32 resultados para Air traffic control

em Deakin Research Online - Australia


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A traffic control device in the form of a humanoid character robot, doll or dummy is used to warn driver of danger ahead on the road. The device can be used on roads, streets and in other sites where there are moving vehicles. The robotic device informs drivers of impending danger by moving its arms and sounding an acoustic alarm. In this way the robot can simulate a policeman or road flagging operator. The device may also include speed detection and preferably speed indication means. The robot may make decisions based on the detected speed of a vehicle and the limit for the area in operating the arms and sound warning means. The robot may also be equipped with a camera or video. The robot may also be controlled wirelessly.

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In order to alleviate the traffic congestion and reduce the complexity of traffic control and management, it is necessary to exploit traffic sub-areas division which should be effective in planing traffic. Some researchers applied the K-Means algorithm to divide traffic sub-areas on the taxi trajectories. However, the traditional K-Means algorithms faced difficulties in processing large-scale Global Position System(GPS) trajectories of taxicabs with the restrictions of memory, I/O, computing performance. This paper proposes a Parallel Traffic Sub-Areas Division(PTSD) method which consists of two stages, on the basis of the Parallel K-Means(PKM) algorithm. During the first stage, we develop a process to cluster traffic sub-areas based on the PKM algorithm. Then, the second stage, we identify boundary of traffic sub-areas on the base of cluster result. According to this method, we divide traffic sub-areas of Beijing on the real-word (GPS) trajectories of taxicabs. The experiment and discussion show that the method is effective in dividing traffic sub-areas.

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This paper presents a conveyor-based methodology to model complex vehicle flows common to factory and distribution warehouse facilities. The AGV and human path modelling techniques available in many commercial discrete event simulation packages require extensive knowledge and time to implement even the simplest flow control rules for multiple vehicle interaction. Although discrete event simulation is accepted as an effective tool to model vehicle delivery movements, human paths and delivery schedules for modern assembly lines, the time to generate accurate models is a significant limitation of existing simulation-based optimisation methodologies. The flow control method has been successfully implemented using two commercial simulation packages. It provides a realistic visual representation, as well as accurate statistical results, and reduces the model development process cost.

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Traffic congestion is one of the major problems in modern cities. This study applies machine learning methods to determine green times in order to minimize in an isolated intersection. Q-learning and neural networks are applied here to set signal light times and minimize total delays. It is assumed that an intersection behaves in a similar fashion to an intelligent agent learning how to set green times in each cycle based on traffic information. Here, a comparison between Q-learning and neural network is presented. In Q-learning, considering continuous green time requires a large state space, making the learning process practically impossible. In contrast to Q-learning methods, the neural network model can easily set the appropriate green time to fit the traffic demand. The performance of the proposed neural network is compared with two traditional alternatives for controlling traffic lights. Simulation results indicate that the application of the proposed method greatly reduces the total delay in the network compared to the alternative methods.

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In this paper, we describe SpeedNet, a GSM network variant which resembles an ad hoc wireless mobile network where base stations keep track of the velocities of mobile users (cars). SpeedNet is intended to track mobile users and their speed passively for both speed policing and control of traffic. The speed of the vehicle is controlled in a speed critical zone by means of an electro-mechanical control system, suitably referred to as VVLS (Vehicular Velocity Limiting System). VVLS is mounted on the vehicle and responds to the command signals generated by the base station. It also determines the next base station to handoff, in order to improve the connection reliability and bandwidth efficiency of the underlying network. Robust Extended Kalman Filter (REKF) is used as a passive velocity estimator of the mobile user with the widely used proportional and integral controller speed control. We demonstrate through simulation and analysis that our prediction algorithm can successfully estimate the mobile user’s velocity with low system complexity as it requires two closest mobile base station measurements and also it is robust against system uncertainties due to the inherent deterministic nature in the mobility model.

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Routing in ad hoc networks faces significant challenges due to node mobility and dynamic network topology. In this work we propose the use of mobility prediction to reduce the search space required for route discovery. A method of mobility prediction making use of a sectorized cluster structure is described with the proposal of the Prediction based Location Aided routing (P-LAR) protocol. Simulation study and analytical results of the of P-LAR find it to offer considerable saving in the amount of routing traffic generated during the route discovery phase.

