CPS: DFG Joint: Medium: Collaborative Research: Perceptive Stochastic Coordination in Mass Platoons of Automated Vehicles

CPS：DFG 联合：媒介：协作研究：自动车辆大规模排中的感知随机协调

基本信息

批准号：
1931981
负责人：
Javad Mohammadpour Velni
金额：
$ 31.74万
依托单位：
University of Georgia Research Foundation Inc
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2020
资助国家：
美国
起止时间：
2020-01-01 至 2023-02-28
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1931981&HistoricalAwards=false
关键词：
CPS DFG Joint Medium Collaborative

项目摘要

Connected Automated Vehicle (CAV) applications are expected to transform the transportation landscape and address some of the pressing safety and efficiency issues. While advances in communication and computing technologies enable the concept of CAVs, the coupling of application, control and communication components of such systems and interference from human actors, pose significant challenges to designing systems that are safe and reliable beyond prototype environments. Realizing CAV applications, in particular in situations where humans may partly remain in the loop, requires addressing uncertainties that arise from human input. Large scale deployment of CAVs will also require addressing challenges in coordination of actions among CAVs and with human operated systems. To address these challenges, this project develops a novel model-based stochastic hybrid systems (SHS)-theoretic approach that relies on describing and communicating behaviors of actors in the system in the form of evolving SHS using Bayesian learning. The models are then utilized in a stochastic model predictive control (SMPC) framework for optimal coordination of actions. The proposed research will provide wide-ranging societal benefits through three major impact areas: first, by advancing research in stochastic communication-aware control design for hybrid systems; second, through the development of new models and advanced controllers to address the emerging challenges of coordinating mixed systems of automated and manned vehicles, hence opening new vistas in other areas involving general multi-agent systems; and third, through educational and outreach activities that are natural extensions of this multidisciplinary research. This project is also the first fruits of a recent National Science Foundation/Deutsche Forschungs Gesellschaft (NSF/DFG) collaboration on cyber-physical systems (CPS). Through this collaboration, NSF funds the US component (University of Central Florida and University of Georgia) while the German partners (University of Technology and University of Koblenz-Landau) are funded by DFG.The overarching goal of this collaborative research is to introduce SHS-based modeling and control concepts to allow the design of highly efficient CAV systems capable of large scale coordination (mass platooning). Such designs are currently challenging due to the uncertainties that stem from human input and communication of actors. The key objectives of the project are to: (1) develop methods for capturing the human, sensors and communication induced uncertainties of mixed automated and manned systems in a stochastic hybrid system form (perception maps) and communicating them in a control-aware fashion, (2) employ the models in an SMPC framework to produce multi-modal decisions and lower level longitudinal motion control in a single unified framework, and (3) validate the analytical outcomes through both extensive data-driven co-simulation using industry utilized models, and a fleet of realistic small CAVs and a full scale prototype CAV.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.

