Modeling vehicle traffic loads by the 2D compound Poisson process
Yang Liu,
Deru Li,
Yingqiu Li and
Haiping Zhang
Applied Stochastic Models in Business and Industry, 2018, vol. 34, issue 5, 607-617
Abstract:
Vehicular loads are an important factor in the fatigue and deterioration of bridges. In this paper, using weight‐in‐motion data from the Nanxi Yangtze river bridge, we propose a novel two‐dimensional (2D) compound Poisson process model of vehicle loads. This model considers the relations between vehicle loads, including vehicle speed and weight, whereby the relationships between these two marginal processes are described by a 2D Lévy copula function. Vehicle loads simulated by the proposed model were then compared with measured vehicle loads. The results show that histograms for vehicle loads simulated by the proposed model are similar to those generated for the measured vehicle loads. Moreover, the theoretical probabilities of vehicle loads are close in value to the empirical probabilities of vehicle loads. In addition, a two‐sample Kolmogorov‐Smirnov test at the significance level of 1% is given, which yields asymptotic p‐values of 3.2966 × 10−4 for vehicle speed and 3.0489 × 10−10 for vehicle weight. These values confirm that the proposed 2D compound Poisson process model is suitable for estimating vehicle loads.
Date: 2018
References: Add references at CitEc
Citations:
Downloads: (external link)
https://doi.org/10.1002/asmb.2344
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:wly:apsmbi:v:34:y:2018:i:5:p:607-617
Access Statistics for this article
More articles in Applied Stochastic Models in Business and Industry from John Wiley & Sons
Bibliographic data for series maintained by Wiley Content Delivery ().