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Home > Archive>Volume 45, Issue 07, 2017 >0941-0947. DOI:10.11908/j.issn.0253-374x.2017.07.001
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Traffic Flow Generation and Load Simulation of Bridges Based on Multicell Cellular Automaton
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    Abstract:

    The simulation of random traffic load is the foundation and crux of load assessment and performance evaluation of bridges. The current traffic simulation based on the Monte Carlo method is inappropriate for describing the dynamic evolution of traffic on microscopic scales within a relatively long span, while the singlecell method based on cellular automaton (CA) remains to be improved concerning precision. In the singlecell method, a car is simulated by a single cell, which could not consider the influence of axle load and exerts a limit on enhancement of simulation precision. In this paper, based on the current CA, a model is proposed to simulate an axle by a cell and to simulate a car by a number of consecutive cells, which is defined as multicell cellular automaton (MCA). It verifies the mathematical model with realistic traffic and its load data. It is demonstrated that the parameters of traffic flow and traffic load, such as traffic volume, time headway, velocity and weight of simulated traffic are reproduced accurately by the multicell method. With the distribution load, bearing shear and midspan moment in a simply supported girder with a length of 1 000 meters set as indexes respectively, the statistics analysis of the load response characteristics of simulated and realistic data is conducted. The result indicates that the relative errors of simulated data of the MCA model to realistic data are within 5%. When MCA is applied, the precision of load response can be increased from the correlated error of less than 17% in the traditional singlecell method to a relatively high precision.

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RUAN Xin, JIN Zeren, ZHOU Junyong, TU Huizhao. Traffic Flow Generation and Load Simulation of Bridges Based on Multicell Cellular Automaton[J].同济大学学报(自然科学版),2017,45(07):0941~0947

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History
  • Received:October 09,2016
  • Revised:May 05,2017
  • Adopted:February 08,2017
  • Online: July 20,2017
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