Preliminary Highway Design with Genetic Algorithms and Geographic Information Systems

A method that integrates geographic information systems (GIS) with genetic algorithms (GAs) for optimizing horizontal highway alignments between two given end points is presented in this article. The proposed approach can be used to optimize alignments in highly irregular geographic spaces. The resulting alignments are smooth and satisfy minimum-radius constraints, as required by highway design standards. The objective function in the proposed model considers land-acquisition cost, environmental impacts such as wetlands and flood plains, length-dependent costs (which are proportional to the alignment length), and user costs. A numerical example based on a real map is employed to demonstrate application of the proposed model to the preliminary design of horizontal alignments.     

Ambient vibration testing and updating of the finite element model of a simply supported beam bridge

An ambient vibration test on a concrete bridge constructed in 1971 and calibration of its finite element model are presented. The bridge is characterized by a system of post-tensioned and simply supported beams. The dynamic characteristics of the bridge, i.e. natural frequencies, mode shapes and damping ratios were computed from the ambient vibration tests by using the Eigensystem Realization Algorithm (ERA). Then, these characteristics were used to update the finite element model of the bridge by formulating an optimization problem and then using Genetic Algorithms (GA) to solve it. From the results of the ambient vibration test of this type of bridge, it is concluded that two-dimensional mode shapes exist: in the longitudinal and transverse; and these experimentally obtained dynamic characteristics were also achieved in the analytical model through updating. The application of GAs as optimization techniques showed great versatility to optimize any number and type of variables in the model.     

Hazard zoning of trunk highway slope disasters: a case study in northern Shaanxi,China

The fragile natural environment of the northern Shaanxi Province in China is susceptible to ambient conditions. Highway slope disasters and the frequent occurrence of highway hazards that different in type, possible outcomes, and scale by region cause severe adverse effects on the construction and operation of trunk highways in the province. Therefore, conducting hazard zoning of highway slope disasters is essential in order to mitigate and manage highway slope disasters and to analyze the distribution regularities of hazards in northern Shaanxi. In this study, a hazard assessment model based on the principle of disaster-causing factor superposition was established. Five hazard assessment indexes, namely terrain gradient, ravine density, annual average days with precipitation more than 25 mm, geotechnical types, and vegetation coverage, were selected to analyze the types of highway slope disasters and disaster-causing factors. The distribution of assessment indexes and the degree of the highway slope disaster hazard were presented using an assessment model and geographic information system (GIS). The hazard zoning of highway slope disasters in northern Shaanxi is classified into slight, moderate, and severe according to hazard characteristics and trunk highway network distribution. Results show that the hazard zoning of highway slope disasters in northern Shaanxi is consistent with the actual distribution.     

GIS技术在边坡植被防护中的应用

将地理信息系统应用于边坡植被护坡领域,以孝襄高速公路植被生态防护工程为例,将公路的走向、起讫地点、边坡特性、护坡方式、植被情况等在地图上显著地标注出来,形成一张包含所有与公路边坡植被防护情况有关的信息地图。     

燃气管道的结构补偿及状态监测系统设计

针对建筑地基沉降引发的建筑燃气管道变形、断裂,分析了问题产生的原因,提出了管件结构补偿措施。作为该措施的补充,设计了一种燃气管道状态自动监测系统。通过分布式数据采集技术和通信技术,实现燃气管道实时监测。     

Data-driven approach to solve vertical drain under time-dependent loading

Currently, the vertical drain consolidation problem is solved by numerous analytical solutions, such as time-dependent solutions and linear or parabolic radial drainage in the smear zone, and no artificial intelligence (AI) approach has been applied. Thus, in this study, a new hybrid model based on deep neural networks (DNNs), particle swarm optimization (PSO), and genetic algorithms (GAs) is proposed to solve this problem. The DNN can effectively simulate any sophisticated equation, and the PSO and GA can optimize the selected DNN and improve the performance of the prediction model. In the present study, analytical solutions to vertical drains in the literature are incorporated into the DNN–PSO and DNN–GA prediction models with three different radial drainage patterns in the smear zone under time-dependent loading. The verification performed with analytical solutions and measurements from three full-scale embankment tests revealed promising applications of the proposed approach.     

