Книги з теми "Simulation vehicle model"

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1

Cersovsky, Donald D. Mathematical model and analysis of the Tactical Unmanned Ground Vehicle (TUGV) using computer simulation. Monterey, Calif: Naval Postgraduate School, 1993.

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2

Tsukamoto, Shigeki. On the simulation test for the relative motion of separated sub-boosters on M-3SII with nearly half a model vehicle ST-735 and their motion analyses using inertial sensors output. Tokyo: Institute of Space and Astronautical Science, 1989.

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3

Motor vehicle dynamics: Modeling and simulation. Singapore: World Scientific, 1997.

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4

Chuvikov, Dmitriy. Models and algorithms for reconstruction and examination of emergency events of road accidents based on logical artificial intelligence. 2nd ed. ru: INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1220729.

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Анотація:
The purpose of the monograph is to create a methodology, combined expert and simulation models, as well as algorithms and software-modeling tools for reconstruction and examination of accident events for automating decision-making by an expert center employee. The methodology of combining and algorithms of joint work of an expert system based on logical artificial intelligence (mivar approach) and a simulation system for solving problems of reconstruction and examination of road accidents are developed; model reconstruction and examination of the accident in the formalism of the knowledge base bipartite oriented mivar nets, including analysis formulas braking qualities of the vehicle, determining the speed of a car's performance in terms of specific DTS, the formula for calculating different occasions: - slip car when braking, driving on curved sections of the road, hitting a car on the pedestrian in uniform motion and unlimited visibility; a method of generation of interfaces for designer expert systems based on the concept of mivar approach; special software in the form of expert systems "Analysis of road accident" in order to reduce the complexity of the process of calculating the disputed accidents, errors in the calculation and improve the accuracy and objectivity of the results obtained and the speed and quality of the calculations. It can be useful to specialists of expert institutions, insurance companies, educational institutions in the field of expertise, as well as unmanned vehicles in terms of objective analysis and examination of road accidents.
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5

Modeling and simulation of aerospace vehicle dynamics. Reston, VA: American Institute of Aeronautics and Astronautics, 2000.

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6

Modeling and simulation of aerospace vehicle dynamics. Reston, Virginia: American Institute of Aeronautics and Astronautics, Inc., 2014.

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7

Olstam, Johan Janson. A model for simulation and generation of surrounding vehicles in driving simulators. Linko ping: Linko pings universitet, 2005.

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8

Jalinier, Christian. Energy consumption of heavy road vehicles: Dynamic verifiable interactive transportation model. Pointe Claire, Que: FERIC, 1992.

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9

Chaturvedi, Alok R. A model for simulating AGV congestion in an FMS. West Lafayette, Ind: Institute for Research in the Behavioral, Economic, and Management Sciences, Krannert Graduate School of Management, Purdue University, 1990.

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10

Porter, Christopher, David Kall, Daniel Beagan, Richard Margiotta, John Koupal, Scott Fincher, and Alan Stanard. Input Guidelines for Motor Vehicle Emissions Simulator Model, Volume 3: Final Report. Washington, D.C.: Transportation Research Board, 2015. http://dx.doi.org/10.17226/22212.

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11

Pushkin, Kachroo, ed. Autonomous underwater vehicles: Modeling, control design, and simulation. Boca Raton: CRC Press, 2011.

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12

Matthew, Brach R., ed. Vehicle accident analysis and reconstruction methods. 2nd ed. Warrendale, Pa: SAE International, 2011.

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13

Bashkatov, Aleksandr. Simulation of accidents on route transport. ru: INFRA-M Academic Publishing LLC., 2022. http://dx.doi.org/10.12737/1860140.

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The monograph is devoted to the study of accidents in the operation of fixed-route vehicles and the development of organizational measures that increase the safety of its functioning within the city. Based on the collected and systematized statistical data, an integrated approach to solving transport security problems has been applied. Within the framework of the study, mathematical models and methods for assessing factors affecting the accident rate of route vehicles are proposed, a statistical assessment of their significance is carried out and technological techniques for improving safety on highways are proposed. It is intended for specialists of management services, dispatchers of transport companies, and may also be of interest to engineering, technical and scientific workers involved in the safety and organization of route transport in cities.
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14

Nalecz, Andrzej G. Vehicle Animation Software (VAS) to animate results obtained from vehicle handling and rollover simulations and tests. Washington, DC: U.S. Dept. of Transportation, National Highway Traffic Safety Administration, 1991.

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15

United States. National Highway Traffic Safety Administration. Office of Crash Avoidance Research., ed. Vehicle Animation Software (VAS) to animate results obtained from vehicle handling and rollover simulations and tests. Washington, DC: U.S. Dept. of Transportation, National Highway Traffic Safety Administration, 1991.

