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

这项研究的目标是开发可用于共同设计交通建模方法和隐私保护技术的概念和方法，以收集和使用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)随着它们监控的流量而移动。他们承诺以低成本收集交通数据，但也引发了隐私问题，因为他们的信息与个人车辆更紧密地联系在一起。在交通研究人员和位置隐私专家密切合作的基础上，本研究旨在回答以下两个相互关联的问题：(1)使用什么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，以及它们对建模数据需求的影响是什么？回答这些问题将产生一个具有隐私意识的交通建模应用程序隐私保护框架，它可以改变移动数据在交通和许多其他科学和工程领域收集和使用的方式。该项目建立在并将促进多学科合作，使包括本科生和研究生、交通和位置隐私研究人员和从业者在内的许多受众受益。研究生和本科生，特别是那些来自代表人数不足的群体的学生，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方面的本科生和研究生水平的课程。研究结果还可以帮助政策制定者就收集哪些移动数据以及如何更好地保护隐私制定适当的政策/法规。PIS将与交通机构和标准组织密切合作，并将尽最大努力将研究成果传达给交通决策者、工程师、行业和学术界。

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.