to be developed, and new research problems utilizing the driving activity data.The outcome of the planning phase will ensure we are able to capture the types of data most important to the community, so that the developed infrastructure will be of most benefit to the broader research community.

当今的智能手机包含许多传感器（例如 GPS、加速计、摄像头），可用于显示驾驶员在车辆中的活动和交通模式。该项目旨在从志愿者开车时收集大量智能手机传感器数据。 我们将为分析和访问提供的数据集和工具将对多个研究领域产生影响，包括数据挖掘、车辆网络、智能交通系统和交通工程。我们收集这些有价值的数据的第一步是确定对研究界最有价值的特定类型的数据、工具和场景。我们计划开发 DriveSense 平台，这是一个用于大规模交通和驾驶活动的工具集合数据收集。这将通过大规模部署免费智能手机应用程序来收集来自各种个人、位置和驾驶情况的数据来实现。我们将DriveSense的组件分为平台组件（软件、工具）和管理组件（招聘、数据管理）。 这将为研究界提供丰富而复杂的数据集。 这将支持对驾驶员智能手机的各种传感器收集的交通和驾驶行为的细粒度信息进行交通研究，并推动对复杂时空数据分析的更一般性研究的进展。探索、开发和验证 DriveSense 平台的特定组件，以便在开始全面开发之前降低所涉及的风险。更具体地说，在项目的规划阶段，我们将：i) 开发并验证将在智能手机上运行以收集数据的前端应用程序的多个组件。我们将开发一个为 Android 平台收集数据的 DriveSense 应用程序原型。ii) 举办研讨会以获取有关研究社区兴趣和需求的反馈。研讨会的目的是聚集来自计算机和通信网络、交通系统和数据分析等多个研究领域的专家，讨论社区的需求和兴趣、需要解决的挑战、需要开发的工具以及利用驾驶技术的新研究问题。规划阶段的结果将确保我们能够捕获对社区最重要的数据类型，以便开发的基础设施将为更广泛的研究社区带来最大利益。