CAREER: A Combined Experimental and Theoretical Study of Human-Connected Automated Vehicle Interactions

本奖学金将透过提高交通系统的效率及安全，为国民经济及福利作出贡献。这将通过引入一种基于车辆自动化和通信技术的新型拥堵管理策略来实现。目前的自动驾驶汽车开发工作主要集中在隔离车辆的安全性上，很少考虑设计对驾驶员和运输系统效率的影响。在许多情况下，这种设计方法可能会给人类司机带来额外的拥堵和不可预见的安全问题。通过仔细描述驾驶员与联网自动驾驶汽车（cav）之间的相互作用，这个CAREER项目将为拥堵管理带来新的范例，并将更有效地利用我们的道路系统，并显著减少整个交通系统的拥堵。这笔拨款还将用于开发一个在线智能辅导系统，该系统提供系统的方法，教授学生在未来高度多样化和动态的工作环境中发挥作用所需的技能和专业知识。这个定制化的教育平台可以被全国其他学科和其他大学采用。这项研究的结果将通过圆桌讨论、利益相关者会议和网络研讨会传播给广泛的受众。本CAREER基金的研究目的是验证人类在与自动驾驶汽车互动时表现出与与他人互动时不同的决策逻辑这一假设。这一假设将通过广泛的现场测试和收集人类驾驶员对各种CAV机动的行为的数据进行评估。该项目还将探索随着时间的推移，人类行为响应cav进化的潜力，并将引入健壮的模型来捕捉人类行为的这种变化。利用现场实验的结果，该项目将引入分散的基于自动驾驶汽车的交通塑造方法，通过利用自动驾驶汽车影响人类驾驶员的行为来维持理想的交通状态。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

This Faculty Early Career Development (CAREER) grant will contribute to the national economy and welfare by enhancing the transportation system efficiency and safety. This will be achieved through introducing a novel congestion management strategy based on vehicle automation and communications technology. The current automated vehicle development efforts mainly focus on the safety of isolated vehicles with little consideration of the impacts of design on human drivers and on transportation system efficiency. Such design approaches, in many cases, can potentially result in additional congestion and unforeseen safety issues for human drivers. Through careful characterization of the interactions between human drivers and connected automated vehicles (CAVs), this CAREER project will lead to new paradigms for congestion management and will result in more efficient utilization of our roadway system and a significant reduction in congestion throughout the transportation system. This grant will also result in the development of an online intelligent tutoring system that offers a systematic approach to teach students the skills and expertise required to function within highly diverse and dynamic work environments of the future. This customizable educational platform can be adopted by other disciplines and other universities across the nation. The findings of this study will be disseminated to a wide range of audiences through round table discussions, stakeholder meetings, and webinars.The research objective of this CAREER grant is to test the hypothesis that humans exhibit a different decision-making logic when interacting with CAVs in comparison with when interacting with other humans. This hypothesis will be evaluated using extensive field tests and data collection from human driver behavior in response to various CAV maneuvers. This project will also explore the potential for the evolution of human behavior in response to CAVs over time and will introduce robust models to capture such changes in human behavior. Utilizing the findings from the field experiments, this project will lead to the introduction of decentralized CAV-based traffic shaping methodologies that can maintain a desired traffic state by utilizing CAVs to influence the behavior of human drivers.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.