известных тестовых функций (в частности, Бина и Корна, Ффонески и Флеминга и др.) и продемонстрирована лучшая эффективность предложенного метода в сравнении с другими известными ГА (например, SPEA, SPEA2, NSGA-II) по критериям оценки качества фронта Парето, в частности, логарифмического гиперобъема (LHV), инвертированного расстояния между поколениями (IGD) и др.

The article presents an approach to improving maneuverability of unmanned ground vehicles (UGVs) interacting with manned ground vehicles (MGVs) within the proposed multi-agent intelligent transport system (MITS) at various configurations of the digital road network. With the developed models, the abilities of improving maneuverability of agent-vehicles in MITS under various control scenarios for the most important characteristics of the system, such as, the arrival intensities of agents, speeds of UGVs and MGVs, clustering methods for the traffic density estimation and intelligent maneuvering are studied. The proposed MITS is implemented based on the reconfigurable digital road network (DRN). There is proposed an approach to improving the maneuverability of the UGVs, aimed to effectively maneuvering in changing lanes and choosing the best routes to bypass traffic congestions and other problem areas with providing the required level of output traffic and minimizing the number of potential traffic accidents in the MITS. The possibilities of improving maneuverability of UGVs at various configurations of the DRN (for example, the roundabouts, "Manhattan Lattice", etc.) are studied.