A private matter: the implications of privacy regulations for intelligent transportation systems

The rapid development and deployment of Intelligent Transportation Systems (ITS) that utilize data on the movement of vehicles can greatly benefit transportation network operations and safety, but may test the limits of personal privacy. In this paper we survey the current state of legal and industry-led privacy protections related to ITS and find that the lack of existing standards, rules, and laws governing the collection, storage, and use of such information could both raise troubling privacy questions and potentially hinder implementation of useful ITS technologies. We then offer practical recommendations for addressing ITS-related privacy concerns though both privacy-by-design solutions (that build privacy protections into data collection systems), and privacy-by-policy solutions (that provide guidelines for data collection and treatment) including limiting the scope of data collection and use, assuring confidentially of data storage, and other ways to build trust and foster consumer consent.     

Analyzing voter support for California’s local option sales taxes for transportation

Local and regional governments in the U.S. rely increasingly on voter-approved local option sales taxes (LOSTs) to fund transportation capital investments, maintenance, and operations. LOSTs typically present voters with lists of local transportation projects and programs to be funded by a ¼ to 1 percent sales tax increase. Most research on LOSTs are case studies, which make generalizations about LOSTs difficult. We conducted a comprehensive, multi-jurisdictional analysis of LOST measures in California, the U.S. state with the greatest number of LOST measures. We examined 76 LOST measures put to voters between 1976 and 2016 to assess factors associated with voter support. LOSTs in California are enacted by counties, which we examined in addition to smaller intra-county geographies using both regression models and case studies. We tested several explanatory variables for association with voter support including macroeconomic and political context, planned measure expenditures, voter characteristics, and spatial distribution of proposed projects. We found that funding dedicated to public transit and returned to local jurisdictions predicts support at the county level, and that LOSTs that create new taxes—as opposed to extending or renewing existing taxes—are less popular with voters, all else equal. Our analyses of sub-county geographies revealed that political party affiliation is the strongest predictor of local voter support for LOSTs and that voters living adjacent to funded projects tended to be more supportive of LOSTs.