Feasibility of Computer Visualization in Highway Development: A Fuzzy Logic-Based Approach

Abstract:   Building transportation infrastructure requires careful planning and design with due consideration to land and environmental impacts. Imprecise assessments of detailed design requirements, and land and environmental impacts lead to frequent scope changes of transportation infrastructure improvement projects. Computer visualization (CV) and geographic information systems (GIS) can greatly assist in understanding the detailed design requirements as well as land and environmental impacts. However, the application of CV is quite limited in transportation primarily because of the limited knowledge of its benefits over cost. This study investigates the feasibility of CV in modeling highway improvement sections. Two potential benefits are realized through the proposed modeling: (1) better representation of future improvements resulting in enhanced public and political support and (2) early identification of adverse environmental and land impacts as well as detail design requirements resulting in fewer scope changes. A fuzzy logic-based general approach is proposed to calculate the expected benefits of CV. A computer code called the Projection Option Processor (POP) is developed in Microstation's BASIC language to automate repetitive tasks in the visualization procedure. Two real highway projects from Maryland are visualized and the benefits and costs of the visualization are estimated using the proposed fuzzy logic-based approach. The results indicate that using POP is cost-effective resulting in higher benefit-cost ratios (B/C). Increasing the number of views, alternatives, and reevaluations for visualization may increase the total visualization cost significantly.     

Performance of global optimization models for dynamic site layout planning of construction projects

Dynamic construction site layout planning is a complex optimization problem that is characterized by nonlinear objectives and constraints, which impose great challenges in obtaining global and feasible solutions. This paper presents and compares between two global optimization models of dynamic site layout planning that were developed to overcome the limitation of previous models in the literature. The first model utilizes Genetic Algorithms (GA) while the second model utilizes Approximate Dynamic Programming (ADP). The performance of these two optimization models is analyzed in terms of the effectiveness of reaching optimum solutions and the efficiency of reducing the computational time. This analysis is performed using a designed set of problems of dynamic site layout planning with changing size and complexity. It was found that ADP outperformed GAs in terms of effectiveness and efficiency. However, GAs still prove to be a viable optimization tool because of its simplicity and multi-objective optimization capabilities.     

A Customized Particle Swarm Method to Solve Highway Alignment Optimization Problem

Abstract: Optimizing highway alignment requires a versatile set of cost functions and an efficient search method to achieve the best design. Because of numerous highway design considerations, this issue is classified as a constrained problem. Moreover, because of the infinite number of possible solutions for the problem and the continuous search space, highway alignment optimization is a complex problem. In this study, a customized particle swarm optimization algorithm was used to search for a near‐optimal highway alignment, which is a compound of several tangents, consisting of circular (for horizontal design) and parabolic (for vertical alignment) curves. The selected highway alignment should meet the constraints of highway design while minimizing total cost as the objective function. The model uses geographical information system (GIS) maps as an efficient and fast way to calculate right‐of‐way costs, earthwork costs, and any other spatial information and constraints that should be implemented in the design process. The efficiency of the algorithm was verified through a case study using an artificial map as the study region. Finally, we applied the algorithm to a real‐world example and the results were compared with the alignment found by traditional methods.     

Intersection Modeling for Highway Alignment Optimization

Abstract:   When optimizing a highway alignment, it is desirable to consider new and modified intersections along it. This article develops methods for locally optimizing intersections within highway alignment optimization processes. Design and operational characteristics for intersections are reviewed from the literature. The formulation considers the major costs that are sensitive to intersection characteristics. Genetic algorithms are used for optimal search. The proposed methods are implemented on an artificial study area and on a real one through the use of geographic information systems. The results show how the methods work for local optimization of intersections as well as for optimizing entire alignments. These methods can be used for improving search flexibility, thus allowing more effective intersections. They also provide a basis for extending the alignment optimization from single highways to networks .     

