ERI: Rethinking Traffic Flow in the Era of Electric Vehicles with Driver Assistance and Automation

该工程研究启动（ERI）项目将支持基础研究，以帮助了解电动汽车对交通流量和运营的潜在好处，并在电动汽车普及的时代，为交通规划，交通管理和交通基础设施设计的重要影响提供有价值的见解。与内燃机车辆不同，电动汽车提供响应迅速且易于获得的性能，因为电动动力系统几乎可以立即提供峰值扭矩和快速加速，并通过电动机特有的再生制动立即减速。这些动力系统的优势可以使当今的高级驾驶员辅助系统（ADAS）和未来的车辆自动化技术更有效地运行，并可能减少交通拥堵，提高安全性，降低整个车队的总体能耗和排放。最终，这些对交通运输行业的好处可以提高生产力，增强经济活力和生活质量，减轻环境影响，减少能源依赖。该奖项重点关注配备当今商用先进驾驶辅助系统（如自适应巡航控制系统）的电动汽车。该研究将（i）开发标准化程序以收集轨迹水平的经验数据，（ii）通过使用来自不同制造商的生产车辆进行现场实验来分析具有自适应巡航控制的电动汽车的综合车辆跟随行为，（iii）开发新的微观水平模型以捕获包含全速范围的车辆跟随行为，及（iv）在仿真中应用微观模型进行前瞻性分析，发展宏观模型（例如基本图），并探讨对交通控制和管理，以及其他方面（例如交通安全和废气排放影响）的可能影响。该研究将为交通从业者和未来的毕业生准备车辆自动化和电气化的新兴技术，以最终加速将本研究获得的知识应用于真实的世界交通工程实践。这项研究将为交通研究人员和从业者提供宝贵的经验数据集、模型和初步见解。该奖项反映了NSF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 Engineering Research Initiation (ERI) project will support fundamental research to help understand electric vehicles’ potential benefit to traffic flow and operations, and to provide valuable insights on the important implications in transportation planning, traffic management, and transportation infrastructure design in an era of increasing electric vehicle adoption. Unlike vehicles with internal combustion engines, electric vehicles offer responsive and easily accessible performance because electric powertrain can deliver peak torque and swift acceleration almost immediately and decelerate immediately via regenerative braking unique to electric motors. These powertrain advantages can enable today’s advanced driver assistance systems (ADAS) and future vehicle automation technologies to operate more efficiently, and potentially reduce traffic congestion, improve safety, and reduce overall energy consumption and emissions of the entire vehicle fleet. Ultimately, these benefits to the transportation sector could improve productivity, enhance economic vitality and quality of life, mitigate environmental impact, and reduce energy dependence.This award focuses on electric vehicles equipped with today’s commercially available Advanced Driver Assistance Systems such as Adaptive Cruise Control. The research will (i) develop standardized procedures to collect empirical data at the trajectory level, (ii) analyze the comprehensive car following behavior of electric vehicles with Adaptive Cruise Control by conducting field experiments using production vehicles from different manufacturers, (iii) develop new microscopic level models to capture the car following behavior that encompasses the full speed range, and (iv) implement the microscopic models in simulation to perform prospective analysis, develop macroscopic models such as the fundamental diagram, and explore possible implications for traffic control and management as well as other aspects such as traffic safety and emissions impacts. The research will prepare transportation practitioners and future graduates for emerging technologies in vehicle automation and electrification to ultimately accelerate the adoption of knowledge gained from this research into real world transportation engineering practice. This research will provide invaluable empirical datasets, models, and initial insights to the community of transportation researchers and practitioners.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.