Model of the Optimal Maneuver Route

Nohel, Jan; Stodola, Petr; Flasar, Zdeněk

doi:10.5772/intechopen.85566

Cited by 9 publications

(7 citation statements)

References 12 publications

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“…Major counter forces are the rolling resistance and the resistance of slope gradient. Counter forces are analyzed in detail in Reference [28]. The last individual composition of movement is the adhesive force.…”

Section: Forces Affecting Movement Of Vehiclesmentioning

confidence: 99%

“…In Reference [27], Nohel et al deal with the calculation of the shortest off-road vehicle route. The theory of vehicle motion based on traction curves is described by Vala and Braun in Reference [28] and Vala and Žalud in Reference [29]. The evaluation of dynamics of vehicle movement in terrain is published by Hlaváček in Reference [30].…”

Section: Introductionmentioning

confidence: 99%

“…The terrain passability model described in this article is based on the study of the mutual influence of terrain slope and soil characteristics on the movement of selected military off-road vehicles. The analysis presented in this article primarily utilizes the key findings of the papers of Vala and Braun [28], Rybansky [10][11][12][13][14][15][16][17][18][19][20][21][22][23], Hlaváček [30] and Bradbury et al [9]. Analysis of both soil databases and surface information is performed by the testing of tractive charts of various wheeled and tracked vehicles and comparing the results of cross-country movement analysis.…”

Section: Introductionmentioning

confidence: 99%

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The Impact of the Accuracy of Terrain Surface Data on the Navigation of Off-Road Vehicles

Rada

Rybanský

Dohnal

2021

IJGI

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Current soil and surface data are not detailed enough to obtain accurate analyses of cross-country movement. The reason for the research presented in this article was the absence of a methodology for the synthetic assessment of the influence of the terrain surface on the movement of military vehicles. The study is based on analyses of data and information sources of soils and surface conditions primarily with the aim to determine their reliability, availability and precision when used for analyses of terrain traversability by off-road vehicles. The key method to achieve the set objective is the employment of tractive charts of military vehicles and utilized coefficients, the coefficient of rolling resistance and the coefficient of adhesion. Input data and information is tested with a comparative method of cross-country movement analyses. Conversion of soil and surface types to tractive chart coefficients is currently not optimal. For the most part, evaluation of soil type is very inaccurate with a wide range of possible values. Results of the analysis propose developing a methodology of evaluating surface and soils for vehicle traversability.

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Section: Forces Affecting Movement Of Vehiclesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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The Impact of the Accuracy of Terrain Surface Data on the Navigation of Off-Road Vehicles

Rada

Rybanský

Dohnal

2021

IJGI

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“…Such validated models can be further implemented and used in military tactical and geographic information systems. The MCS CZ, using the TDSS, specifies the spatial course of the maneuver axis on the battlefield in the form of offensive maneuvers described in the work by Nohel and Flasar 7 and Nohel et al 8 The MCS CZ is constantly being improved. One of its improvements is the model of multiple maneuver of units, which allows commanders to design a coordinated maneuver of up to three units, teams or vehicles toward a common goal.…”

Section: Introductionmentioning

confidence: 99%

Multiple maneuver model of cooperating ground combat troops

Nohel

Stodola

Flasar

et al. 2022

Journal of Defense Modeling & Simulation

Self Cite

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The article describes the possibilities of using the Maneuver Control System CZ (MCS CZ) in creating a multiple maneuver of a group of cooperating units. It is a tactical information system designed to support the decision-making of commanders in order to effectively deploy their units on the battlefield. The system evaluates the geographical and hydrometeorological battlefield influences as well as the enemy’s situation to calculate the maneuver axes of a unit composed of up to three teams with the same goal. To verify the calculations of mathematical-algorithmic models of the system, two measurements were performed on model situations. In the first of them, a group of three unmanned systems carried out an attack on an identified delivery system of weapons of mass destruction. The second model situation included a hasty attack by three infantry squads on anti-aircraft equipment. In both cases, the resulting group of maneuvers used the fastest and safe axes of advance, spatially synchronized according to tactical principles. In both cases, the enemy’s weapon systems were quickly attacked and destroyed immediately after their identification from three directions. The commander’s decision-making process was largely replaced by the MCS CZ calculations in model situations, which significantly shortened its duration.

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“…Nohel et al [ 2 ] describe the structure of the optimal route model implemented in TDSS, and its further possible use in the maneuver management system. In their calculations, they combine an assessment of the entire terrain and the safety characteristics of the working area; they focus on the cross-country capabilities of wheeled vehicles in terrain conditions; however, in the case of autonomous vehicles, there is still a need for direct control on the ground due to the accidental occurrence of microrelief forms and obstacles.…”

Section: Introductionmentioning

confidence: 99%

On the Problem of Restoring and Classifying a 3D Object in Creating a Simulator of a Realistic Urban Environment

Gorodnichev

Erokhin

Polyantseva

et al. 2022

Sensors

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Since the 20th century, a rapid process of motorization has begun. The main goal of researchers, engineers and technology companies is to increase the safety and optimality of the movement of vehicles, as well as to reduce the environmental damage caused by the automotive industry. The difficulty of managing traffic flows is that cars are driven by a person and their behavior, even in similar situations, is different and difficult to predict. To solve this problem, ground-based unmanned vehicles are increasingly being developed and implemented; however, like any other intelligent system, it is necessary to train different road scenarios. Currently, an engineer is driving an unmanned vehicle for training and thousands of kilometers are being driven for training. Of course, this approach to training unmanned vehicles is very long, and it is impossible to reproduce all the scenarios that can be found in real operations on a real road. Based on this, we offer a simulator of a realistic urban environment which allows you to reduce the training time and allows you to generate all kinds of events. To implement such a simulator, it is necessary to develop a method that would allow recreating a realistic world in one passage with cameras (monocular) installed on board the vehicle. Based on this, the purpose of this work is to develop an intelligent vehicle recognition system using convolutional neural networks, which allows you to create mesh objects for further placement in the simulator. It is important to note that the resulting objects should be optimal in size so as not to overload the system, since a large number of road infrastructure objects are stored there. Also, neural complexity should not be excessive. In this paper, the general concept and classification of convolutional neural networks are given, which allow solving the problem of recognizing 3D objects in images. Based on the analysis, the existing neural network architectures do not solve the problems mentioned above. In this connection, the authors first of all carried out the design of the system according to the methodology of modeling business processes, and also modified and developed the architecture of the neural network, which allows classifying objects with sufficient accuracy, obtaining optimized mesh objects and reducing computational complexity. The methods proposed in this paper are used in a simulator of a realistic urban environment, which reduces the time and computational costs when training unmanned transport systems.

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Model of the Optimal Maneuver Route

Cited by 9 publications

References 12 publications

The Impact of the Accuracy of Terrain Surface Data on the Navigation of Off-Road Vehicles

The Impact of the Accuracy of Terrain Surface Data on the Navigation of Off-Road Vehicles

Multiple maneuver model of cooperating ground combat troops

On the Problem of Restoring and Classifying a 3D Object in Creating a Simulator of a Realistic Urban Environment

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