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16

Nalecz, Andrzej G. Vehicle Animation Software (VAS) to animate results obtained from vehicle handling and rollover simulations and tests. Washington, DC: U.S. Dept. of Transportation, National Highway Traffic Safety Administration, 1991.

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17

Pushkin, Kachroo, ed. Autonomous underwater vehicles: Modeling, control design, and simulation. Boca Raton: CRC Press, 2011.

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18

Liu, Wei. Introduction to hybrid vehicle system modeling & control. Hoboken, N.J: Wiley, 2012.

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19

Dubanov, Aleksandr. Computer simulation in pursuit problems. ru: Publishing Center RIOR, 2022. http://dx.doi.org/10.29039/02102-6.

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Currently, computer simulation in virtual reality systems has a special status. In order for a computer model to meet the requirements of the tasks it models, it is necessary that the mathematical apparatus correctly describe the simulated phenomena. In this monograph, the simulation of pursuit problems is carried out. An adaptive modeling of the behavior of both pursuers and targets is carried out. An iterative calculation of the trajectories of the participants in the pursuit problem is carried out. The main attention is paid to the methods of pursuit and parallel rendezvous. These methods are taken as the basis of the study and are modified in the future. The scientific novelty of the study is the iterative calculation of the trajectories of the participants in the pursuit task when moving at a constant speed, while following the predicted trajectories. The predicted trajectories form a one-parameter network of continuous lines of the first order of smoothness. The predicted trajectories are calculated taking into account the restrictions on the curvature of the participant in the pursuit problem. The fact of restrictions on curvature can be interpreted as restrictions on the angular frequency of rotation of the object of the pursuit problem. Also, the novelty is the calculation of the iterative process of group pursuit of multiple targets, when targets are hit simultaneously or at specified intervals. The calculation of the parameters of the network of predicted trajectories is carried out with a curvature variation in order to achieve the desired temporal effect. The work also simulates the adaptive behavior of the pursuer and the target. The principle of behavior can be expressed on the example of a pursuer with a simple phrase: "You go to the left - I go to the left." This happens at each iteration step in terms of choosing the direction of rotation. For the purpose, the principle of adaptive behavior is expressed by the phrase: "You go to the left - I go to the right." The studies, algorithms and models presented in the monograph can be in demand in the design of autonomously controlled unmanned aerial vehicles with elements of artificial intelligence. The task models in the monograph are supplemented with many animated images, where you can see the research process. Also, the tasks have an implementation in a computer mathematics system and can be transferred to virtual reality systems if necessary.
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20

Tsamilis, Sotirios E. Nonlinear analysis of coupled roll/sway/yaw stability characteristics of submersible vehicles. Monterey, Calif: Naval Postgraduate School, 1997.

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21

Khare, M. Modelling urban vehicle emissions. Southampton, UK: WIT Press, 2002.

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22

Porter, Christopher, David Kall, Daniel Beagan, Richard Margiotta, John Koupal, Scott Fincher, and Alan Stanard. Input Guidelines for Motor Vehicle Emissions Simulator Model, Volume 2: Practitioners’ Handbook: Project Level Inputs. Washington, D.C.: Transportation Research Board, 2015. http://dx.doi.org/10.17226/22213.

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23

Porter, Christopher, David Kall, Daniel Beagan, Richard Margiotta, John Koupal, Scott Fincher, and Alan Stanard. Input Guidelines for Motor Vehicle Emissions Simulator Model, Volume 1: Practitioners’ Handbook: Regional Level Inputs. Washington, D.C.: Transportation Research Board, 2015. http://dx.doi.org/10.17226/22214.

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24

Schramm, Dieter. Modellbildung und Simulation der Dynamik von Kraftfahrzeugen. Berlin: Springer Berlin, 2009.

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25

Che zai wu qi jian mo yu fang zhen. Beijing Shi: Guo fang gong ye chu ban she, 2011.

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26

Rocker, M. Modeling on nonacoustic combustion instability in simulations of hybrid motor tests. Marshall Space Flight Center, Ala: National Aeronautics and Space Administration, Marshall Space Flight Center, 2000.

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27

Ferrucci, Francesco. Pro-active Dynamic Vehicle Routing: Real-Time Control and Request-Forecasting Approaches to Improve Customer Service. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013.

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28

V, Cook M., Rycroft Michael J, Institute of Mathematics and its Applications., and Conference on Aerospace Vehicle Dynamics and Control (1992 : Cranfield Institute of Technology), eds. Aerospace vehicle dynamics and control: Based on the proceedings of a conference organized by the Institute of Mathematics and its Applications on aerospace vehicle dynamics and control, held at the Cranfield Institute of Technology, in September 1992. Oxford: Clarendon Press, 1994.

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29

Office, General Accounting. Air pollution: EPA's actions to ensure vehicle compliance with emission standards : briefing report to the chairman, Subcommittee on Oversight and Investigations, Committee on Energy and Commerce, House of Representatives. Washington, D.C: GAO, 1992.

