CPS: Medium: GOALI: Design Automation for Automotive Cyber-Physical Systems

CPS：中：GOALI：汽车网络物理系统设计自动化

• 批准号: 2038960
• 负责人: Samarjit Chakraborty
• 金额: $ 120万
• 依托单位: University of North Carolina at Chapel Hill
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-01-01 至 2024-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2038960&HistoricalAwards=false
• 关键词: CPS; Medium; GOALI; Design; Automation

This project aims to transform the software development process in modern cars, which are witnessing significant innovation with many new autonomous functions being introduced, culminating in a fully autonomous vehicle. Most of these new features are indeed implemented in software, at the heart of which lies several control algorithms. Such control algorithms operate in a feedback loop, involving sensing the state of the plant or the system to be controlled, computing a control input, and actuating the plant in order to enforce a desired behavior on it. Examples of this range from brake and engine control, to cruise control, automated parking, and to fully autonomous driving. Current development flows start with mathematically designing a controller, followed by implementing it in software on the embedded systems existing in a car. This flow has worked well in the past, where automotive embedded systems were simple – with few processors, communication buses, and simple sensors. The control algorithms were simple as well, and important functions were largely implemented by mechanical subsystems. But modern cars have over 100 processors connected by several miles of cables, and multiple sensors like cameras, radars and lidars, whose data needs complex processing before it can be used by a controller. Further, the control algorithms themselves are also more complex since they need to implement new autonomous features that did not exist before. As a result, both computation, communication, and memory accesses in such a complex hardware/software system can now be organized in many different ways, with each being associated with different tradeoffs in accuracy, timing, and resource requirements. These in turn have considerable impact on control performance and how the control strategy needs to be designed. As a result, the clear separation between designing the controller, followed by implementing it in software in the car, no longer works well. This project aims to develop both the theoretical foundations and the tool support to adapt this design flow to emerging automotive control strategies and embedded systems. This will not only result in more cost-effective design of future cars, but will also help with certifying the implemented controllers, thereby leading to safer autonomous cars. In particular, the goal is to automate the synthesis and implementation of control algorithms on distributed embedded architectures consisting of different types of multicore processors, GPUs, FPGA-based accelerators, different communication buses, gateways, and sensors associated with compute-intensive processing. Starting with specifications of plants, control objectives, controller templates, and a partially-specified implementation architecture, this project seeks to synthesize both controller and implementation architecture parameters that meet all control objectives and resource constraints. Towards this, a variety of techniques from switched control, interface compatibility checking, and scheduling of multi-mode systems – that bring together control theory, real-time systems, program analysis, and mathematical optimization, will be used. In collaboration with General Motors, this project will build a tool chain that integrates controller design tools like Matlab/Simulink with standard embedded systems design and configuration tools. This project will demonstrate the benefits of this new design flow and tool support by addressing a set of challenge problems from General Motors.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.

该项目旨在改变现代汽车的软件开发流程，现代汽车正在见证重大创新，引入了许多新的自动驾驶功能，最终形成了完全自动驾驶的汽车，其中大多数新功能确实是在软件中实现的，而软件的核心在于。此类控制算法在反馈回路中运行，感测要控制的设备或系统的状态，计算控制输入，并启动设备以强制其执行所需的行为。制动和发动机控制，巡航控制，自动化当前的开发流程从数学设计控制器开始，然后在汽车中现有的嵌入式系统上的软件中实现该流程，在过去，汽车嵌入式系统很简单——控制算法也很简单，重要的功能主要由机械子系统实现，但现代汽车有超过 100 个处理器，通过数英里的电缆连接，以及多个传感器，例如摄像头、雷达和传感器。激光雷达，其数据需要复杂的处理此外，控制算法本身也更加复杂，因为它们需要实现以前不存在的新的自主功能，因此，在如此复杂的硬件中进行计算、通信和内存访问。 /软件系统现在可以以多种不同的方式进行组织，每种方式都与准确性、时序和资源需求的不同权衡相关，这些反过来又对控制性能以及如何设计控制策略产生相当大的影响。 ，设计控制器和随后实现它之间的明确分离该项目旨在开发理论基础和工具支持，以使该设计流程适应新兴的汽车控制策略和嵌入式系统。未来的汽车，但也将有助于认证所实施的控制器，从而实现更安全的自动驾驶汽车，特别是，目标是在由不同类型的多核处理器、GPU、FPGA 组成的分布式嵌入式架构上自动合成和实现控制算法。基于加速器，与计算密集型处理相关的不同通信总线、网关和传感器从工厂规范、控制目标、控制器模板和部分指定的实施架构开始，该项目旨在综合满足所有控制的控制器和实施架构参数。为此，将使用多种技术，包括切换控制、接口兼容性检查和多模式系统调度，这些技术将控制理论、实时系统、程序分析和数学优化结合在一起。该项目将与通用汽车公司合作，建造一个将 Matlab/Simulink 等控制器设计工具与标准嵌入式系统设计和配置工具集成在一起的工具链。该项目将通过解决通用汽车公司的一系列挑战问题来展示这种新设计流程和工具支持的优势。该奖项反映了 NSF 的法定奖项。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

Perception Computing-Aware Controller Synthesis for Autonomous Systems

• DOI: 10.23919/date51398.2021.9474189
• 发表时间: 2021-02
• 期刊: 2021 Design, Automation & Test in Europe Conference & Exhibition (DATE)
• 作者: Clara Hobbs;Debayan Roy;Parasara Sridhar Duggirala;F. D. Smith;Soheil Samii;James H. Anderson;S. Chakraborty

Safety-Aware Implementation of Control Tasks via Scheduling with Period Boosting and Compressing

通过周期提升和压缩调度实现控制任务的安全感知

• DOI: 10.1109/rtcsa58653.2023.00031
• 发表时间: 2023
• 期刊: IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA
• 作者: Xu, Shengjie;Ghosh, Bineet;Hobbs, Clara;Thiagarajan, P. S.;Joshi, Prachi;Chakraborty, Samarjit
• 通讯作者: Chakraborty, Samarjit

Offline and Online Monitoring of Scattered Uncertain Logs Using Uncertain Linear Dynamical Systems

使用不确定线性动力系统对分散的不确定日志进行离线和在线监测

• 发表时间: 2022
• 期刊: and Systems (FORTE
• 作者: Bineet Ghosh;Étienne André
• 通讯作者: Étienne André

Exploiting Process Dynamics in Multi-Stage Schedule Optimization for Flexible Manufacturing

利用流程动力学实现柔性制造的多阶段进度优化

• DOI: 10.1109/etfa52439.2022.9921465
• 发表时间: 2022
• 期刊: 7th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA
• 作者: Balszun, Michael;Hobbs, Clara;Fraccaroli, Enrico;Roy, Debayan;Chakraborty, Samarjit
• 通讯作者: Chakraborty, Samarjit

SMT-based Control Safety Property Checking in Cyber-Physical Systems under Timing Uncertainties

时序不确定性下信息物理系统中基于 SMT 的控制安全属性检查

• 发表时间: 2024
• 期刊: 37th International Conference on VLSI Design
• 作者: Yeolekar, Anand;Metta, Ravindra;Chakraborty, Samarjit
• 通讯作者: Chakraborty, Samarjit