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.

This work is devoted to the study of communication subsystem of networks-on-chip (NoCs) development with an emphasis on their topologies. The main characteristics of NoC topologies and the routing problem in NoCs with various topologies are considered. It is proposed to use two-dimensional circulant topologies for NoC design, since they have significantly better characteristics than most common mesh and torus topologies, and, in contrast to many other approaches to improving topologies, have a regular structure. The emphasis is on using ring circulants which although in some cases have somewhat worse characteristics than the optimal circulants, compensate by one-length first generatrix in such graphs that greatly facilitate routing in them. The paper considers three different approaches to routing in NoCs with ring circulant topology: Table routing, Clockwise routing, and Adaptive routing. The algorithms of routing are proposed, the results of synthesis of routers, based on them, are presented, and the cost of chip resources for the implementation of such communication subsystems in NoCs is estimated.

Modern computational tasks are often required to not only guarantee predefined accuracy, but get the result fast. Optimizing calculations using floating point numbers, as opposed to integers, is a non-trivial task. For this reason, there is a need to explore new ways to improve such operations. This paper presents analysis and comparison of various floating point formats - float, posit and bfloat. One of the promising areas in which the problem of using such values can be considered to be the most acute is neural networks. That is why we pay special attention to algorithms of linear algebra and artificial intelligence to assess efficiency of new data types in this area. The research results showed that software implementations of posit16 and posit32 have high accuracy, but they are not particularly fast; on the other hand, bfloat16 is not much different from float32 in accuracy, but significantly surpasses it in performance for large amounts of data and complex machine learning algorithms. Thus, posit16 can be used in systems with less stringent performance requirements, as well as in conditions of limited computer memory; and also in cases when bfloat16 cannot provide required accuracy. As for bfloat16, it can speed up systems based on the IEEE 754 standard, but it cannot solve all the problems of conventional floating point arithmetic. Thus, although posits and bfloats are not a full fledged replacement for float, they provide (under certain conditions) advantages that can be useful for implementation of machine learning algorithms.

For a family of optimal two-dimensional circulant networks with an analytical description, two new improved versions of the shortest path search algorithm with a constant complexity estimate are obtained. A simple, based on the geometric model of circulant graphs, proof of the formulas used for the shortest path search algorithm is given. Pair exchange algorithms are presented, and their estimates are given for networks-on-chip (NoCs) with a topology in the form of the considered graphs. New versions of the algorithm improve the previously proposed shortest path search algorithm for optimal generalized Petersen graphs with an analytical description. The new proposed algorithm is a promising solution for the use in NoCs which was confirmed by an experimental study while synthesizing NoC communication subsystems and comparing the consumed hardware resources with those when other previously developed routing algorithms.

This article considers the usage of circulant topologies as a promising deadlock-free topology for networks-on-chip (NoCs). A new high-level model, Newxim, for the exploration of NoCs with any topology is presented. Two methods for solving the problem of cyclic dependencies in circulant topologies, which limit their applications for NoCs due to the increased possibility of deadlocks, are proposed. The first method of dealing with deadlocks is universal and applicable to any topology; it is based on the idea of bypassing blocked sections of the network on an acyclic subnetwork. The second method—Ring-Split—takes into account the features of circulant topologies. The results of high-level modeling and comparison of the peak throughput of NoCs for circulant and mesh topologies using deadlock-free routing algorithms are presented. It was shown that a new approach for routing in circulants (compared to mesh topology) shows up to 59% better network throughput with a uniform distribution of network load.