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Design and Implementation of Transportation Management System

机译:运输管理系统的设计与实现

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This paper proposes an effective method of transportation management system. This proposed system is designed to interconnect public transport vehicles and bus stations to "Central Room" to monitor the vehicles & traffic status. Based on the collected data and via analyzing road condition, estimated arrival times are computed and transmitted to all relevant stations. The main structure of proposed system consists of Bus unit, station unit and main control centre with servers. Bus and station unit can be hardware unit or mobile android unit. Monitoring Busses based on GPS and GPRS applications. The data transferred between Bus units, station units and the main servers are managed via GPRS/UMTS link. At the server (Central Room) and based on the collected data from buses and via analyzing road condition, accurate arrival times will be computed (Via Neural network (NN)/Kalman Filter (KF)) and transmitted to all relevant stations. In this paper, we proposed a modified technique to predict bus arrival time depending on the two algorithms (NN & KF) simultaneously to take advantage of historical data (NN) with current data (KF). Achieving these main features will cause major improvements in public transport convenience and safety. Field tests were performed under real traffic situations in order to test the system.
机译:本文提出了一种有效的运输管理系统方法。这一提出的系统旨在将公共交通工具和公交车站互连到“中心室”,以监控车辆和交通状态。基于收集的数据和通过分析道路状况,计算估计的到达时间并传输到所有相关站。建议系统的主要结构包括总线单元,站单元和主控制中心与服务器组成。总线和站单元可以是硬件单元或移动Android单元。基于GPS和GPRS应用的监控总线。在总线单元,站单元和主服务器之间传输的数据通过GPRS / UMTS链路进行管理。在服务器(中央房间)并基于来自总线的收集数据和通过分析路况,将计算准确到达时间(通过神经网络(NN)/卡尔曼滤波器(KF))并传输到所有相关站。在本文中,我们提出了一种修改的技术,以预测总线到达时间,这取决于两个算法(NN&KF)同时利用当前数据(KF)的历史数据(NN)。实现这些主要功能将导致公共交通便利和安全的重大改进。在实际交通情况下进行现场测试,以测试系统。

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