On the Implementation of High Performance Computing Extensionfor Day-to-Day Traffic Assignment

Wasuwat Petprakob, Lalith Wijerathne, Takamasa Iryo, Junji Urata, Kazuki Fukuda, Muneo Hori

Research output: Contribution to journalConference articlepeer-review

Abstract

The ability to find near-optimal traffic assignments for a very large network within a few days time will substantially contribute to reduce economic losses following major earthquake disasters. However, lack of efficient numerical tools and methodologies to solve this NP-hard problem within a reasonably short time is a major challenge. This paper presents details of an HPC (High Performance Computing) enhanced system which is developed to address this need of finding near-optimal traffic assignment for large networks in a short time. The developed system is based on day-to-day algorithm and enhanced with a distributed memory parallel extension to accelerate the computation by utilizing computer clusters or supercomputers. Details of basic implementations, strategies to accelerate the serial computations and parallel scalability, and numerical examples to demonstrate the effectiveness of the proposed strategies are presented.

Original languageEnglish
Pages (from-to)267-274
Number of pages8
JournalTransportation Research Procedia
Volume34
DOIs
Publication statusPublished - 2018
Externally publishedYes
Event6th International Symposium of Transport Simulation, ISTS 2018 and the 5th International Workshop on Traffic Data Collection and its Standardization, IWTDCS 2018 - Matsuyama, Japan
Duration: 2018 Aug 62018 Aug 8

Keywords

  • day-to-day traffic assignment
  • domain decomposition
  • high performance computing
  • post-disaster route guidance

ASJC Scopus subject areas

  • Transportation

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