An official website of the United States government
Connected autonomous vehicles (CAVs) have emerged as a promising solution for enhancing transportation efficiency. However, the increased adoption of CAVs is expected to lead to a rise in transportation demand and, subsequently, higher energy consumption. In this context, electric CAVs (E-CAVs) present a significant opportunity to shape the future of efficient transportation systems. While conventional CAVs possess the potential to reduce fuel consumption, E-CAVs offer similar prospects but through distinct approaches. Notably, the control of acceleration and regenerative brakes in E-CAVs stands out as an area of immense potential for increasing efficiency, leveraging various control methods in conjunction with the cooperative and perception capabilities inherent in CAVs. To bridge this knowledge gap, this paper conducts a comprehensive survey of energy efficiency methods employed in conventional CAVs while also exploring energy efficiency strategies specifically tailored for E-CAVs.
more »
« less
This content will become publicly available on February 1, 2026
Testing and Verification of Connected and Autonomous Vehicles: A Review
Connected and Autonomous Vehicles (CAVs) have the potential to revolutionize transportation by addressing critical challenges such as safety, energy efficiency, traffic congestion, and environmental impact. Realizing these benefits, however, requires the development of a rigorous testing and verification framework to enable the safe, efficient, and reliable deployment of CAVs across diverse operational scenarios. Despite the growing body of research, there remains a significant gap in review papers that comprehensively summarize recent studies related to the testing and verification of CAVs while identifying current challenges and highlighting future research directions. This paper seeks to address this gap by presenting a comprehensive review of the existing testing and verification frameworks for CAVs and identifying their associated challenges. Key topics covered include scenario generation, verification cost functions, assertion values, and security considerations. Furthermore, the paper highlights limitations within current frameworks, emphasizing the gaps that hinder systematic and comprehensive evaluations.
more »
« less
- Award ID(s):
- 2241718
- PAR ID:
- 10633974
- Publisher / Repository:
- MDPI, Electronics Journal
- Date Published:
- Journal Name:
- Electronics
- Volume:
- 14
- Issue:
- 3
- ISSN:
- 2079-9292
- Page Range / eLocation ID:
- 600
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Abstract Connected autonomous vehicles (CAVs) have the potential to deal with the steady increase in road traffic while solving transportation related issues such as traffic congestion, pollution, and road safety. Therefore, CAVs are becoming increasingly popular and viewed as the next generation transportation solution. Although modular advancements have been achieved in the development of CAVs, these efforts are not fully integrated to operationalize CAVs in realistic driving scenarios. This paper surveys a wide range of efforts reported in the literature about the CAV developments, summarizes the CAV impacts from a statistical perspective, explores current state of practice in the field of CAVs in terms of autonomy technologies, communication backbone, and computation needs. Furthermore, this paper provides general guidance on how transportation infrastructures need to be prepared in order to effectively operationalize CAVs. The paper also identifies challenges that need to be addressed in near future for effective and reliable adoption of CAVs.more » « less
-
Abstract In April 2023, the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), in partnership with the National Institute of Child Health and Human Development, the National Institute on Aging, and the Office of Behavioral and Social Sciences Research, hosted a 2‐day online workshop to discuss neural plasticity in energy homeostasis and obesity. The goal was to provide a broad view of current knowledge while identifying research questions and challenges regarding neural systems that control food intake and energy balance. This review includes highlights from the meeting and is intended both to introduce unfamiliar audiences with concepts central to energy homeostasis, feeding, and obesity and to highlight up‐and‐coming research in these areas that may be of special interest to those with a background in these fields. The overarching theme of this review addresses plasticity within the central and peripheral nervous systems that regulates and influences eating, emphasizing distinctions between healthy and disease states. This is by no means a comprehensive review because this is a broad and rapidly developing area. However, we have pointed out relevant reviews and primary articles throughout, as well as gaps in current understanding and opportunities for developments in the field.more » « less
-
Blockchain has emerged as a solution for ensuring accurate and truthful environmental variable monitoring needed for the management of pollutants and natural resources. The immutability property of blockchain helps protect the measured data on pollution and natural resources to enable truthful reporting and effective management and control of polluting agents. However, specifics on what to measure, how to use blockchain, and highlighting which blockchain frameworks have been adopted need to be explored to fill the research gaps. Therefore, we review existing works on the use of blockchain for monitoring and managing environmental variables in this paper. Specifically, we examine existing blockchain applications on greenhouse gas emissions, solid and plastic waste, food waste, food security, water usage, and the circular economy and identify what motivates the adoption of blockchain, features sought, used blockchain frameworks and consensus algorithms, and the adopted supporting technologies to complement data sensing and reporting. We conclude the review by identifying practical works that provide implementation details for rapid adoption and remaining challenges that merit future research.more » « less
-
Abstract Synthetic ensemble forecasts are an important tool for testing the robustness of forecast‐informed reservoir operations (FIRO). These forecasts are statistically generated to mimic the skill of hindcasts derived from operational ensemble forecasting systems, but they can be created for time periods when hindcast data are unavailable, allowing for a more comprehensive evaluation of FIRO policies. Nevertheless, it remains unclear how to determine whether a candidate synthetic ensemble forecasting approach is sufficiently representative of its real‐world counterpart to support FIRO policy evaluation. This highlights a need for formalfit‐for‐purposevalidation frameworks to advance synthetic forecasting as a generalizable risk analysis strategy. We address this research gap by first introducing a novel operations‐based validation framework, where reservoir storage and release simulations under a FIRO policy are compared when forced with a single ensemble hindcast and many different synthetic ensembles. We evaluate the suitability of synthetic forecasts based on formal probabilistic verification of the operational outcomes. Second, we develop a new synthetic ensemble forecasting algorithm and compare it to a previous algorithm using this validation framework across a set of stylized, hydrologically diverse reservoir systems in California. Results reveal clear differences in operational suitability, with the new method consistently outperforming the previous one. These findings demonstrate the promise of the newer synthetic forecasting approach as a generalizable tool for FIRO policy evaluation and robustness testing. They also underscore the value of the proposed validation framework in benchmarking and guiding future improvements in synthetic forecast development.more » « less
