CAREER: Data-driven Multiscale Modeling of Complex Traffic Systems Utilizing Networked Driving Simulators

职业：利用网络驾驶模拟器对复杂交通系统进行数据驱动的多尺度建模

• 批准号: 2238359
• 负责人: Subhradeep Roy
• 金额: $ 55.65万
• 依托单位: Embry-Riddle Aeronautical University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-07-01 至 2028-06-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2238359&HistoricalAwards=false
• 关键词: CAREER; Data; driven; Multiscale; Modeling

This Faculty Early Career Development (CAREER) award supports research that will investigate human driving behavior and interactions among traffic participants, with the aim of empowering technological advances in autonomous and connected vehicles. Understanding human driving behavior is vital for engineering connected and autonomous vehicles that safely share roads with humans. This award supports fundamental research about human driving behavior, including their physiological and cognitive engagement with other drivers and the environment. To ensure a safe and cost-effective approach, the project will utilize an immersive virtual reality driving simulator. Controlled and repeatable experiments will be conducted in this environment by systematically exposing drivers to a variety of traffic scenarios. The project will integrate educational activities that introduce students, including students from underrepresented groups, to STEM topics, as well as outreach activities to raise awareness of the general public to traffic safety, secondary crashes, and impaired driving. This CAREER project will study multiscale traffic interactions, at the vehicle, driver, and cognitive levels. Using brain scans for multiple interacting participants, this project will investigate whether brain coupling characteristics emerge among drivers at the group level, and how cognitive level engagement relates to other driving behaviors. The research findings have potentially transformative implications for cognitive and behavioral neuroscience and technological advancement in driver assistance systems. The project will generate rich multiscale datasets, identify experimentally-informed modeling parameters, and discover experimentally-validated traffic models.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.

该学院早期职业发展（CAREER）奖支持研究人类驾驶行为和交通参与者之间的互动，旨在推动自动驾驶和联网车辆的技术进步。了解人类驾驶行为对于设计与人类安全共享道路的互联自动驾驶汽车至关重要。该奖项支持有关人类驾驶行为的基础研究，包括他们与其他驾驶员和环境的生理和认知互动。为了确保安全且经济高效的方法，该项目将利用沉浸式虚拟现实驾驶模拟器。通过系统地将驾驶员暴露在各种交通场景中，将在这种环境中进行受控和可重复的实验。该项目将整合向学生（包括来自弱势群体的学生）介绍 STEM 主题的教育活动，以及提高公众对交通安全、二次碰撞和酒后驾驶意识的外展活动。该职业项目将研究车辆、驾驶员和认知层面的多尺度交通交互。该项目将利用多个互动参与者的脑部扫描，研究群体层面的驾驶员之间是否出现大脑耦合特征，以及认知水平参与度与其他驾驶行为之间的关系。研究结果对认知和行为神经科学以及驾驶员辅助系统的技术进步具有潜在的变革性影响。该项目将生成丰富的多尺度数据集，识别基于实验的建模参数，并发现经过实验验证的交通模型。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。