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One dimension of the emerging politics of connected and automated vehicles (CAVs) is the development of public concerns over their societal implications and associated policy issues. This study uses original survey data from the United States to contribute to the anticipation of future policy and political issues for CAVs. Several studies have surveyed the public regarding CAVs; however, there are few studies that highlight the multidimensional public concerns that CAVs will most likely bring. The study breaks down the concept of “public” by showing that the demographic variables of gender, age, race, ethnicity, income, location (rural, suburban, urban), and political ideology (conservative, moderate, liberal) are significantly associated with three of the most salient public concerns to date (safety, privacy, and data security). Furthermore, the effects of demographic variables also vary across the type of policy issue. For example, women tend to be more concerned about safety than their male counterparts, and Hispanics (Latinx) tend to be more concerned about privacy than non-Hispanics. The research shows how the social scientific analysis of the “politics” of CAVs will require attention to the variegated connections between different types of public concern and different demographic variables.

 

With the growth of commercial and recreational use of unmanned aerial vehicles (UAVs, or drones), there is increasing attention to the need for regulation. A systematic review is conducted using a multiple comparative perspective: across three political jurisdictions (the United States, the European Union, and Japan) and across two areas of societal implication and policy (i.e., privacy and safety), with additional comparisons drawn from regulations for related cyber-physical systems. The multiple comparative analysis conducted in this paper shows that safety is a much more salient concern than privacy. Moreover, safety is focused on technical features of the UAVs, registration and certification, and differentiation by use case. Privacy regulations tend to follow broader digital privacy guidelines. Although there are some privacy rules that are UAV-specific, many of them do not yet directly address privacy challenges that are specific for UAVs. Additional comparisons with safety and privacy policies for automated vehicles and the smart grid reveal areas of potential development for harmonization and policy guidance. The study concludes with ten recommendations for future policy development. 

Complementary features of randomized controlled trials (RCTs) and observational studies (OSs) can be used jointly to estimate the average treatment effect of a target population. We propose a calibration weighting estimator that enforces the covariate balance between the RCT and OS, therefore improving the trial-based estimator's generalizability. Exploiting semiparametric efficiency theory, we propose a doubly robust augmented calibration weighting estimator that achieves the efficiency bound derived under the identification assumptions. A nonparametric sieve method is provided as an alternative to the parametric approach, which enables the robust approximation of the nuisance functions and data-adaptive selection of outcome predictors for calibration. We establish asymptotic results and confirm the finite sample performances of the proposed estimators by simulation experiments and an application on the estimation of the treatment effect of adjuvant chemotherapy for early-stage non-small-cell lung patients after surgery.

 

This study develops a comparative, sociotechnical design perspective for interdisciplinary teams of social scientists and computer scientists. Sociotechnical design refers to identifying both technical and governance challenges and to understanding the ways in which the two types of problems affect and define each other. Approaching design as an open-ended, iterative process, the study develops a triple comparative perspective to problem finding and solutions: across two types of technological systems (the smart grid and connected and automated vehicles), three areas of societal implication and values (safety, equity, and privacy), and two continents (North America and Europe with a focus on the U.S. and Germany). The study then describes the implementation in an international collaboration of research and teaching. The collaborative experience and comparative research provide insights into the salience of the values across technological systems, portability of solutions across technological systems, and potential for policy harmonization across countries. 

Utilities and local power providers throughout the world have recognized the advantages of the "smart grid" to encourage consumers to engage in greater energy efficiency. The digitalization of electricity and the consumer interface enables utilities to develop pricing arrangements that can smooth peak load. Time-varying price signals can enable devices associated with heating, air conditioning, and ventilation (HVAC) systems to communicate with market prices in order to more efficiently configure energy demand. Moreover, the shorter time intervals and greater collection of data can facilitate the integration of distributed renewable energy into the power grid. This study contributes to the understanding of time-varying pricing using a model that examines the extent to which transactive energy can reduce economic costs of an aggregated group of households with varying levels of distributed solar energy. It also considers the potential for transactive energy to smooth the demand curve. 

Transactive Energy (TE) is an emerging discipline that utilizes economic and control techniques for operating and managing the power grid effectively. Distributed Energy Resources (DERs) represent a fundamental shift away from traditionally centrally managed energy generation and storage to one that is rather distributed. However, integrating and managing DERs into the power grid is highly challenging owing to the TE implementation issues such as privacy, equity, efficiency, reliability, and security. The TE market structures allow utilities to transact (i.e., buy and sell) power services (production, distribution, and storage) from/to DER providers integrated as part of the grid. Flexible power pricing in TE enables power services transactions to dynamically adjust power generation and storage in a way that continuously balances power supply and demand as well as minimize cost of grid operations. Therefore, it has become important to analyze various market models utilized in different TE applications for their impact on above implementation issues.In this demo, we show-case the Transactive Energy Simulation and Analysis Toolsuite (TE-SAT) with its three publicly available design studios for experimenting with TE markets. All three design studios are built using metamodeling tool called the Web-based Graphical Modeling Environment (WebGME). Using a Git-like storage and tracking backend server, WebGME enables multi-user editing on models and experiments using simply a web-browser. This directly facilitates collaboration among different TE stakeholders for developing and analyzing grid operations and market models. Additionally, these design studios provide an integrated and scalable cloud backend for running corresponding simulation experiments.