This $175,000 Project Grant from the National Science Foundation's Division of Computer and Network Systems, under the Computer and Information Science and Engineering program (CFDA 47.070), will fund research at Texas Tech University from April 2022 to March 2024 related to developing novel modeling, control, and optimization methods for connected and automated vehicles. The research aims to improve the efficiency and sustainability of urban transportation systems while respecting individual...
This $482,972 National Science Foundation (NSF) Engineering program (CFDA 47.041) grant supports fundamental research at North Carolina State University (NC State) to understand the behavior and interactions of mixed autonomous and human-driven vehicle traffic streams. The project aims to: (1) characterize the driving behaviors of human-driven and connected automated vehicles in conflicting traffic, (2) analyze the collective impact of mixed traffic on traffic flow, and (3) develop robust...
The National Science Foundation (NSF) Division of Civil, Mechanical, and Manufacturing Innovation awarded a $202,000 Project Grant to Michigan State University under the Engineering (CFDA 47.041) program. The funding will support collaborative research to develop scalable, data-driven predictive control frameworks for managing mixed traffic systems with connected and automated vehicles alongside human-driven vehicles. The project aims to enable advancements in transportation efficiency and...
The Colorado State University was awarded a $295,602 project grant from the National Science Foundation Division of Computer and Network Systems to support research titled "EAGER: EXPLORING MULTI-MODAL DEEP LEARNING SYSTEMS FOR SUSTAINABLE CONNECTED AND AUTONOMOUS VEHICLES" from October 1, 2021 to September 30, 2023. This award will fund research under the Computer and Information Science and Engineering federal grant program (CFDA 47.070), which supports investigator-initiated...
This $316,963 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program will support research to enhance the safety and reliability of autonomous vehicles. The project aims to thoroughly examine and improve the controller and machine learning components of autonomous driving systems through a combination of model-based and data-driven approaches. The research will focus on identifying spatial and temporal vulnerabilities that...
This National Science Foundation (NSF) CAREER Award under the Engineering (CFDA 47.041) program provides $556,507 in funding to Embry-Riddle Aeronautical University from July 1, 2023 to June 30, 2028. The award supports fundamental research to investigate human driving behavior and interactions among traffic participants, with the goal of enabling technological advances in autonomous and connected vehicles. The research will leverage an immersive virtual reality driving simulator to conduct...
This $272,238 Project Grant, awarded on July 15, 2024 by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070), supports research to enhance the safety and reliability of autonomous vehicles. The project aims to identify vulnerabilities in the software and machine learning components of autonomous vehicle systems, and develop mitigation techniques to improve their overall resilience. The research will combine model-based and...
This $350,961 National Science Foundation project grant supports the development of algorithms and design principles to enable safe and secure collaboration between artificial intelligence systems and human operators in autonomous vehicles. Funded under the Computer and Information Science and Engineering program, the objectives are to maintain human vigilance through secondary in-vehicle tasks calibrated to AI decision uncertainty levels, develop a fault-tolerant AI capable of assessing its own...
This $1,499,949 federal Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) will fund research to enhance the safety of autonomous vehicle (AV) systems. The key focus areas include: Developing rational machine learning (ML) models that can accurately predict driving decisions based on valid rationales, rather than inappropriate extrapolations from common scenarios. Integrating hardware reliability into the...
This $235,187 federal Project Grant award from the National Science Foundation's Engineering program (CFDA 47.041) supports research to develop principled algorithms and practical tools for systematically discovering and repairing unsafe behavior in multi-module autonomous vehicle systems. The key objectives are to: (1) create an automated method for constructing test scenarios that decouple high-level semantics and low-level details; (2) develop a search-based testing approach to efficiently...