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首页> 外文会议>The 2nd International Workshop on Artificial Intelligence and Mathematical Methods in Pavement and Geomechanical Systems, Aug 11-12, 2000, Newark, Delaware, USA >Formulation of a composite distress index for flexible pavements using genetic algorithms
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Formulation of a composite distress index for flexible pavements using genetic algorithms

机译：使用遗传算法制定柔性路面的复合遇险指标

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摘要

A generalized procedure for the formulation of Pavement Distress Index (PDI) is presented in this paper. Based on the deduct-value (DV) concept in PAVER, this procedure formulates PDI as the maximum PDI value in a user-defined scale minus the Total Deduct Value (TDV), which is the sum of the product of each individual DV and its corresponding weight. These weights are then identified to be respectively related to their DV-percentages, i.e. DV over TDV, by a polynomial relationship, called weight-curve. As what the weight-curve captured is the rating behavior of pavement experts, it is found to be reasonably stable and less influencing upon PDI than individual DVs do. Therefore, the proposed procedure automated the PDI formulation process by fixing the weight-curve initially. It is adjusted using the newly determined DVs, only when the procedure fails to converge or the determined DVs are not satisfactory. Genetic Algorithms are employed throughout this process. Both weight-curve and individual DVs are determined by minimizing the squared errors between user-rated PDIs and that produced by the proposed formulation, i.e. using the weight-curve and DVs. Simulated data from PAVER is first used to establish this process, and then actual data from one State Department of Transportation is used for validation purpose. The proposed methodology caters user-defined PDI scales, distress definitions, and helps determine DVs for individual distress, so that user-rated PDI will be reproduced when similar pavement condition happens. It will greatly facilitate the formulation of the PDI for any
机译：本文介绍了制定路面遇险指数（PDI）的通用程序。基于PAVER中的扣除值（DV）概念，此过程将PDI公式化为用户定义的比例中的最大PDI值减去总扣除值（TDV），该值是每个DV及其乘积的乘积之和。相应的重量。然后，通过称为权重曲线的多项式关系，将这些权重标识为分别与它们的DV百分比相关，即DV超过TDV。由于捕获的重量曲线是路面专家的评级行为，因此它被发现是相当稳定的，并且对PDI的影响小于单个DV。因此，建议的程序通过最初固定重量曲线来自动化PDI配制过程。仅当过程无法收敛或确定的DV不令人满意时，才使用新确定的DV对其进行调整。在整个过程中都采用了遗传算法。权重曲线和单个DV都是通过最小化用户评估的PDI与拟议公式产生的误差之间的平方误差来确定的，即使用权重曲线和DV。首先使用来自PAVER的模拟数据来建立此过程，然后将来自一个州交通部的实际数据用于验证目的。所提出的方法可以迎合用户定义的PDI比例，遇险定义，并帮助确定各个遇险情况的DV，以便在发生类似的路面情况时可以重现用户评级的PDI。这将极大地方便任何人制定PDI

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