A Digital Twin Paradigm: Vehicle-to-Cloud Based Advanced Driver Assistance Systems

Wang, Ziran; Liao, Xishun; Zhao, Xuanpeng; Han, Kyungtae; Tiwari, Prashant; Barth, Matthew; Wu, Guoyuan

doi:10.1109/vtc2020-spring48590.2020.9128938

Cited by 107 publications

(43 citation statements)

References 12 publications

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“…Furthermore, in the current scientific literature, DTs do not dynamically modify the environment, so virtualisations of specific processes (e.g., autonomous navigation) have not been investigated. For this reason, the development of this framework permits more accurate results to be obtained by virtualising the scenarios [ 55 ]. Furthermore, the techniques employed in this paper do not require previous real data since the modelling of the environment and the AGVs is complete.…”

Section: Digital Twin From Industry 40 Conceptionmentioning

confidence: 99%

Digital Twin for Automatic Transportation in Industry 4.0

Martínez-Gutiérrez

Díez-González

Ferrero-Guillén

et al. 2021

Sensors

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Industry 4.0 is the fourth industrial revolution consisting of the digitalization of processes facilitating an incremental value chain. Smart Manufacturing (SM) is one of the branches of the Industry 4.0 regarding logistics, visual inspection of pieces, optimal organization of processes, machine sensorization, real-time data adquisition and treatment and virtualization of industrial activities. Among these tecniques, Digital Twin (DT) is attracting the research interest of the scientific community in the last few years due to the cost reduction through the simulation of the dynamic behaviour of the industrial plant predicting potential problems in the SM paradigm. In this paper, we propose a new DT design concept based on external service for the transportation of the Automatic Guided Vehicles (AGVs) which are being recently introduced for the Material Requirement Planning satisfaction in the collaborative industrial plant. We have performed real experimentation in two different scenarios through the definition of an Industrial Ethernet platform for the real validation of the DT results obtained. Results show the correlation between the virtual and real experiments carried out in the two scenarios defined in this paper with an accuracy of 97.95% and 98.82% in the total time of the missions analysed in the DT. Therefore, these results validate the model created for the AGV navigation, thus fulfilling the objectives of this paper.

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Section: Digital Twin From Industry 40 Conceptionmentioning

confidence: 99%

Digital Twin for Automatic Transportation in Industry 4.0

Martínez-Gutiérrez

Díez-González

Ferrero-Guillén

et al. 2021

Sensors

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show abstract

“…While the first is mainly a business-related topic and as such not in the scope of this paper, the last two are in fact technological challenges. The research field of autonomous driving has led to numerous approaches and use cases where access to cloud platforms plays a central role in the customer's car [4], [5]. Moreover, it has been advised that big data and thus cloud-based computing can also be applied as early as during the development and test phases of automotive software [6].…”

Section: Related Workmentioning

confidence: 99%

Towards Cloud-supported Automotive Software Development and Test

Bergelt¹,

Englisch²

2020

ESS

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The development of automotive software has been an evolving process for the last decades. As a result, the paradigm of software development which is independent of the target hardware platform has been adopted in almost all parts of the automotive industry. Deploying software to a hardware platform is now controlled by an enormous parameter set stored in a mapping configuration. This led to the creation of numerous vendor-specific tools for electronic control unit (ECU) development. While this approach simplifies and supports the re-usability of vehicle functions it also increases the complexity as well as the difficulty for integration tests and error localization. In this paper, we present a conceptual platform which allows to establish references between different development and test phase items in a developer-friendly way. It revolves around two self-developed tools supported by an extensive AUTOSAR knowledge base. The system creates inter-connectivity so that it becomes easier to locate the actual origin of a misbehavior or to find a test error manifestation in the actual end system for developers and testers alike.

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“…Therefore, in this study, a Digital Twin simulation architecture is built based on the Unity game engine [12]. A Digital Twin is defined as a digital replica of a real entity in the physical world [13]. Given the characteristics of the Digital Twin and the powerful features of Unity, users are able to build comprehensive CAV models with all necessary modules, as well as realistic road environments with high-fidelity assets.…”

Section: Introductionmentioning

confidence: 99%

Digital Twin Simulation of Connected and Automated Vehicles with the Unity Game Engine

Wang¹

2021

Preprint

Self Cite

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A Digital Twin is defined as a digital replica of a real entity in the physical world. In this study, the Digital Twin simulation is developed for connected and automated vehicles (CAVs) by leveraging the Unity game engine. A Digital Twin simulation architecture is proposed, which contains the physical world and the digital world. Particularly, the digital world consists of three layers, where the Unity game objects are built to simulate the "hardware", the Unity scripting API are used to simulate the "software", and external tools (e.g., SUMO, MATLAB, python, and/or AWS) are leveraged to enhance the simulation functionalities. A case study of personazlied adaptive cruise control (P-ACC) is conducted to showcase the effectiveness of the proposed Digital Twin simulation, where the ACC system can be designed to satisfy each driver's preference with the help of cloud computing.

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A Digital Twin Paradigm: Vehicle-to-Cloud Based Advanced Driver Assistance Systems

Cited by 107 publications

References 12 publications

Digital Twin for Automatic Transportation in Industry 4.0

Digital Twin for Automatic Transportation in Industry 4.0

Towards Cloud-supported Automotive Software Development and Test

Digital Twin Simulation of Connected and Automated Vehicles with the Unity Game Engine

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