...
首页> 外文期刊>Transportation research >An efficient and exact event-based algorithm for solving simplified first order dynamic network loading problems in continuous time
【24h】

An efficient and exact event-based algorithm for solving simplified first order dynamic network loading problems in continuous time

机译:一种有效且基于事件的高效算法,用于解决连续时间内简化的一阶动态网络负载问题

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       

摘要

In this paper a novel solution algorithm is proposed for exactly solving simplified first order dynamic network loading (DNL) problems for any generalised network. This DNL solution algorithm, termed eLTM (event-based Link Transmission Model), is based on the seminal Lighthill-Witham-Richards (LWR) model, adopts a triangular fundamental diagram and includes a generalised first order node model formulation. Unlike virtually all DNL solution algorithms, eLTM does not rely on time discretisation, but instead adopts an event based approach. The main advantage of this approach is the possibility of yielding exact results. Furthermore, an approximate version of the same algorithm is introduced. The user can configure an a-priori threshold that dictates the approximation error (measurable a-posteriori). Using this approximation the computational effort required decreases significantly, making it especially suitable for large scale applications. The computational complexity is investigated and results are demonstrated via theoretical and real world case studies. Fixed periods of stationary demands are included adopting a matrix demand profile to mimic basic departure time demand fluctuations. Finally, the information loss of the approximate solution is assessed under different configurations. Crown Copyright (C) 2015 Published by Elsevier Ltd. All rights reserved.
机译:在本文中,提出了一种新颖的求解算法,用于精确解决任何广义网络的简化一阶动态网络加载(DNL)问题。这种DNL解决方案算法称为eLTM(基于事件的链路传输模型),基于具有开创性的Lighthill-Witham-Richards(LWR)模型,采用了三角形基本图,并包含了广义的一阶节点模型。与几乎所有DNL解决方案算法不同,eLTM不依赖时间离散化,而是采用基于事件的方法。这种方法的主要优点是可以产生准确的结果。此外,介绍了相同算法的近似版本。用户可以配置一个先验阈值,该阈值指示近似误差(可测量的后验)。使用此近似值,所需的计算量将大大减少,从而使其特别适合大规模应用。研究了计算的复杂性,并通过理论和现实案例研究证明了结果。包括固定需求的固定时间段,采用矩阵需求曲线来模拟基本出发时间需求波动。最后,在不同配置下评估近似解的信息损失。 Crown版权所有(C)2015,由Elsevier Ltd.发行。保留所有权利。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号