In response to the quick development and adoption of connected and autonomous vehicles (CAVs), U.S. cities and states have recently started building CAV cyberinfrastructure. However, there is not an adequate supply of skilled research workforce in this field. A key obstacle to such workforce development is the lack of well-structured training programs for utilizing CAV cyberinfrastructure to enable and potentially transform fundamental CAV research. To address this issue, a project-oriented training program will be developed in this CyberTraining project to enable scientific research workforce development for CAV cyberinfrastructure. It is estimated that the adoption of CAVs would lead to nearly $800 billion in annual social and economic benefits by 2050, therefore, it is important for the nation to invest in CAV cyberinfrastructure research workforce training programs. The proposed training program targets students and early-stage researchers who are interested in CAVs, including participants with a broad diversity in academic level and in experience level with CAVs. It is expected that more than 100 trainees will participate every year in the training program, including researchers from various domains such as cyber-physical systems, edge computing, wireless networking, deep learning, computer vision, and big data. A longstanding collaboration with the trainees and/or their advisors will be built to ensure a broad adoption of CAV cyberinfrastructure by the research community to catalyze major research advances. The long-term goal of this project is to develop a first of its kind open CAV cyberinfrastructure, an integrated training and research hub, to accelerate research and education in CAVs.
The goal of this project is to develop a collaborative and integrated training program to enable scientific research work force development for Connected and Autonomous Vehicle CyberInfrastructure (CAV-CI) and foster broad adoption of CAV-CI to advance fundamental CAV related research. To achieve these goals, the project will leverage existing partnerships with relevant stakeholders to create tailored, high-impact, engaging, collaborative, and integrated training modules for CAV-CI research workforce development. With the aim of enhancing trainees design and implementation capabilities, problem-solving skills, and critical thinking ability, the proposed training program will result in: (1) a project-oriented short course plus long-term coaching and support, (2) hands-on training modules on the perception, network, and application layers in CAV-CI, (3) an annual research workshop that disseminates research results and receives feedback on the training program from the research and industrial communities, and (4) research projects for students supported through NSF's Research Experiences for Undergraduates (REU)program and capstone projects for senior undergraduates. During the training workshops, project-oriented training will be offered to actively engage trainees in learning and solving real-world problems. Three sample research projects will be designed, allowing trainees to develop complete research skills, i.e., competency to solve authentic problems. Following every sample research project, with each having a strong practical relevance and meaningfulness, two versions of training modules will be developed to reach a broader trainee group: a fundamental training module for undergraduate students and community college educators, and a research-intensive training module for graduate students and postdocs. By taking either the fundamental or the research-intensive training modules, trainees will enhance their problem-solving skills, improve their creative and independent thinking ability, as well as gaining enthusiasm and confidence in conducting CAV-CI enabled research. The CAV-CI education, research and training activities include specific goals to train individuals from underrepresented groups and the broader STEM workforce.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
