We demonstrate a working functional prototype of a cooperative perception system that maintains a real-time digital twin of the traffic environment, providing a more accurate and more reliable model than any of the participant subsystems—in this case, smart vehicles and infrastructure stations—would manage individually. The importance of such technology is that it can facilitate a spectrum of new derivative services, including cloud-assisted and cloud-controlled ADAS functions, dynamic map generation with analytics for traffic control and road infrastructure monitoring, a digital framework for operating vehicle testing grounds, logistics facilities, etc. In this paper, we constrain our discussion on the viability of the core concept and implement a system that provides a single service: the live visualization of our digital twin in a 3D simulation, which instantly and reliably matches the state of the real-world environment and showcases the advantages of real-time fusion of sensory data from various traffic participants. We envision this prototype system as part of a larger network of local information processing and integration nodes, i.e., the logically centralized digital twin is maintained in a physically distributed edge cloud.

Nowadays, cybersecurity is an emerging research area in the automotive industry, and it is investigated by many different perspectives. Our article is a review of existing vehicular security solutions that covers the state-of-the-art and future research directions. This article is a new contribution to tutorials/surveys related to the vehicular cybersecurity domain with the latest details. We developed a database from 140 articles from the field of automotive security. In the database, we assigned specific attributes to every article (such as Web of Science Impact Factor or the number of citations). The data set was analyzed by the K-means clustering and decision tree analysis methods to identify and characterize the generated groups of papers. Following this, the article highlights the research areas that might receive more attention in the future.

Since modern vehicles are connected and their transport processes are strongly supported by different automated functions, malicious external interventions can impair safety integrity. Therefore, it seems to be reasonable in the future to introduce safety and security co-engineering approaches in the automotive industry. With regard to the performed evaluation, three main promising research orientations have been identified. Automotive safety and security related development of co-engineering methodology and validation framework are of key importance from the viewpoint of autonomous transportation. Accordingly, a scenario based, integrated evaluation of automotive safety and security would be closely fit to the concept of SOTIF and the SoS approach. Beyond this, the communication and network security of "vehicle to everything" channels have to also be in the focus of automotive researches. Additionally, the development of automotive anomaly detection systems, especially focusing on the complex SoS operation processes will be a highly important research orientation.

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This article investigates cybersecurity issues related to in-vehicle communication networks. In-vehicle communication network security is evaluated based on the protection characteristics of the network components and the topology of the network. The automotive communication network topologies are represented as undirected weighted graphs, and their vulnerability is estimated based on the specific characteristics of the generated graph. Thirteen different vehicle models have been investigated to compare the vulnerability levels of the in-vehicle network using the Dijkstra's shortest route algorithm. An important advantage of the proposed method is that it is in accordance with the most relevant security evaluation models. On the other hand, the newly introduced approach considers the Secure-by-Design concept principles.