Automated and connected vehicles are emerging in the market. Currently, solutions are being proposed to use these technologies for cooperative driving, which can significantly improve road safety. Vehicular safety applications must be tested before deployment. It is challenging to verify and validate them in the real world. Therefore, simulation is used for this purpose. Modeling this technology necessitates coupled use of traffic flow, vehicle dynamics, and communication network simulators. State-of-the-art tools exist in these domains; however, they are difficult to integrate or lack full domain coverage. This article analyzes the requirements for an integrated connected and automated vehicle simulation environment for simulating vehicular cooperative driving automation with consideration of surrounding objects’ influence. For this purpose, we have assessed the existing challenges and practices. Vehicular simulation tools, signal propagation, and cooperative perception models are reviewed and analyzed. In our review, we focus mainly on autonomous driving simulators with 3D graphical environments as they have not yet been assessed for cooperative driving task fitness. Further, the current state of connected and automated vehicle simulation studies using these tools is surveyed, including single-tool and co-simulation approaches. We discuss the shortcomings of existing methods and propose an architecture for an integrated simulation environment (ISE) with full domain coverage using open source tools. The obtained conclusions can be further used in the development of connected and automated vehicle ISEs.

Automated and connected vehicles are emerging in the market. Currently, solutions are being proposed to use these technologies for cooperative driving, which can significantly improve road safety. Vehicular safety applications must be tested before deployment. It is challenging to verify and validate them in the real world. Therefore, simulation is used for this purpose. Modeling these technologies necessitates coupled the use of traffic flow, vehicle dynamics, communication network, perception and signal propagation models. State-of-the-art tools exist in these domains; however, they lack full domain coverage, and the low-level processes that affect each vehicle’s behavior are often left unaccounted for, which (according to complex system theory) can lead to erroneous assumptions about system-level outcomes. This paper analyzes the requirements for an integrated connected and automated vehicle simulation environment for simulating vehicle behavior with consideration of surrounding objects’ influence on machine perception and signal propagation. We discuss the shortcomings of existing methods, propose an architecture for a simulation environment with full domain coverage, and develop a preliminary version of the CAVISE integrated simulation environment for connected and automated vehicles using open-source tools. Scenarios of object detection and signal exchange were simulated, and data on the influence of surrounding objects on quantitative and qualitative changes in scenario simulation results was obtained. It was found that a more accurate description of surrounding objects and their influence on machine perception and signal transmission does lead to quantitative and qualitative changes in the measured parameters. This conclusion should be further used in simulation environment development for connected and automated vehicle technology verification and validation.

Population growth has led to an increased demand for transportation. This increase has subsequently resulted in problems such as road accidents, greenhouse gas emissions, and others. Automated and connected vehicles could be a solution to these problems. However, before they can be released on public roads, they must go through extensive testing, including computer simulation. State-of-the-art open-source connected and automated vehicle simulation environments do not provide signal propagation modeling in 3D environments with elevation differences for vehicular communications. While open-source 3D signal propagation models are available. To avoid redeveloping complex existing technology, it is desirable to integrate such models into state-of-the-art simulation environments. This paper proposes integrating a 3D signal propagation model OPAL into the CAVISE simulation environment as an alternative to the available GEMV2 2D signal propagation model. A comparison of GEMV2 and OPAL models is provided, and an extended CAVISE architecture that can interchange between the two models is synthesized and described. Approaches to further integrate OPAL into the architecture by porting it to Unreal Engine are explored. Various scenarios of information exchange between vehicles using the GEMV2 and OPAL models are simulated. The results are compared, and the models are validated against each other. Current limitations of OPAL capabilities regarding 3D scenario generation are discussed, and possible approaches to improvement are suggested. The findings will be used to develop signal propagation simulation in scenarios with elevation differences and 3D structures in CAVISE.

Nowadays, the problems of traffic accidents, inefficiency, and congestion still affect transportation systems. Conventional solutions often do not resolve and can even exacerbate the problems. Intelligent transportation system (ITS) technology, including intelligent vehicles, could provide a solution for these problems. However, such technologies should be thoroughly verified and validated before their large-scale adoption. Computer simulation can be used for this task to avoid the expenses of real-world testing. Modern consumer hardware computers are not powerful enough to handle large-scale scenes with high detail. Therefore, a parallel simulation approach employing multiple computers, each processing a separate scene of limited size, is proposed. To define the requirements for a suitable simulation tool, the needs of ITS simulation and Digital Twin technology are discussed, and existing simulation environments suitable for ITS technology verification and validation are evaluated. Further, an architecture for a parallel and multi-level simulation environment for large-scale detailed ITS modeling is proposed. The proposed integrated simulation environment uses the nanoscopic CARLA and microscopic SUMO simulators to implement multi-level and parallel nanoscopic simulation by creating a large scene on the microscopic simulation level and combining the information from multiple parallelly executed nanoscopic scenes. Special handling for nanoscopic scene logic is proposed using a concept of Buffer Zones that allows traffic participants to perceive environmental information beyond the logical boundary of the scene they belong to. The proposed approaches are demonstrated in a series of experiments as a proof of concept and are integrated into the CAVISE simulation environment.

Reliable Vehicle-to-Everything (V2X) evaluation requires propagation models that represent terrain and multilevel infrastructure. Most integrated vehicular simulators still rely on planar models, but the magnitude of the resulting bias is unclear. This study quantitatively compares flattened two-dimensional (2D) and terrain-aware three-dimensional (3D) variants of three scenarios using identical Sionna RT settings. The pipeline combines OpenStreetMap and digital elevation data, Blender/Blosm scene construction, and SUMO mobility traces. The scenarios represent a 4 km mountain pass, an overpass bridge, and an underground tunnel. Path gain is computed at 5.9 GHz; received signal strength and link outage are then derived using a 23 dBm transmit power and a −94 dBm receiver sensitivity. The outage rate increases from 21% to 30% for the mountain pass, from 20% to 33% for the bridge, and from 0% to 80% for the tunnel with 3D geometry. Mean signal-loss discrepancies reach approximately 9 dB for the mountain pass and 10 dB for the bridge. GPU acceleration reduces per-frame processing time by approximately one order of magnitude in a controlled bridge benchmark. The results show that 3D-aware propagation modeling is necessary for credible assessment of V2X applications in environments with elevation changes.