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30

Office, General Accounting. Air pollution: Improved atmospheric model should help focus acid rain debate : report to the chairman, Subcommittee on Oversight and Investigations, Committee on Energy and Commerce, House of Representatives. Washington, D.C: GAO, 1989.

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31

Office, General Accounting. Air pollution: EPA's efforts to control gasoline vapors from motor vehicles : report to the chairman, Subcommittee on Oversight and Investigations, Committee on Energy and Commerce, House of Representatives. Washington, D.C: GAO, 1989.

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32

Office, General Accounting. Air pollution: EPA not adequately ensuring vehicles comply with emission standards : report to the chairman, Subcommittee on Oversight and Investigations, Committee on Energy and Commerce, House of Representatives. Washington, D.C: GAO, 1990.

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33

Office, General Accounting. Air pollution: Reliability of EPA's mobile source emission model could be improved : report to the Chairman, Subcommittee on Oversight and Investigations, Committee on Energy and Commerce, House of Representatives. Washington, D.C: The Office, 1990.

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34

Office, General Accounting. Air pollution: Reliability and adequacy of air quality dispersion models : report to the chairman, Subcommittee on Oversight and Investigations, Committee on Energy and Commerce, House of Representatives. Washington, D.C: The Office, 1988.

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35

Office, General Accounting. Air pollution: Reliability and adequacy of air quality dispersion models : report to the chairman, Subcommittee on Oversight and Investigations, Committee on Energy and Commerce, House of Representatives. Washington, D.C: The Office, 1988.

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36

Office, General Accounting. Air pollution: Emission sources regulated by multiple Clean Air Act provisions : report to the Chairman, Subcommittee on Clean Air, Wetlands, Private Property, and Nuclear Safety, Commmittee on Environment and Public Works, U.S. Senate. Washington, D.C. (P.O. Box 37050, Washington, D.C. 20013): U.S. General Accounting Office, 2000.

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37

Office, General Accounting. Air pollution: EPA's strategy to control emissions of benzene and gasoline vapor : report to the chairman, Subcommittee on Oversight and Investigations, Committee on Energy and Commerce, House of Representatives. Washington, D.C: GAO, 1985.

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38

Office, General Accounting. Air pollution: The Border Smog Reduction Act's impact on ozone levels : report to Congressional committees. Washington, D.C. (P.O. Box 37050, Washington, D.C. 20013): The Office, 1999.

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39

Office, General Accounting. Air pollution: Hazards of indoor radon could pose a national health problem : report. Washington, D.C: U.S. General Accounting Office, 1987.

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40

Office, General Accounting. Air pollution: Allowance trading offers an opportunity to reduce emissions at less cost : report to the Chairman, Environment, Energy, and Natural Resources Subcommittee, Committee on Government Operations, House of Representatives. Washington, D.C: The Office, 1994.

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41

Office, General Accounting. Air pollution: Emissions from older electricity generating units : report to congressional committees. Washington, D.C. (P.O. Box 37050, Washington 20013): U.S. General Accounting Office, 2002.

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42

Office, General Accounting. Air pollution: Issues inhibiting marine vessel emission controls are still unresolved : report to the chairman, Subcommittee on Oversight and Investigations, Committee on Energy and Commerce, House of Representatives. Washington, D.C: The Office, 1988.

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43

D, Shaughnessy J., and Langley Research Center, eds. Hypersonic vehicle simulation model: Winged-cone configuration. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1990.

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44

National Aeronautics and Space Administration (NASA) Staff. Hypersonic Vehicle Simulation Model: Winged-Cone Configuration. Independently Published, 2018.

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45

Center, Turner-Fairbank Highway Research, ed. In-vehicle information systems: Demand model. [McLean, Va: U.S. Dept. of Transportation, Federal Highway Administration, Research, Development, and Technology, Turner-Fairbank Highway Research Center, 2000.

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46

In-vehicle information systems: Demand model. [McLean, Va: U.S. Dept. of Transportation, Federal Highway Administration, Research, Development, and Technology, Turner-Fairbank Highway Research Center, 2000.

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47

Developing a Conceptual Unmanned Aerial Vehicle Communications Mobile AD Hoc Network Simulation Model. Storming Media, 2002.

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48

Engineers, Society of Automotive, and SAE International Congress & Exposition (1993 : Detroit, Mich.), eds. Vehicle dynamics and simulation. Warrendale, PA: Society of Automotive Engineers, 1993.

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49

Engineers, Society of Automotive. Research into Vehicle Dynamics and Simulation - 1997. SAE International, 1997.

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50

Engineers, Society of Automotive, and SAE International Congress & Exposition (1997 : Detroit, Mich.), eds. Research into vehicle dynamics and simulation - 1997. Warrendale, PA: Society of Automotive Engineers, 1997.

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