移动计算流量仿真模型的图形化分析

W. Suh
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引用次数: 0

摘要

随着越来越多的路边和车载传感器的部署,各种各样的交通数据正在变得实时可用。这些实时交通数据通过无线通信在车辆之间以及车辆与交通管理中心之间共享。这一系列事件为移动计算和在线交通模拟创造了机会。本文介绍了基于移动计算的自组织分布式仿真模型的基本分析背景。图形化地描述了临时分布式仿真中的回滚过程。流量图和累积车辆数量图显示,随着所选阈值的不同,整个系统的仿真速度和估计精度可能存在显著差异。提出了测量系统可预测性的两个主要标准:1)预测视界的长度,即系统提供的估计比当前挂钟时间提前了多远;2)在特定预测视界上的估计有多准确,即估计的准确度有多高(与实际交通状况相比)。这两个标准以及逻辑过程仿真与实时现场数据驱动的仿真客户端数据之间的关系也以图形方式进行了演示。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Graphical Analysis of Mobile Computing Traffic Simulation Model
As more roadside and in-vehicle sensors are deployed, variety of traffic data are becoming available in real time. These real time traffic data are shared among vehicles and between vehicles and traffic management centers through wireless communication. This course of events creates an opportunity for mobile computing and online traffic simulations. This paper presents the fundamental analytical background on mobile computing based ad hoc distributed simulation model. Rollback process in the ad hoc distributed simulation is graphically described. Flow rate diagram and cumulative number of vehicle diagram shows that the overall system simulation speed and estimate accuracy may differ significantly as a function of the selected threshold. Two main criteria to measure the system's predictability are presented: 1) length of prediction horizon, that is, how far in advance of the current wall-clock time the system provides estimates and 2) how accurate the estimates are at specific prediction horizon, i.e. how accurate is the estimate (compared with the actual traffic conditions). These two criteria and the relation between logical process simulations and the real time field data driven simulation client data are graphically demonstrated as well.
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