联网自动驾驶汽车 (CAV) 应用预计将改变交通格局并解决一些紧迫的安全和效率问题。虽然通信和计算技术的进步使 CAV 的概念成为可能，但此类系统的应用、控制和通信组件的耦合以及人类参与者的干扰，对设计超出原型环境的安全可靠的系统提出了重大挑战。实现 CAV 应用，特别是在人类可能部分参与循环的情况下，需要解决人类输入产生的不确定性。 CAV 的大规模部署还需要解决 CAV 之间以及与人类操作系统协调行动方面的挑战。为了应对这些挑战，该项目开发了一种新颖的基于模型的随机混合系统（SHS）理论方法，该方法依赖于使用贝叶斯学习以不断发展的 SHS 的形式描述和交流系统中参与者的行为。然后将这些模型用于随机模型预测控制 (SMPC) 框架中，以实现最佳的行动协调。拟议的研究将通过三个主要影响领域提供广泛的社会效益：首先，推进混合系统随机通信感知控制设计的研究；其次，通过开发新模型和先进控制器来解决协调自动驾驶和有人驾驶混合系统的新挑战，从而为涉及通用多智能体系统的其他领域开辟新前景；第三，通过作为多学科研究的自然延伸的教育和推广活动。该项目也是美国国家科学基金会/德国研究基金会 (NSF/DFG) 最近在网络物理系统 (CPS) 方面合作的首批成果。通过此次合作，NSF 资助美国部分（中佛罗里达大学和佐治亚大学），而德国合作伙伴（科技大学和科布伦茨-兰道大学）则由 DFG 资助。这项合作研究的总体目标是引入 SHS基于建模和控制概念，允许设计能够进行大规模协调（大规模编队）的高效 CAV 系统。由于人类输入和参与者沟通带来的不确定性，此类设计目前具有挑战性。该项目的主要目标是：（1）开发方法，以随机混合系统形式（感知图）捕获人类、传感器和通信引起的混合自动化和载人系统的不确定性，并以控制感知方式进行通信， (2) 采用 SMPC 框架中的模型在单个统一框架中生成多模式决策和较低级别的纵向运动控制，以及 (3) 通过使用行业使用的模型进行广泛的数据驱动协同仿真来验证分析结果，和一支现实的小舰队CAV 和全尺寸原型 CAV。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。

项目成果

期刊论文数量（7）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Gaussian Process based Stochastic Model Predictive Control for Cooperative Adaptive Cruise Control

基于高斯过程的协同自适应巡航控制随机模型预测控制

DOI：
10.1109/vnc52810.2021.9644629
发表时间：
2021-11
期刊：
IEEE Vehicular Networking Conference (VNC
影响因子：
0
作者：
Mosharafian, Sahand;Razzaghpour, Mahdi;Fallah, Yaser P.;Mohammadpour Velni, Javad
通讯作者：
Mohammadpour Velni, Javad

Impact of Information Flow Topology on Safety of Tightly-coupled Connected and Automated Vehicle Platoons Utilizing Stochastic Control

信息流拓扑对利用随机控制的紧耦合连接和自动化车队安全的影响

DOI：
10.48550/arxiv.2203.15772
发表时间：
2022-03-29
期刊：
2022 European Control Conference (ECC)
影响因子：
0
作者：
Mahdi Razzaghpour;Sah;Mosharafian;Arash Raftari;J. Mohammadpour;Y. P. Fallah
通讯作者：
Y. P. Fallah

Eco-driving Trajectory Planning of a Heterogeneous Platoon in Urban Environments⋆

城市环境下异构车队的生态驾驶轨迹规划–

DOI：
10.1016/j.ifacol.2022.10.278
发表时间：
2022-01
期刊：
IFAC-PapersOnLine
影响因子：
0
作者：
Zhen, Hao;Mosharafian, Sahand;Yang, Jidong J.;Velni, Javad Mohammadpour
通讯作者：
Velni, Javad Mohammadpour

Leveraging autonomous vehicles in mixed-autonomy traffic networks with reinforcement learning-controlled intersections

在具有强化学习控制交叉口的混合自主交通网络中利用自动驾驶汽车

DOI：
10.1080/19427867.2022.2146302
发表时间：
2022-11-28
期刊：
Transportation Letters
影响因子：
0
作者：
Sah;Mosharafian;Shirin Afzali;Javad Mohammadpour Velni
通讯作者：
Javad Mohammadpour Velni

Finite State Markov Modeling of C-V2X Erasure Links For Performance and Stability Analysis of Platooning Applications

用于队列应用性能和稳定性分析的 C-V2X 擦除链路有限状态马尔可夫建模

DOI：
10.1109/syscon53536.2022.9773892
发表时间：
2021-11-13
期刊：
2022 IEEE International Systems Conference (SysCon)
影响因子：
0
作者：
Mahdi Razzaghpour;Adwait Datar;Daniel Schneider;Mahdi Zaman;H. Werner;Hannes Frey;J. Mohammadpour;Y. P. Fallah
通讯作者：
Y. P. Fallah