• Title/Summary/Keyword: Multi-Vehicle

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Multi-system vehicle formation control based on nearest neighbor trajectory optimization

  • Mingxia, Huang;Yangyong, Liu;Ning, Gao;Tao, Yang
    • Advances in nano research
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    • v.13 no.6
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    • pp.587-597
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    • 2022
  • In the present study, a novel optimization method in formation control of multi -system vehicles based on the trajectory of the nearest neighbor trajectory is presented. In this regard, the state equations of each vehicle and multisystem is derived and the optimization scheme based on minimizing the differences between actual positions and desired positions of the vehicles are conducted. This formation control is a position-based decentralized model. The trajectory of the nearest neighbor are optimized based on the current position and state of the vehicle. This approach aids the whole multi-agent system to be optimized on their trajectory. Furthermore, to overcome the cumulative errors and maintain stability in the network a semi-centralized scheme is designed for the purpose of checking vehicle position to its predefined trajectory. The model is implemented in Matlab software and the results for different initial state and different trajectory definition are presented. In addition, to avoid collision avoidance and maintain the distances between vehicles agents at a predefined desired distances. In this regard, a neural fuzzy network is defined to be utilized in conjunction with the control system to avoid collision between vehicles. The outcome reveals that the model has acceptable stability and accuracy.

DEVELOPMENT OF MATDYMO (MULTI-AGENT FOR TRAFFIC SIMULATION WITH VEHICLE DYNAMICS MODEL) I: DEVELOPMENT OF TRAFFIC ENVIRONMENT

  • CHOI K. Y.;KWON S. J.;SUH M. W.
    • International Journal of Automotive Technology
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    • v.7 no.1
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    • pp.25-34
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    • 2006
  • For decades, simulation technique has been well validated in areas such as computer and communication systems. Recently, the technique has been much used in the area of transportation and traffic forecasting. Several methods have been proposed for investigating complex traffic flows. However, the dynamics of vehicles and diversities of driver characteristics have never been considered sufficiently in these methods, although they are considered important factors in traffic flow analysis. In this paper, we propose a traffic simulation tool called Multi-Agent for Traffic Simulation with Vehicle Dynamics Model (MATDYMO). Road transport consultants, traffic engineers and urban traffic control center managers are expected to use MATDYMO to efficiently simulate traffic flow. MATDYMO has four sub systems: the road management system, the vehicle motion control system, the driver management system, and the integration control system. The road management system simulates traffic flow for various traffic environments (e.g., multi-lane roads, nodes, virtual lanes, and signals); the vehicle motion control system constructs the vehicle agent by using various vehicle dynamic models; the driver management system constructs the driver agent capable of having different driving styles; and lastly, the integrated control system regulates the MATDYMO as a whole and observes the agents running in the system. The vehicle motion control system and driver management system are described in the companion paper. An interrupted and uninterrupted flow model were simulated, and the simulation results were verified by comparing them with the results from a commercial software, TRANSYT-7F. The simulation result of the uninterrupted flow model showed that the driver agent displayed human-like behavior ranging from slow and careful driving to fast and aggressive driving. The simulation of the interrupted flow model was implemented as two cases. The first case analyzed traffic flow as the traffic signals changed at different intervals and as the turning traffic volume changed. Second case analyzed the traffic flow as the traffic signals changed at different intervals and as the road length changed. The simulation results of the interrupted flow model showed that the close relationship between traffic state change and traffic signal interval.

MULTI-SENSOR DATA FUSION FOR FUTURE TELEMATICS APPLICATION

  • Kim, Seong-Baek;Lee, Seung-Yong;Choi, Ji-Hoon;Choi, Kyung-Ho;Jang, Byung-Tae
    • Journal of Astronomy and Space Sciences
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    • v.20 no.4
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    • pp.359-364
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    • 2003
  • In this paper, we present multi-sensor data fusion for telematics application. Successful telematics can be realized through the integration of navigation and spatial information. The well-determined acquisition of vehicle's position plays a vital role in application service. The development of GPS is used to provide the navigation data, but the performance is limited in areas where poor satellite visibility environment exists. Hence, multi-sensor fusion including IMU (Inertial Measurement Unit), GPS(Global Positioning System), and DMI (Distance Measurement Indicator) is required to provide the vehicle's position to service provider and driver behind the wheel. The multi-sensor fusion is implemented via algorithm based on Kalman filtering technique. Navigation accuracy can be enhanced using this filtering approach. For the verification of fusion approach, land vehicle test was performed and the results were discussed. Results showed that the horizontal position errors were suppressed around 1 meter level accuracy under simulated non-GPS availability environment. Under normal GPS environment, the horizontal position errors were under 40㎝ in curve trajectory and 27㎝ in linear trajectory, which are definitely depending on vehicular dynamics.

