CAREER: Conflicting Traffic Streams with Mixed Traffic: Modeling and Control

职业：冲突交通流与混合交通：建模和控制

• 批准号: 2401555
• 负责人: Danjue Chen
• 金额: $ 50万
• 依托单位: North Carolina State 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: 2023-10-01 至 2025-11-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2401555&HistoricalAwards=false
• 关键词: CAREER; Conflicting; Traffic; Streams; Mixed

This Faculty Early Career Development (CAREER) grant supports fundamental research in understanding of traffic flow patterns in mixed autonomous and human-controlled traffic streams. Emerging connected automated vehicle (CAV) technologies hold enormous potential to reduce transportation system congestion, improve safety, and facilitate higher energy efficiency. While anticipated benefits are greatest when all vehicles on the roads are CAVs, the near-term future will consist of mixed connected vehicles (CVs) connected automated vehicles and non-connected (human-driven, or HV) vehicles. This project will study mixed traffic streams, quantifying their impact on congestion and traffic flow, and develop robust strategies intended to improve performance and safety of the system as a whole, thereby enabling better understanding of how different vehicle types interact in traffic. The results will guide the development of roadway design, policies, and long-term planning for future transportation systems. The research activities will be closely integrated with a set of education and outreach activities to effectively promote smart and sustainable transportation. These activities include (i) developing a set of tools that will be shared with the research and practice communities (e.g., portable driving simulators, and an open-sourced micro-simulation platform), (ii) enhancing existing engineering curricula, (iii) broadening participation of women in STEM, and (iv) providing outreach to a broad audience, including K-12 students and teachers as well as cross-sector research communities. The research objectives of this project are to (i) characterize the driving behaviors of HVs and CAVs in conflicting traffic streams, (ii) the collective impact of mixed traffic on the traffic flow, and (iii) investigate robust tactical-level control strategies for CAVs to improve system performance with respect to throughput, traffic flow stability, and safety. The research involves data collection on using driving simulators and field tests, establishment of behavior models for different vehicle types (i.e., CAVs, CVs, and HVs) based on the collected data, and design and evaluation of tactical level control strategies using rule-based and Artificial Intelligent (AI)-based control approaches. This research will uncover the cooperative behavior of CAVs and the behavior of HVs and CVs under cooperation in the context of conflicting traffic streams. The research is expected to produce effective control strategies for CTS with mixed traffic. The outreach plan will provide high school students and teachers with exposure to the university's virtual driving lab as well as to research challenges in emerging transportation systems.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.

这项教师早期职业发展（Career）基金支持理解混合自主和人为控制交通流中交通流模式的基础研究。新兴的互联自动驾驶汽车（CAV）技术在减少交通系统拥堵、提高安全性和提高能源效率方面具有巨大潜力。当道路上的所有车辆都是自动驾驶汽车时，预期的好处是最大的，但在不久的将来，混合联网汽车（cv）将连接自动驾驶汽车和非联网（人工驾驶或HV）汽车。该项目将研究混合交通流，量化其对拥堵和交通流量的影响，并制定旨在提高整个系统性能和安全性的稳健策略，从而更好地了解不同类型的车辆在交通中如何相互作用。研究结果将指导道路设计、政策制定和未来交通系统的长期规划。研究活动将与一系列教育和外展活动紧密结合，以有效推广智能和可持续交通。这些活动包括(i)开发一套将与研究和实践社区共享的工具（例如，便携式驾驶模拟器和开源微模拟平台），（ii）增强现有的工程课程，（iii）扩大女性在STEM中的参与，以及（iv）向广泛的受众提供外展服务，包括K-12学生和教师以及跨部门研究社区。该项目的研究目标是(i)描述hv和cav在冲突交通流中的驾驶行为，（ii）混合交通对交通流的总体影响，以及（iii）研究cav的稳健战术级控制策略，以提高系统在吞吐量、交通流稳定性和安全性方面的性能。研究内容包括使用驾驶模拟器和现场测试收集数据，根据收集的数据建立不同类型车辆（即cav， cv和hv）的行为模型，并采用基于规则和基于人工智能（AI）的控制方法设计和评估战术级控制策略。本研究将揭示在交通流冲突的背景下，自动驾驶汽车的合作行为以及自动驾驶汽车和自动驾驶汽车在合作下的行为。该研究有望为混合交通的CTS提供有效的控制策略。该推广计划将为高中学生和教师提供接触大学虚拟驾驶实验室的机会，并研究新兴交通系统的挑战。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。