Reduction of Uncertainties for Safety Assessment of Automated Driving Under Parallel Simulations

In the future, management in smart societies will revolve around knowledge workers and the works they produce. This article is committed to explore new management framework, model, paradigm, and solution for organizing, managing, and measuring knowledge works. First, the parallel management framework is presented that would allow for the virtual-real interactions of humans in social space, robots in physical space, and digital humans in cyberspace to realize descriptive, predictive, and prescriptive intelligence for management. Then, the management foundation models are proposed by fusing scenarios engineering with artificial intelligence foundation models and cyber-physical-social systems. Moreover, the new management paradigm driven by decentralized autonomous organizations and operations is formulated for the advancement of smart organizations and intelligent operations. On these basis, the management operating systems that highlight features of simple intelligence, provable security, flexible scalability, and ecological harmony are finally put forward as new management solution.Index Terms-Decentralized autonomous organizations and operations (DAO), management foundation model, management intelligence, management operating system (MOS), metaverse, parallel management. I. INTRODUCTIONM ANAGEMENT is regarded as the art and science of how to effectively use resources to achieve the predefined goals. Management as a field originated from ancient China [1], [2], [3], [4] and dated from the monograph entitled "Guanzi" [5], [6], [7], which contains the dialectical idea of the opposition and unity between simplicity and complexity as well as many unique management concepts and thoughts. Especially, its decision-making concept is very Manuscript

show abstract

“…and external environments (e.g., competitors, market, etc.) at the end of management process [39], [40].…”

Section: A Scenarios: From Features Engineering To Scenarios Engineeringmentioning

confidence: 99%

The Future of Management: DAO to Smart Organizations and Intelligent Operations

Qin

Wang

2023

IEEE Trans. Syst. Man Cybern, Syst.

View full text Add to dashboard Cite

show abstract

“…Due to human factors in CPSS, it is impossible to identify the system's optimal strategy using only the collected data. In order to achieve convergent solutions, predictive radars forecast data from future scenarios first and then evaluate different situations [54], [55].…”

Section: Predictive Radarsmentioning

confidence: 99%

RadarVerses in Metaverses: A CPSI-Based Architecture for 6S Radar Systems in CPSS

Liu

Shen

Tian

et al. 2023

IEEE Trans. Syst. Man Cybern, Syst.

View full text Add to dashboard Cite

Metaverses have caused significant changes in the industry and their academic foundation can be traced back to the term cyber-physical-social systems (CPSS), which was proposed in 2010. Radar is an important sensor in sensing systems that are widely applied in many fields, especially, in autonomous driving. To deal with the complex environment, smart radars with realtime information processing capabilities are required. Human factors play a critical role in the operation and management of radar systems, thus, digital twins' radars in cyber-physical systems (CPS) are unable to achieve intelligence in CPSS due to an incomplete consideration of human involvement. For this consideration, we propose a novel framework of RadarVerses for smart radars in metaverses based on ACP-based parallel intelligence, which is also known as cyber-physical-social intelligence (CPSI). RadarVerses consist of five main parts which are physical radars, descriptive radars, predictive radars, prescriptive radars, and deep radars. To construct RadarVerses at the technical level, we introduce four main technical foundations: 1) communication technology; 2) scenarios engineering; 3) foundation models; and 4) digital workers. In addition, we also provide a case study about LiDARs' predictive maintenance of accumulated snow in RadarVerses.

show abstract

“…For AVs, high-level intelligence is indicated by a high-degree consistency between the system driving and human driving process. Studies on the similarity between human and AV driving have chosen specific parameters, such as the type of operation taken by the ADS and human [28], and the TTC with the front vehicle when the operation is taken [22]. However, these parameters are difficult to generalize in different scenarios and can only describe the similarity at a specific state rather than over the whole driving process.…”

Section: Anthropomorphic Indexmentioning

confidence: 99%

Performance Evaluation Method for Automated Driving System in Logical Scenario

Zhang

Zhu²,

Zhao³

et al. 2022

Automot. Innov.

View full text Add to dashboard Cite

With the continuous improvement of automated driving technology, how to evaluate the performance of an automated driving system is attracting more and more attention. Meanwhile, with the creation of scenario-based test methods, the traditional evaluation index based on a single test can no longer meet the requirements of high-level safety verification for automated driving system, and the performance evaluation of such a system in logical scenarios will be the mainstream. Based on the scenario-based test method and Turing test theory, a performance evaluation method for an automated driving system in the whole parameter space of a logical scenario is proposed. The logical scenario parameter space is partitioned according to the risk degree of concrete scenario, and the evaluation process in different zones are determined. Subsequently, the anthropomorphic index in the safe zone and the collision-avoidance index in the danger zone are defined by comparing test results of human driving and ideal vehicle motion. Taking front vehicle low-speed and cut-out scenarios as examples, two automated driving algorithms are tested in the virtual environment, and the test results are evaluated both by the proposed method and by human observation. The results show that the results of the proposed method are consistent with the subjective feelings of humans; additionally, it can be applied to scenario-based tests and the verification process of an automated driving system.

show abstract

Reduction of Uncertainties for Safety Assessment of Automated Driving Under Parallel Simulations

Cited by 13 publications

References 19 publications

The Future of Management: DAO to Smart Organizations and Intelligent Operations

The Future of Management: DAO to Smart Organizations and Intelligent Operations

RadarVerses in Metaverses: A CPSI-Based Architecture for 6S Radar Systems in CPSS

Performance Evaluation Method for Automated Driving System in Logical Scenario

Contact Info

Product

Resources

About