4.6 Article

Parallel Driving OS: A Ubiquitous Operating System for Autonomous Driving in CPSS

Journal

IEEE TRANSACTIONS ON INTELLIGENT VEHICLES
Volume 7, Issue 4, Pages 886-895

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIV.2022.3223728

Keywords

Autonomous vehicles; Operating systems; Robots; Behavioral sciences; Complex systems; Training; Vehicle safety; Ubiquitous computing; Autonomous driving; intelligent vehicle; parallel driving operating system; ubiquitous operating system

Funding

  1. National Key Research and Development Program of China [2022YFB4703700]
  2. Key-Area Research and Development Program of Guangdong Province [2020B0909050001, 2020B090921003]
  3. Natural Science Foundation of Hebei Province [2021402011]
  4. National Natural Science Foundation of China [62273135]
  5. Natural Science Foundation of Hubei Province in China [2021CFB460]

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With the rapid development of autonomous driving technologies, a ubiquitous operating system named Parallel Driving Operating System (PDOS) is proposed to solve the incompatibility issue among different autonomous driving algorithms and platforms. The PDOS architecture includes multiple layers and can support heterogeneous hardware, resource management, algorithm optimization, and application development. Evaluation results demonstrate the high performance of PDOS in multiple autonomous driving scenarios.
With the rapid development of autonomous driving technologies, a vast array of autonomous driving algorithms and platforms have emerged. These algorithms and platforms are usually designed for different tasks in specific scenarios, which makes them incompatible with each other. To solve the problem, we propose a ubiquitous operating system named Parallel Driving Operating System (PDOS) based on the parallel driving theory. Specifically, the PDOS architecture includes the hardware layer, the kernel layer, the functional layer, and the application layer, which can realize heterogeneous hardware support, ubiquitous resource management, algorithm optimization, and ubiquitous application development, respectively. Moreover, we derive the PDOS into specific operating systems in four application scenarios, i.e., intelligent mining, intelligent warehousing, intelligent logistics, and intelligent port. To validate the PDOS, we test its usability, reliability, and efficiency in these scenarios. Evaluation results demonstrate the high performance of PDOS in multiple autonomous driving, and indicate that PDOS is an efficient operating system for parallel driving.

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