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Mobile ad-hoc networks are characterised by constant topology changes, the absence of fixed infrastructure and lack of any centralised control. Traditional routing algorithms prove to be inefficient in such a changing environment. Ad-hoc routing protocols such as dynamic source routing (DSR), ad-hoc on-demand distance vector routing (AODV) and destination-sequence distance vector (DSDV) have been proposed to solve the multi hop routing problem in ad-hoc networks. Performance studies of these routing protocols have assumed constant bit rate (CBR) traffic. Real-time multimedia traffic generated by video-on demand and teleconferencing services are mostly variable bit rate (VBR) traffic. Most of these multimedia traffic is encoded using the MPEG standard. (ISO moving picture expert group). When video traffic is transferred over MANETs a series of performance issues arise. In this paper we present a performance comparison of three ad-hoc routing protocols - DSR, AODV and DSDV when streaming MPEG4 traffic. Simulation studies show that DSDV performs better than AODV and DSR. However all three protocols fail to provide good performance in large, highly mobile network environments. Further study is required to improve the performance of these protocols in mobile ad-hoc networks offering VBR services.

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In this paper, we describe SpeedNet, a GSM network variant which resembles an ad hoc wireless mobile network where base stations (possibly other vehicles in the network) keep track of the velocities of mobile users (cars). SpeedNet is intended to track mobile users and their speed passively for both speed policing and control of traffic. The speed of the vehicle is controlled in a speed critical zone by means of an electro-mechanical control system, suitably referred to as VVLS (vehicular velocity limiting system). VVLS is mounted in the vehicle and responds to the command signals generated by the base station. It also determines the next basestation to handoff, in order to improve the connection reliability and bandwidth efficiency of the underlying network. Robust extended Kalman filter (REKF) is used as a passive velocity estimator of the mobile user with the widely used proportional and integral controller speed control. We demonstrate through simulation and analysis that our prediction algorithm can successfully estimate the mobile users velocity with low system complexity as it requires two closet mobile-base station measurement and also it is robust against system uncertainties due to the inherent deterministic nature in the mobility model.

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The operation of two 60 m2 solar air heaters serving a large studio teaching space has been monitored for a twelve month period. The solar contribution of the heaters was found to be less than 5%, and in some instances the heaters actually contributed to the space heating load. A validated mathematical model of the studio and it’s heating, ventilation and air conditioning system was used to investigate performance improvement strategies. It was found a different control strategy and recommissioned control sensors would substantially improve the solar air heater performance.

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The ring spinning process has been used to produce fine and high quality staple fibre yarns. The stability of the rotating yarn loop (i.e. balloon) between the yarn-guide and the traveller-ring is crucial to the success and economics of this process. Balloon control rings are used to contain the yarn-loop, by reducing the yarn tension and decreasing the balloon flutter instability. Flutter instability here refers to the uncontrolled changes in a ballooning yarn under dynamic forces, including the air drag. Due to the significant variation in the length and radius of the balloon during the bobbin filling process, the optimal location for the balloon control ring is not easily determined. In order to address this difficulty, this study investigates the variation in the radius of a free balloon and examines the effect of balloon control rings of various diameters at different locations on yarn tension and balloon flutter stability. The results indicate that the maximum radius of a free balloon and its corresponding position depend not only on the yarn-length to balloon-height ratio, but also on yarn type and count. A control ring of suitable radius and position can significantly reduce yarn tension and decrease flutter instability of free single-loop balloons. While the balloon control rings are usually fixed to, and move in sinc with, the ring frame, results reported in this study suggest that theoretically, a balloon control ring that always remains approximately half way between the yarn-guide and the ring rail during spinning can lead to significant reduction in yarn tension.

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This simple and scalable Differentiated Services (DiffServ) QoS control model is acceptable for the core of the network. However, more explicit and stringent admission and reservation based QoS mechanisms are required in the wireless access segment of the network, where available resources are severely limited and the degree of traffic aggregation is not significant, thus rendering the DiffServ principles less effective. In this paper we present a suitable hybrid QoS architecture framework to address the problem. At the wireless access end, the local QoS mechanism is designed in the context of IEEE 802.11 WLAN with 802.11e QoS extensions. At the edge and over the DiffServ domain, the Fair Intelligent Congestion Control (FICC) algorithm is applied to provide fairness among traffic aggregates and control congestion at the bottleneck interface between the wireless link and the network core.