Collaborative Research: Mobile Sensors as Traffic Probes - Addressing Transportation Modeling and Privacy Protection in an Integrated Framework

协作研究：移动传感器作为交通探针 - 在集成框架中解决交通建模和隐私保护问题

• 批准号: 1031452
• 负责人: Xuegang Ban
• 金额: $ 17.1万
• 依托单位: Rensselaer Polytechnic Institute
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-01 至 2014-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1031452&HistoricalAwards=false
• 关键词: Collaborative; Research; Mobile; Sensors; Traffic

The goal of this research is to develop concepts and methodologies that can be used to co-design transportation modeling methods and privacy protection techniques in collecting and using data from mobile traffic sensors. Mobile sensors such as cell phones move with the flow they are monitoring as opposed to fixed-location sensor in the road infrastructure. They promise low-cost collection of traffic data but also raise privacy concerns since their information is more closely tied to individual vehicles. Building on a close collaboration of transportation researchers and location privacy experts, this research aims to answer the following two interrelated questions: (1) what form of mobile data to use and how their use will impact privacy; and (2) what methods should be used to protect mobile data privacy and what are their implications to data requirements for modeling? Answering these questions will result in a framework with privacy-aware transportation modeling application-aware privacy protection, which can transform the way how mobile data are collected and used in transportation and many other science and engineering fields.This project builds on and will promote multidisciplinary collaborations, which benefit many audiences, including undergraduate and graduate students, transportation and location privacy researchers, and practitioners. Graduate and undergraduate students, especially those from underrepresented groups, can participate in the research. Results from this research will be used to enhance undergraduate and graduate level courses in both transportation engineering and computational privacy. Research findings can also help policy makers design proper policies/regulations on what mobile data to collect and how to better protect privacy. The PIs will work closely with transportation agencies and Standard groups and will make their best effort to convey research findings to transportation decision makers, engineers, the industry, and the academic communities.

本研究的目标是开发概念和方法，可用于共同设计交通建模方法和隐私保护技术，以收集和使用来自移动交通传感器的数据。与道路基础设施中的固定位置传感器不同，移动传感器（如手机）随着它们所监测的流量而移动。它们承诺以低成本收集交通数据，但也引发了隐私问题，因为它们的信息与每辆车的联系更紧密。在交通研究人员和位置隐私专家的密切合作基础上，本研究旨在回答以下两个相互关联的问题：(1)使用何种形式的移动数据及其使用将如何影响隐私；(2)应该使用什么方法来保护移动数据隐私，这些方法对建模的数据需求有什么影响？回答这些问题将产生一个具有隐私感知的运输建模应用感知隐私保护的框架，它可以改变移动数据在运输和许多其他科学和工程领域的收集和使用方式。该项目建立在并将促进多学科合作的基础上，这将使许多受众受益，包括本科生和研究生、交通和位置隐私研究人员以及从业者。研究生和本科生，特别是那些来自代表性不足群体的学生，可以参与研究。这项研究的结果将用于加强交通工程和计算隐私的本科和研究生水平的课程。研究结果还可以帮助政策制定者制定适当的政策/法规，规定收集哪些移动数据以及如何更好地保护隐私。pi将与交通运输机构和标准组织密切合作，尽最大努力将研究成果传达给交通运输决策者、工程师、行业和学术界。