基于时空大数据的公路工程信息化技术框架 ——以铺前跨海大桥为例

以空天地一体化为代表的时空大 数据结合了GIS、遥感、倾斜摄影、BIM和物 联网等技术,是公路信息化发展的重要动 力。本文阐述了由地理建模、地理设计、地理 监测及地理控制组成的时空大数据技术架 构,提出了地理信息、BIM和倾斜摄影等关 键技术,并介绍了基于BIM的公路信息化技 术在海南文昌铺前跨海大桥的设计和施工中 实际应用的经验和思考,揭示了将BIM和GIS 结合的技术应用于我国桥梁设计和施工领域 的优势,为以后进一步结合遥感、倾斜摄影 等先进技术,促进公路信息化技术和应用的 进一步发展奠定基础。     

基于ArcIMS的公路地质灾害信息远程查询系统

为实现公路地质灾害信息网络浏览和远程查询,系统以ArcSDE和Oracle数据库管理系统标准数据、灾害空间地理数据和灾害一般属性数据,建立系统服务器端的核心数据库,以ArcIMS为平台结合JSP、Severlet、JavaBean、ArcSDE等综合技术进行公路地质灾害信息的WebGIS开发。在Struts框架的基础上,建立远程公路地质灾害信息管理系统。实现了崩塌、滑坡、泥石流等灾害空间信息的网络发布,提供了基于GIS的地质灾害信息远程查询平台,用户可以在互联网终端检索有关公路地质灾害文字、图片等形式的一般属性数据、空间地理信息和灾害监测数据,为及时了解公路地质灾害的发生、发展、降低地质灾害造成的损失和整治灾害提供有效地手段。     

基于GIS+BIM信息协同的景观参数化 设计研究——以山地风景环境道路规划设计 实验为例

构建GIS、BIM协同的景观信息模型是实现精准化 景观规划的有效途径。以山地风景环境道路为对象,提出集成 地理信息系统(GIS)和建筑信息模型(BIM)的山地道路选线分 析与交互设计方法,实现GIS数据关联BIM模型,构建以地理 空间环境信息为基础的BIM景观信息模型,从而提升规划设 计精细化程度与精准化水平,以期为景观规划、设计、建设、 管理、运维提供信息支撑与决策参考。     

基于PSO-BP算法的隧道非线性位移分析模型

粒子群优化(PSO)算法是近年来发展迅速,并得到广泛应用的一种仿生全局最优化算法.与遗传算法相比,该算法具有操作简单、易于编程的优点.结合铜黄高速公路汤屯段大田连拱隧道施工,采用PSO算法对BP神经网络的权值进行自动优化,获得训练效果最好的BP网络模型参数以提高网络的泛化能力,建立起基于PSO-BP算法的大田隧道施工位移非线性智能分析模型,并采用此模型对后续施工隧道变形进行了预测分析.与实测位移对比表明,本文建立的PSO-BP模型平均预测相对误差仅为3.1%,可很好地作为隧道信息化施工的一种辅助方法,并为其他类似岩土工程提供借鉴.     

A GIS-Based Traffic Signal Coordination and Information Management System

Abstract: This paper discusses research conducted at the Georgia Institute of Technology that investigated the use of geographic information system (GIS) technology as a tool in traffic signal information management and signalized intersection coordination. TRANSYT-7F is the most widely used and respected computer model for optimizing the coordination of traffic signals. Unfortunately, creating an optimal TRANSYT-7F model is very costly. The hypothesis of this research was that using a specialized GIS in conjunction with TRANSYT-7F could enhance the process of coordinating a traffic signal system. The research resulted in the development of a GIS-based traffic signal coordination and information system that operates on a microcomputer. This system is an improvement over existing TRANSYT-7F models because relationships between intersections do not have to be encoded manually. Instead, the system takes advantage of the GIS's topologic data structure, which provides these relationships. The process of analyzing different network optimization scenarios is simplified with this system because the user need only to select intersections to be coordinated from the GIS graphic display rather than cutting and pasting from existing input files. Alternatively, the system can serve as a multipurpose signal information system and play a vital role in decision support. It can provide improved access to signal data and allows for swift identification of intersections that experience excessive delays or unacceptable levels of service.     

