Dynamic Stabilization of Unmanned Vehicle Convoy in Road Climatic Environment of the Russian Federation
Sergei Evgenevich Buznikov1, Andrei Mikhailovich Saikin2, Dmitrii Sergeevich Elkin3, Vladislav Olegovich Strukov4
1Sergei Evgenevich Buznikov*, Federal State Unitary Enterprise Central Scientific Research Automobile and Automotive Institute “NAMI” (FSUE «NAMI»), Moscow, Russia.
2Andrei Mikhailovich Saikin, Federal State Unitary Enterprise Central Scientific Research Automobile and Automotive Institute “NAMI” (FSUE «NAMI»), Moscow, Russia.
3Dmitrii Sergeevich Elkin, Federal State Unitary Enterprise Central Scientific Research Automobile and Automotive Institute “NAMI” (FSUE «NAMI»), Moscow, Russia.
4Vladislav Olegovich Strukov, Federal State Unitary Enterprise Central Scientific Research Automobile and Automotive Institute “NAMI” (FSUE «NAMI»), Moscow, Russia.
Manuscript received on July 20, 2019. | Revised Manuscript received on August 10, 2019. | Manuscript published on August 30, 2019. | PP: 5302-5306 | Volume-8 Issue-6, August 2019. | Retrieval Number: F9156088619/2019©BEIESP | DOI: 10.35940/ijitee.F9156.088619
Open Access | Ethics and Policies | Cite | Mendeley
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: This work analyzes experimental results of traffic control of unmanned vehicle convoy (UMV) with manned master vehicle in Russian road climatic environment. The problem of obstacle avoidance in driving lanes and position stabilization on preset motion path is reduced to the problem of dynamic stabilization of state variables. Its solution is aided by virtual data sensors requiring for minimum configuration of engineering tools. Relative positions of vehicles are determined by algorithms of combined data processing of navigation systems and machine vision which make it possible to solve this problem without visible road markings and radio vision for satellite navigation. Experimental results show that the developed control algorithms of UMV convoy are capable to solve the problem of its dynamic stabilization in actual traffic environment. The developed control algorithms of traction, braking, and path provide efficient operation on all types of surfaces including slippery roads. Scientific novelty of this work is comprised of experimental verification of efficiency of the developed solutions for advanced unmanned vehicles in Russia.
Keywords: Vehicle, Autonomous Vehicle, Unmanned Vehicle, Neuron Networks, Computer Vision Systems, Traffic Safety, Traffic Control system, convoy of Unmanned vehicles, virtual sensor, Dynamic Stabilization, Navigation, vision Systems.