Testing self-driving vehicles is still a new and immature process; the globally harmonised procedure expected much later. The resource-demanding nature of real-world tests makes it indispensable to develop and improve the efficiency of virtual environment based testing methods. Accordingly, a novel X-in-the-Loop framework is proposed to fully exploit the recent advances in info-communication technologies, vehicle automation, and testing and validation requirements. This methodology real-time connects physical and virtual testing with high correlation while completely blurs the sharp boundaries between them. Measurement results confirm the superior performance of the 5G communication link in providing a stable, real-time connection between the real world and its virtual representation. The live demonstration proved the presented concept at the newly constructed Hungarian proving ground for automated driving. The performed investigation also includes comprehensive benchmarking, focusing on the most up-to-date automotive testing frameworks. The analysis considers the methodologies and techniques applied by the most relevant actors in the automotive testing sector worldwide. Accordingly, the newly developed testing framework is evaluated and validated in light of the state-of-the-art methods used by the automotive industry.

Impacts of Autonomous Cars from a Traffic Engineering Perspective

The Research Center for Autonomous Road Vehicles (RECAR) was founded in 2015 upon the initiative of the Faculty of Transportation Engineering and Vehicle Engineering of Budapest University of Technology and Economics. The research center is supported by industrial partners and other academic partners targeting research and educational purposes. In complement to this project, the construction of a new automotive test track is also under development especially for autonomous road vehicle testing serving as automotive proving ground in Zalaegerszeg, Hungary. Accordingly, an intensive research has been started in RECAR center in the field of autonomous vehicle technology. The paper’s goal is to share the main practical and methodological experiences with the scientific audience as well as the industrial sector. Based on the initial research actions we intend to enlighten the upcoming research challenges of driverless vehicles and automated intelligent transport system. Basically, three main topics are concerned. Firstly, the main issues concerning autonomous vehicle research are summarized. Secondly, the requirements for autonomous test track design are concluded. Thirdly, the legal questions that emerge with the appearance of driverless vehicles are investigated, especially concerning liability.

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.

Autonomous vehicles are at the forefront of interest due to the expectations of changing transportation for the better. In order to make better decisions on the road, vehicles use information from various sources: their own sensors, messages arriving from surrounding vehicles and objects, as well as from centralized entities—including their own Digital Twin. Certain decisions require the information to arrive with low latency and some of this information (such as video) requires broadband communication. Furthermore, the vehicles can populate an area, so they can represent mass communication endpoints that still need low latency and massive broadband. The mobility of the vehicles obviously requires the complete coverage of the roads with reliable wireless communication technologies fulfilling the previously mentioned needs. The fifth generation of cellular mobile technologies, 5G, addresses these requirements. The current paper presents real-life scenarios—on the M86 highway and the ZalaZONE proving ground in Hungary—for the demonstration of vehicular communication with 5G support, where the cars exchange sensor and control information with each other, their environment, and their Digital Twins. The demonstrations were carried out through the Scenario-in-the-Loop (SciL) methodology, where some of the actionable triggers were not physically present around the vehicles, but sensed or simulated around their Digital Twin. The measurements around the demonstrations aim to reveal the feasibility of the 5G Non-Standalone Architecture for certain communication scenarios, and they mainly aim to reveal the current latency and throughput limitations under real-life conditions.

While mobile network operators have started announcing their 5G-capable network implementations, practical details of their capabilities are not widely supported through measurements. This paper describes a practically implemented 5G architecture - based on the 5G Option 3x reference model - and initial results on its KPI (Key Performance Indicator) measurements.Beside being matched against the 5G network expectations, the results are compared to our actual hands-on 4G network measurements. The analysis of the 5G testbed result shows that - as expected - 5G outperforms 4G in all basic KPIs, including up- and downlink throughput as well as latency. Furthermore, the practical measurement results on this non-standalone 5G architecture show that - when traffic preferences are configured well - latency and jitter are not significantly affected by the load of the cell or the core network. This is a long-awaited proof on 5G KPI promises coming true.