Parallel Point Clouds: Hybrid Point Cloud Generation and 3D Model Enhancement via Virtual–Real Integration

Tian, Yonglin; Wang, Xiao; Shen, Yu; Guo, Zhongzheng; Wang, Zilei; Wang, Fei‐Yue

doi:10.3390/rs13152868

Cited by 15 publications

(7 citation statements)

References 35 publications

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“…It was used to search for challenging scenarios for improving the perception capability of autonomous vehicles. A similar concept was utilized in [299], which presented a virtual-real interactive point cloud generation framework for autonomous driving, called parallel point clouds (PPCs). To accelerate the evaluation and development of autonomous vehicles, [33] designed a human-in-theloop parallel testing system to implement more challenging tests via virtual-real interaction.…”

Section: Ddt In Automated Vehicle Developmentmentioning

confidence: 99%

Review and Perspectives on Driver Digital Twin and Its Enabling Technologies for Intelligent Vehicles

Lou

Xing

et al. 2022

IEEE Trans. Intell. Veh.

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Digital Twin (DT) is an emerging technology and has been introduced into intelligent driving and transportation systems to digitize and synergize connected automated vehicles. However, existing studies focus on the design of the automated vehicle, whereas the digitization of the human driver, who plays an important role in driving, is largely ignored. Furthermore, previous driver-related tasks are limited to specific scenarios and have limited applicability. Thus, a novel concept of a driver digital twin (DDT) is proposed in this study to bridge the gap between existing automated driving systems and fully digitized ones and aid in the development of a complete driving human cyber-physical system (H-CPS). This concept is essential for constructing a harmonious human-centric intelligent driving system that considers the proactivity and sensitivity of the human driver. The primary characteristics of the DDT include multimodal state fusion, personalized modeling, and time variance. Compared with the original DT, the proposed DDT emphasizes on internal personality and capability with respect to the external physiological-level state. This study systematically illustrates the DDT and outlines its key enabling aspects. The related technologies are comprehensively reviewed and discussed with a view to improving them by leveraging the DDT. In addition, the potential applications and unsettled challenges are considered. This study aims to provide fundamental theoretical support to researchers in determining the future scope of the DDT system.

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Section: Ddt In Automated Vehicle Developmentmentioning

confidence: 99%

Review and Perspectives on Driver Digital Twin and Its Enabling Technologies for Intelligent Vehicles

Lou

Xing

et al. 2022

IEEE Trans. Intell. Veh.

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“…On the other hand, point cloud annotation presents another challenge since a single point has no meaning. Tian [37] proposed the Parallel Point Clouds framework trying to find a solution to these issues. A 360-degree scanning virtual LiDAR was first designed as the virtual sensor in parallel point clouds.…”

Section: B Parallel Point Cloudsmentioning

confidence: 99%

Parallel Sensing in Metaverses: Virtual-Real Interactive Smart Systems for “6S” Sensing

Shen¹,

Liu²,

Tian

et al. 2022

IEEE/CAA J. Autom. Sinica

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In the construction of Metaverses, sensors that are referred to as the "bridge of information transmission", play a key role. The functionality and efficiency of today's sensors, which operate in a manner similar to physical sensing, are frequently constrained by their hardware and software. In this research, we proposed the Parallel Sensing framework, which includes background, concept, basic methods and typical application of parallel sensing. In our formulation, sensors are redefined as the integration of real physical sensors and virtual software-defined sensors based on parallel intelligence, in order to boost the performance of the sensors. Each sensor will have a parallel counterpart in the virtual world within the framework of parallel sensing. Digital sensors serve as the brain of sensors and maintain the same properties as physical sensors. Parallel sensing allows physical sensors to operate in discrete time periods to conserve energy, while cloud-based descriptive, predictive, and prescriptive sensors operate continuously to offer compensation data and serve as guardians. To better illustrate parallel sensing concept, we show some example applications of parallel sensing such as parallel vision, parallel point cloud and parallel light fields, both of which are designed by construct virtual sensors to extend small real data to virtual big data and then boost the performance of perception models. Experimental results demonstrate the effective of parallel sensing framework. The interaction between the real and virtual worlds enables sensors to operate actively, allowing them to intelligently adapt to various scenarios and ultimately attain the goal of "Cognitive, Parallel, Crypto, Federated, Social and Ecologic" 6S sensing.

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“…First, as shown in Figure 8, we build artificial radar systems including sensor models and scenarios of mining areas based on Unreal Engine 4 to generate virtual data in cyber space [100]. In our artificial systems, virtual radars are consistent with real radars in appearance and internal physical parameters.…”

Section: Autonomous Drivingmentioning

confidence: 99%

Parallel Radars: From Digital Twins to Digital Intelligence for Smart Radar Systems

Liu

Shen

Fan

et al. 2022

Sensors

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Radar is widely employed in many applications, especially in autonomous driving. At present, radars are only designed as simple data collectors, and they are unable to meet new requirements for real-time and intelligent information processing as environmental complexity increases. It is inevitable that smart radar systems will need to be developed to deal with these challenges and digital twins in cyber-physical systems (CPS) have proven to be effective tools in many aspects. However, human involvement is closely related to radar technology and plays an important role in the operation and management of radars; thus, digital twins’ radars in CPS are insufficient to realize smart radar systems due to the inadequate consideration of human factors. ACP-based parallel intelligence in cyber-physical-social systems (CPSS) is used to construct a novel framework for smart radars, called Parallel Radars. A Parallel Radar consists of three main parts: a Descriptive Radar for constructing artificial radar systems in cyberspace, a Predictive Radar for conducting computational experiments with artificial systems, and a Prescriptive Radar for providing prescriptive control to both physical and artificial radars to complete parallel execution. To connect silos of data and protect data privacy, federated radars are proposed. Additionally, taking mines as an example, the application of Parallel Radars in autonomous driving is discussed in detail, and various experiments have been conducted to demonstrate the effectiveness of Parallel Radars.

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Parallel Point Clouds: Hybrid Point Cloud Generation and 3D Model Enhancement via Virtual–Real Integration

Cited by 15 publications

References 35 publications

Review and Perspectives on Driver Digital Twin and Its Enabling Technologies for Intelligent Vehicles

Review and Perspectives on Driver Digital Twin and Its Enabling Technologies for Intelligent Vehicles

Parallel Sensing in Metaverses: Virtual-Real Interactive Smart Systems for “6S” Sensing

Parallel Radars: From Digital Twins to Digital Intelligence for Smart Radar Systems

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