基于GIS的高速公路路面管理智能决策模型研究
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摘要
近年来高速公路交通量大幅度增加,在过重的交通荷载和自然环境的综合作用下,公路病害尤其是路面病害日益增多,而路面管理工作是路网养护管理中核心内容。但是目前我国公路养护管理事业总体上还处于较低的发展水平,现代信息技术等高新技术的集成与应用比较薄弱,高速公路养护管理部门采用的传统管理手段与养护需求之间的矛盾日益突出,提高高速公路养护管理的科学化、信息化与智能化成为交通部门的一个重要课题。
本文以路面管理为目的,在道路工程学和管理科学理论的基础上,以高速公路养护管理决策为主要研究对象,采用现场调研与数值计算相结合的综合研究手段,并运用了现代数学理论、地理信息理论以及人工智能等先进技术,以GIS技术为开发平台,通过系统分析的方法构建既能交互式运行又有自适应能力的决策管理模型,可为路面管理决策者进行路面使用性能评价与预测,并在预定的标准和约束条件下合理确定多目标的路面管理决策优化方案,促使路面管理过程系统化,用以满足现代化、大规模和高质量的路面养护要求,这对于高速公路运营和社会经济的可持续发展都具有很重要的理论和现实意义。本文主要研究内容有：
1.阐述了论文研究的背景及研究意义,全面分析了国内外路面管理系统的内涵、组成和发展现状,并对目前国内路面管理系统研究动态进行剖析和对比,确定本文的研究思路和方向。
2.通过研究国内外高速公路路面养护管理模式和业务需求的现状,提出以GIS技术为平台的养护管理总体设计,根据高速公路养护管理部门的操作业务流程,制定了系统的数据处理流程和功能组成,并设计了系统的总体框架和混合模式的网络结构模型,确定了系统部署方案和原则。
3.根据养护管理数据需求分析,确定了养护管理空间数据库和属性数据库的主要内容,设计高速公路数据采集的录入标准,外业数据包括路面破损、路面弯沉、路面平整度、抗滑性能、交通量等,内业数据有路面结构类型、路段编码、路面维修历史数据等。通过动态分段技术实现对公路空间数据和属性数据的有效关联,实现适合于高速公路养护管理的GIS数据库管理。
4.路面状况评价是路面管理系统的必要的功能模块,是进行路况预测、优化对策的基础。以沥青混凝土路面养护实际检测中经常采用和易于仪器测量的路面破损状况、行驶质量、强度及安全四个单项评价为基础,针对影响路面性能的不确定因素,提出符合高速公路养护管理实际工作需求的基于模糊神经网络的路面使用性能综合评价模型。
5.针对影响路面性能的主要因素进行分析,根据当前高速公路大多数运营时间较长的实际情况,通过对数据库中的历史数据进行训练、测试,建立可以自学习、自适应的BP神经网络模型的路面性能预测模型,为跨年度的道路养护资金需求提供参考。
6.路面的养护决策优化是整个路面养护管理系统的核心,在研究养护决策优化和多目标优化的基础上,针对传统数学规划方法进行的高速公路路面养护决策优化运行效率较低和难以实际运用的不足,建立带约束条件的多目标离散PSO养护决策模型,通过各个粒子在解空间追随最优的粒子进行搜索优化,从而得到在养护资金等多个约束条件下的全局最优养护方案Pareto解,解决了大规模复杂路网的管理策略优化的问题,以实现养护管理决策的智能化。
Highway traffic has increased substantially in recent years, because the heavy traffic loads and the effect of the natural environment, especially the pavement diseases is increasing, resulting in a significant increase in road maintenance work. But at present our country highway maintenance management career in general is still at a low level of development, the integration and application of modern information technology is relatively weak, the traditional means of management and maintenance needs of the contradiction between the increasingly prominent. In order to improve highway scientific management, information and intelligence technology becomes an important subject in transportation department.
