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Statistical Modeling Framework of Vessel Traffic Streams in Tokyo Bay

机译:东京湾船舶交通流统计建模框架

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摘要

The use of AIS historical data provides a great opportunity for traffic streams analysis and also for discovering related processes that govern the traffic in confined areas. To model traffic streams, a statistical analysis is necessary to determine the most optimized spatial distributions that can represent the traffic with its evolution throughout the analyzed area. In this paper, a framework is designed where AIS historical data is utilized to explore the existing maneuvering patterns in the area and model the parameters describing the traffic flow. This work is the first step leading to the creation of a macroscopic model of traffic flow through statistical inference analysis of vessel traffic streams within a selected area.The results of this work shed light on the behavior of vessel traffic streams at a macroscopic level (group vessel level), through statistical modeling of the traffic flow into distribution functions. This work sets the basis for exploring the behavior of vessel traffic streams at specific locations and times; and eventually predicts and assesses the evolution of future traffic through simulation.
机译:AIS历史数据的使用为交通流分析以及发现控制狭窄区域交通的相关过程提供了绝佳的机会。为了对交通流进行建模,必须进行统计分析以确定最优化的空间分布,以反映交通在整个分析区域内的演变情况。在本文中,设计了一个框架,其中利用AIS历史数据来探索该区域中现有的机动模式并为描述交通流的参数建模。这项工作是通过对选定区域内船只交通流进行统计推断分析来建立交通流宏观模型的第一步。这项工作的结果为宏观层面的船只交通流的行为提供了启发(组船只级别),通过将流量转化为分布函数的统计模型进行。这项工作为探索特定位置和时间的船舶交通流的行为奠定了基础。并最终通过模拟来预测和评估未来流量的演变。

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