Influence Assessment of Intelligent Unmanned Ground Vehicles on the Transport Network State

Abstract

This article is devoted to econometric analysis of the results of experiments conducted with two agent-based models, which describe the movement of ground vehicles. There are two types of road users in these models: manned ground vehicles (MGV) and unmanned ground vehicles (UGV). In the first model, the main difference between UGV and MGV is an ability to exchange massages between UGV for transmitting information about extreme situations, which allows them to adjust speed and direction of movement. In the second model, in addition to the above differences, UGV have an additional advantage, namely, the ability to intelligently assess density of traffic flow for efficient maneuvering. In these models, at a given roundabout, traffic characteristics such as output stream traffic and the number of traffic accidents are analyzed. The main task of the econometric analysis is to study dependence of these traffic characteristics on the model parameters such as average vehicle speed, input flow rate, message exchange rate between UGV, and the impact of the effect obtained from the implementation into UGV ability of intelligent estimation of traffic flow density.