Based on the pavement management for the purpose, in road engineering and the management science theory, it carries out expressway maintenance management decision as the main research object, using the field investigation and numerical calculation combined with comprehensive research methods, and the use of modern mathematics theory, geographic information theory and artificial intelligence technology. It used GIS technology as the development platform, to build adaptive capacity and interactive multi-objective decision maintenance management system. It can meet the modern, large-scale and high quality of road maintenance requirements for road pavement performance evaluation and prediction, a reasonable allocation of funds determine the road maintenance program, provides intelligent multi-objective optimization decision management, which for highway operations and more sustainable and economic development has important theoretical and practical significance. This article mainly research content has:
1. Paper describes the background to the study and research significance, through understand the development of pavement maintenance management system status, and through dynamic analysis and comparison about the current pavement management system determine the ideas and directions of this paper.
2. By studying highway pavement maintenance management and business needs of the present situation. GIS technology as a platform for the conservation management of the overall design, according to expressway maintenance management business processes, developed a system of data processing processes and functions composition, and designed of the system's software framework and mixed-mode network structure model to determine the system deployment plan and principles.
3. According to maintenance and management data needs analysis, it determines the maintenance management system of the main content of spatial database and attribute database. To design highway data collection criteria, field data include pavement breakage, pavement deflection, smoothness of pavement, skid resistance, traffic, etc., industry data are pavement types, road of code and road maintenance history data. Through dynamic segmentation technology, road space data and attribute data associated with, it effective achieved highway maintenance management of the GIS database.
4. Pavement condition evaluation is a necessary function module of pavement management system, is the basis for traffic forecast and optimization strategies.To asphalt concrete pavement maintenance, we often test four evaluations, there are pavement damage condition, ride quality, strength and safety. For the uncertain factors affecting the performance of the road, accord with the actual demand it put forward based on fuzzy neural network model for comprehensive evaluation of pavement performance.
5. By analysis the main factors affecting road performance, based on the current most of highway the actual situation, through the historical data in the database for training and testing, it established self-learning, adaptive BP neural network model of the pavement performance prediction model for multi-year road maintenance funding needs to provide reference.
6. Pavement maintenance decision optimization is the core of the whole pavement maintenance management system, based on maintenance decision optimization and multi objective optimization study, the traditional mathematical programming method has low efficiency and difficult to use insufficient for expressway pavement maintenance decision optimization. It established multi-objective constrained discrete PSO maintenance decision model, each particle in the solution space by following the optimal particle search optimization, to obtain optimal maintenance scheme of Pareto solution in maintenance funds and other multiple constraints. It solved the large-scale and complex road network management strategy optimization problems, to realize the intelligent maintenance management decision.
本文以路面管理为目的,在道路工程学和管理科学理论的基础上,以高速公路养护管理决策为主要研究对象,采用现场调研与数值计算相结合的综合研究手段,并运用了现代数学理论、地理信息理论以及人工智能等先进技术,以GIS技术为开发平台,通过系统分析的方法构建既能交互式运行又有自适应能力的决策管理模型,可为路面管理决策者进行路面使用性能评价与预测,并在预定的标准和约束条件下合理确定多目标的路面管理决策优化方案,促使路面管理过程系统化,用以满足现代化、大规模和高质量的路面养护要求,这对于高速公路运营和社会经济的可持续发展都具有很重要的理论和现实意义。本文主要研究内容有：
1.阐述了论文研究的背景及研究意义,全面分析了国内外路面管理系统的内涵、组成和发展现状,并对目前国内路面管理系统研究动态进行剖析和对比,确定本文的研究思路和方向。
2.通过研究国内外高速公路路面养护管理模式和业务需求的现状,提出以GIS技术为平台的养护管理总体设计,根据高速公路养护管理部门的操作业务流程,制定了系统的数据处理流程和功能组成,并设计了系统的总体框架和混合模式的网络结构模型,确定了系统部署方案和原则。
3.根据养护管理数据需求分析,确定了养护管理空间数据库和属性数据库的主要内容,设计高速公路数据采集的录入标准,外业数据包括路面破损、路面弯沉、路面平整度、抗滑性能、交通量等,内业数据有路面结构类型、路段编码、路面维修历史数据等。通过动态分段技术实现对公路空间数据和属性数据的有效关联,实现适合于高速公路养护管理的GIS数据库管理。
4.路面状况评价是路面管理系统的必要的功能模块,是进行路况预测、优化对策的基础。以沥青混凝土路面养护实际检测中经常采用和易于仪器测量的路面破损状况、行驶质量、强度及安全四个单项评价为基础,针对影响路面性能的不确定因素,提出符合高速公路养护管理实际工作需求的基于模糊神经网络的路面使用性能综合评价模型。
5.针对影响路面性能的主要因素进行分析,根据当前高速公路大多数运营时间较长的实际情况,通过对数据库中的历史数据进行训练、测试,建立可以自学习、自适应的BP神经网络模型的路面性能预测模型,为跨年度的道路养护资金需求提供参考。