Application of Multi Criteria Decision Making for Selection of Automobile Safety Option (안전 옵션 선정 다준규의사결정 모델)

  • Kim, Taehee
    • Journal of Auto-vehicle Safety Association
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    • v.10 no.2
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    • pp.50-55
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    • 2018
  • Choosing automobile safety options is price-performance matter. The best fit options to buyer who has a certain driving habit are problem of MCDM (Multi Criteria Decision Making) because price of safety option, statistics of relating accident, consequence of accident, and driving habit are the multi criteria to be evaluated. In this paper, PROMETHEE-GAIA methodology is applied for solving this MCDM problem. The result shows that a different driving habit makes different choosing priority of safety options.

DEVELOPMENT OF MATDYMO(MULTI-AGENT FOR TRAFFIC SIMULATION WITH VEHICLE DYNAMICS MODEL) II: DEVELOPMENT OF VEHICLE AND DRIVER AGENT

  • Cho, K.Y.;Kwon, S.J.;Suh, M.W.
    • International Journal of Automotive Technology
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    • v.7 no.2
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    • pp.145-154
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    • 2006
  • In the companion paper, the composition and structure of the MATDYMO (Multi-Agent for Traffic Simulation with Vehicle Dynamic Model) were proposed. MATDYMO consists of the road management system, the vehicle motion control system, the driver management system, and the integration control system. Among these systems, the road management system and the integration control system were discussed In the companion paper. In this paper, the vehicle motion control system and the driver management system are discussed. The driver management system constructs the driver agent capable of having different driving styles ranging from slow and careful driving to fast and aggressive driving through the yielding index and passing index. According to these indices, the agents pass or yield their lane for other vehicles; the driver management system constructs the vehicle agents capable of representing the physical vehicle itself. A vehicle agent shows its behavior according to its dynamic characteristics. The vehicle agent contains the nonlinear subcomponents of engine, torque converter, automatic transmission, and wheels. The simulation is conducted for an interrupted flow model and its results are verified by comparison with the results from a commercial software, TRANSYT-7F. The interrupted flow model simulation is implemented for three cases. The first case analyzes the agents' behaviors in the interrupted flow model and it confirms that the agent's behavior could characterize the diversity of human behavior and vehicle well through every rule and communication frameworks. The second case analyzes the traffic signals changed at different intervals and as the acceleration rate changed. The third case analyzes the effects of the traffic signals and traffic volume. The results of these analyses showed that the change of the traffic state was closely related with the vehicle acceleration rate, traffic volume, and the traffic signal interval between intersections. These simulations confirmed that MATDYMO can represent the real traffic condition of the interrupted flow model. At the current stage of development, MATDYMO shows great promise and has significant implications on future traffic state forecasting research.

A Study on NDT Techniques for Evaluation of Corrosion in Multi-layered Conductive Structures of Urban Railroad Car of the paper (도시철도차량의 다층 구조물 부식 측정을 위한 비파괴 기법 연구)

  • Lee, Chan-Woo;Chung, Jung-Duk;Song, Sung-Jin
    • Proceedings of the KSR Conference
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    • 2011.10a
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    • pp.2691-2696
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    • 2011
  • THE CARBODY AND BOGIE FRAME OF AN URBAN RAILWAY VEHICLE CONSIST OF MULTI-LAYERED WELDING STRUCTURE. IN KOREA ENDURANCE LIMIT OF AN URBAN RAILWAY VEHICLE IS STSTED IN THE RULE OF MANAGING URBAN RAILWAY VEHICLE UNDER THE LAW OF URBAN RAILWAY. IN KOREA AN URBAN RAILWAY VEHICLE IS DESIGNED AND MADE TO KEEP ITS QUALITY OVER 25 YEARS. WHEN THE RAILWAY VEHICLE BECOMES 25 YEARS OLD, CORROSION OF CARBODY AND UNDER FRAME OF A RAILWAY VEHICLE IS EVALUATED ACCORDING TO THE NON-DESTRUCTIVE TESTING. IT CAN BE USED AS LONG AS 40 YEARS. IT IS STATED IN THE ARTICLE 4 'THE METHOD AND STANDARDS OF PRECISE DIAGNOSIS' UNDER THE RULE OF MANAGING RAILWAY VEHICLE IN KOREA. SO, IN THIS STUDY, WE HAVE INVESTIGATED PERFORMANCE OF PULSED EDDY CURRENT TESTING METHOD BY MEASURING THICKNESS VARIATION OF FABRICATE OF CARBODY AND UNDER FRAME FOR URBAN RAILROAD CAR. AND THEM, THE PROCESS OF EVALUATING REMAINING LIFE ACCORDING TO TESTING OF CORROSION AMOUNT IS INTRODUCED.

