Towards a Digital Twin Framework for Connected Vehicles

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Abstract

In the last decade, vehicles have become more and more sophisticated in terms of automated driving assistance systems, safety systems, such as sleep detection, or infotainment. These systems are enabled through a growing amount of sensors and actuators built into modern vehicles, including cameras, GPS, distance sensors, or collision detection sensors, each controlled by a growing number of ECUs. Using the data generated by these vehicles, new applications can be developed, the most promising being autonomous driving. However, besides the sensing capabilities, e.g., to detect other vehicles or pedestrians, it is also necessary to provide a high interconnection of multiple vehicles in traffic. By doing so, vehicles can notify other vehicles of hazardous driving conditions, accidents, or traffic jams, leading to an Internet of Vehicles. Yet, ensuring a reliable and uniform communication and coordination of multiple heterogeneous vehicles from different manufacturers is a challenging task. In this paper, we introduce a first approach for a digital twin framework intended for connected vehicles. It enhances connected vehicles with an administration shell, making it possible for them to be recognized by other vehicles and to communicate with them.

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Gerhards, J., Schneider, T., & Hirmer, P. (2022). Towards a Digital Twin Framework for Connected Vehicles. In International Conference on Internet of Things, Big Data and Security, IoTBDS - Proceedings (Vol. 2022-April, pp. 189–196). Science and Technology Publications, Lda. https://doi.org/10.5220/0011066600003194

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