Prescreening and Repairing in a Genetic Algorithm for Highway Alignment Optimization

Abstract:   The method of handling infeasible solutions in an evolutionary search algorithm [e.g., genetic algorithms (GAs)] is crucial to the effectiveness of the solution search process. This problem arises because solution search steps, techniques, and operators used in GAs (such as reproduction, mutation, and recombination) are normally  " blind " to the constraints, and thus GAs can generate solutions that do not satisfy the requirements of the problems. In GA-based highway alignment optimization (HAO), many infeasible solutions, which violate model constraints, are also possibly generated, and evaluation of such solutions is wasteful. This study focuses on ways to avoid wasting computation time on evaluating infeasible solutions generated from the GA-based HAO, and develops a prescreening and repairing (P&R) method for an efficient search of highway alignments. The key idea of the P&R method is to repair (before the very detailed alignment evaluation) any candidate alignments whose violations of design constraints can be fixed with reasonable modifications. However, infeasible alignments whose violations of constraints are too severe to repair are discarded (prescreened) before any detailed evaluation procedure is applied. The proposed P&R method is simple, but significantly improves computation time and solution quality in the GA-based HAO process. Such improvements are demonstrated with a test example for a real road project. Through the example study, it is shown that the model incorporating the P&R method can find a good solution much faster (by approximately 23%) than the model with the conventional penalty method. In addition, the P&R method allows the model to evaluate about 70% more solutions than that it can evaluate with the penalty method for the same number of generations.     

Regional water quality management for the Karun–Dez River basin, Iran

To achieve water quality goals in a river basin, a water quality management model (WQMM) has been developed through the geographic information system (GIS) approach and a mathematical water quality model. The developed model has been applied to the Karun and Dez Rivers, where water quality has decreased due to heavy pollutant loads from Khuzestan province cities and surrounding areas. Pollution sources, land use, geographic features and measured water quality data of the river basin were incorporated into the Arc‐View GIS database. With the database, the management model calculated management type and management cost for each management project in the river basin. Until now, river management policy for polluted rivers in Iran first penalizes pollution sources and then constructs treatment plants for the pollution sources whose wastewater is released untreated and for which the wastewater quality goal of the Iranian Department of Environment is not met. Different management projects with a time programme were proposed and they were compared with the results of the river quality without any management approach. It became clear that the results based on the management approach were much better than those for the unmanaged condition from the viewpoint of the achievement of water quality goals and cost optimization.     

Neural network model incorporating a genetic algorithm in estimating construction costs

This paper applies the back-propagation network (BPN) model incorporating genetic algorithms (GAs) to cost estimation. GAs were adopted in the BPN to determine the BPN's parameters and to improve the accuracy of construction cost estimation. Previously, there have been no appropriate rules to determine these parameters. The construction cost data for 530 residential buildings constructed in Korea between 1997 and 2000 were used for training and evaluating the performance of the model. This study showed that a BPN model incorporating a GA was more effective and accurate in estimating construction costs than the BPN model using trial and error.     

基于GIS的公路安全信息管理系统研究及应用

利用GIS技术手段建立了唐山市道路信息电子数据库和道路网络,在Visual Stidio2008平台基础上,进行Web GIS唐山市公路安全信息管理系统的开发,实现了集城市公路安全评价决策分析、交通事故影响范围缓冲分析、交通事故紧急救援最佳路径分析等功能于一体的数字化公路安全信息管理系统。