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Analysis of Dynamic Characteristics for Four-Wheel-Steering Automated Guided Vehicle(AGV) System (4륜 조향 무인 컨테이너 차량(AGV) 시스템의 동특성 분석)

  • 최재영;이영진;변성태;이권순;이만형
    • 제어로봇시스템학회:학술대회논문집
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    • 2000.10a
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    • pp.306-306
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    • 2000
  • This paper analyze the dynamic characteristics of Automated Guided Vehicle(AGV) which is being developed as a part of automation in port through DADS, one of the multi-dynamic analysis program, Previous evaluation of a vehicle is carried out through the continuous driving test of a real vehicle, however this method raise the loss of finance and time. If it is possible to analyze the dynamic characteristics of vehicle before construction completely we can compensate the loss of money and time during constructing. AGV contained containers is very heavy and its center of gravity can be easily changed with the disturbance from road or cornering. It makes AGV unsatisfied, therefore we evaluate the handling characteristics and stability of the full vehicle model. This paper contribute to establish the foundation of the development of a new system like a AGV which have a special structure.

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Optimization of Multi-Vehicle Delivery using Sweep Algorithm and Common Area Double Reassignment (Sweep해법 및 공동구역 2차 재할당에 의한 복수차량 배송 최적화 연구)

  • Park, Sungmee;Moon, Geeju
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.37 no.1
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    • pp.133-140
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    • 2014
  • An efficient heuristic for two-vehicle-one-depot problems is developed in this research. Vehicle moving speeds are various along hour based time intervals due to traffic jams of rush hours. Two different heuristics are examined. One is that the delivery area assignment is made using Sweep algorithm for two vehicles by splitting the whole area in half to equally divide all delivery points. The other is using common area by leaving unassigned area between the assigned for two vehicles. The common area is reassigned by two stages to balance the completion time of two vehicle's delivery. The heuristic with common area performed better than the other due to various vehicle moving speeds and traffic jams.

Multi-Agent for Traffic Simulation with Vehicle Dynamic Model I : Development of Traffic Environment (차량 동역학을 이용한 멀티에이전트 기반 교통시뮬레이션 개발 I : 교통 환경 개발)

  • 조기용;권성진;배철호;서명원
    • Transactions of the Korean Society of Automotive Engineers
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    • v.12 no.5
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    • pp.125-135
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    • 2004
  • The validity of simulation has been well-established for decades in areas such as computer and communication system. Recently, the technique has become entrenched in specific areas such as transportation and traffic forecasting. Several methods have been proposed for investigating complex traffic flows. However, the dynamics of vehicles and their driver's characteristics, even though it is known that they are important factors for any traffic flow analysis, have never been considered sufficiently. In this paper, the traffic simulation using a multi-agent approach with considering vehicle dynamics is proposed. The multi-agent system is constructed with the traffic environment and the agents of vehicle and driver. The traffic environment consists of multi-lane roads, nodes, virtual lanes, and signals. To ensure the fast calculation, the agents are performed on the based of the rules to regulate their behaviors. The communication frameworks are proposed for the agents to share the information of vehicles' velocity and position. The model of a driver agent which controls a vehicle agent is described in the companion paper. The vehicle model contains the nonlinear subcomponents of engine, torque converter, automatic transmission, and wheels. The simulation has proceeded for an interrupted and uninterrupted flow model. The result has shown that the driver agent performs human-like behavior ranging from slow and careful to fast and aggressive driving behavior, and that the change of the traffic state is closely related with the distance and the signal delay between intersections. The system developed shows the effectiveness and the practical usefulness of the traffic simulation.

Multi-vehicle Route Selection Based on an Ant System

  • Kim, Dong-Hun
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.8 no.1
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    • pp.61-67
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    • 2008
  • This paper introduces the multi-vehicle routing problem(MRP) which is different from the traveling sales problem(TSP), and presents the ant system(AS) applied to the MRP. The proposed MRP is a distributive model of TSP since many vehicles are used, not just one salesman in TSP and even some constraints exist. In the AS, a set of cooperating agents called vehicles cooperate to find good solutions to the MRP. To make the proposed MRP extended more, Tokyo city model(TCM) is proposed. The goal in TCM is to find a set of routes that minimizes the total traveling time such that each vehicle can reach its destination as soon as possible. The results show that the AS can effectively find a set of routes minimizing the total traveling time even though the TCM has some constraints.