6.路面的养护决策优化是整个路面养护管理系统的核心,在研究养护决策优化和多目标优化的基础上,针对传统数学规划方法进行的高速公路路面养护决策优化运行效率较低和难以实际运用的不足,建立带约束条件的多目标离散PSO养护决策模型,通过各个粒子在解空间追随最优的粒子进行搜索优化,从而得到在养护资金等多个约束条件下的全局最优养护方案Pareto解,解决了大规模复杂路网的管理策略优化的问题,以实现养护管理决策的智能化。
Highway traffic has increased substantially in recent years, because the heavy traffic loads and the effect of the natural environment, especially the pavement diseases is increasing, resulting in a significant increase in road maintenance work. But at present our country highway maintenance management career in general is still at a low level of development, the integration and application of modern information technology is relatively weak, the traditional means of management and maintenance needs of the contradiction between the increasingly prominent. In order to improve highway scientific management, information and intelligence technology becomes an important subject in transportation department.
Based on the pavement management for the purpose, in road engineering and the management science theory, it carries out expressway maintenance management decision as the main research object, using the field investigation and numerical calculation combined with comprehensive research methods, and the use of modern mathematics theory, geographic information theory and artificial intelligence technology. It used GIS technology as the development platform, to build adaptive capacity and interactive multi-objective decision maintenance management system. It can meet the modern, large-scale and high quality of road maintenance requirements for road pavement performance evaluation and prediction, a reasonable allocation of funds determine the road maintenance program, provides intelligent multi-objective optimization decision management, which for highway operations and more sustainable and economic development has important theoretical and practical significance. This article mainly research content has:
1. Paper describes the background to the study and research significance, through understand the development of pavement maintenance management system status, and through dynamic analysis and comparison about the current pavement management system determine the ideas and directions of this paper.
2. By studying highway pavement maintenance management and business needs of the present situation. GIS technology as a platform for the conservation management of the overall design, according to expressway maintenance management business processes, developed a system of data processing processes and functions composition, and designed of the system's software framework and mixed-mode network structure model to determine the system deployment plan and principles.
3. According to maintenance and management data needs analysis, it determines the maintenance management system of the main content of spatial database and attribute database. To design highway data collection criteria, field data include pavement breakage, pavement deflection, smoothness of pavement, skid resistance, traffic, etc., industry data are pavement types, road of code and road maintenance history data. Through dynamic segmentation technology, road space data and attribute data associated with, it effective achieved highway maintenance management of the GIS database.
4. Pavement condition evaluation is a necessary function module of pavement management system, is the basis for traffic forecast and optimization strategies.To asphalt concrete pavement maintenance, we often test four evaluations, there are pavement damage condition, ride quality, strength and safety. For the uncertain factors affecting the performance of the road, accord with the actual demand it put forward based on fuzzy neural network model for comprehensive evaluation of pavement performance.
5. By analysis the main factors affecting road performance, based on the current most of highway the actual situation, through the historical data in the database for training and testing, it established self-learning, adaptive BP neural network model of the pavement performance prediction model for multi-year road maintenance funding needs to provide reference.
6. Pavement maintenance decision optimization is the core of the whole pavement maintenance management system, based on maintenance decision optimization and multi objective optimization study, the traditional mathematical programming method has low efficiency and difficult to use insufficient for expressway pavement maintenance decision optimization. It established multi-objective constrained discrete PSO maintenance decision model, each particle in the solution space by following the optimal particle search optimization, to obtain optimal maintenance scheme of Pareto solution in maintenance funds and other multiple constraints. It solved the large-scale and complex road network management strategy optimization problems, to realize the intelligent maintenance management decision.
引文
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