A Markov‐Based Road Maintenance Optimization Model Considering User Costs

User costs of different maintenance actions need to be assessed in road maintenance as well as the maintenance costs. The vehicle operating cost (VOC) and the travel delay cost are two major components of the user costs associated with road maintenance actions. This article simplifies the general calculation models of these two user cost components and develops a multiobjective Markov‐based model to minimize both maintenance cost and user cost subject to a number of constraints including the average annual budget limit and the performance requirement. The road deterioration process is modeled as a discrete‐time Markov process, the states of road performance are defined in terms of the road roughness, and the state transition probabilities are estimated considering the effects of deterioration and maintenance actions. An example is provided to illustrate the use of the proposed road maintenance optimization model. The results show that the optimal road maintenance plan obtained from the model is practical to implement and is cost‐effective compared with the periodical road maintenance plan. The results also indicate that the maintenance cost and the user cost are competitive. When maintenance works are carried out more frequently, the life‐cycle maintenance costs will increase while the life‐cycle user costs will decrease. This is because the VOC contributes the most amount of the user cost and its change has a contrary trend to the change of the maintenance cost over time.     

Network‐level scheduling of road construction projects considering user and business impacts

Construction projects are often associated with partial or full road closures, which result in user costs and community disruptions in terms of reduced business productivity. A number of studies have addressed the problem of scheduling construction projects based on a variety of stakeholder objectives. Yet still, there seems to exist a few gaps regarding (1) possible tradeoffs between road user cost reduction and business cost reduction associated with optimal scheduling, (2) role of the project type (rehabilitation and capacity expansion) on the solution methodology, and (3) lack of solution algorithm to address the problem complexity by deriving the optimal solution. In addressing these gaps, this article adopts a novel approach for developing an optimal project schedule for multiple road projects within a construction horizon. The goal is to minimize the overall cost of the projects to road users and adjacent businesses over the construction horizon. The project scheduling problem is formulated as a mixed‐integer nonlinear program. We solve the problem using a local decomposition method. The methodology is demonstrated using the Sioux Falls city network with two project types: capacity expansion and rehabilitation. The results of the numerical experiment suggest that (1) the solution algorithm converges to optimal solution in finite iterations and (2) a network‐wide scheduling of urban road projects using explicit optimization can yield a significant reduction in business disruption costs while incurring a relatively smaller increase in system travel time, and overall, is superior to a schedule developed only considering the total system travel time.     

A sequential exploration algorithm for the design optimization of horizontal road alignment

Most computer-aided optimization procedures for horizontal alignment optimization of roads require the use of information such as horizontal points of intersection (PIs) to determine an alignment. In these methods, to obtain parameters such as the radius of the curve corresponding to a specific PI, the previous and next PIs must be known. In this paper, a sequential exploration algorithm (SEA) is proposed, and the algorithm continuously explores the entire optimization space through certain steps. Only the parameters of the previous node are required to determine the current node's parameters during the exploration process, avoiding the tight coupling between PIs in traditional optimization algorithms. Furthermore, the proposed SEA does not require assumptions about the positions and numbers of the PIs, and it can design near-optimal road alignments that match geometric restrictions and automatically take transition curves into account. Another feature of the proposed algorithm is that it directly optimizes the geometric element parameters based on the actual milepost, and it is a fully collaborative optimization approach that does not require secondary optimization nesting during the optimization process. Analyses comparing the optimization effects of different algorithms are performed on a numerical case, that is, a problem of avoiding obstacles, and two actual cases from the literature, that is, a new road design problem and an existing road reconstruction problem. It is discovered that the proposed SEA results in an approximately 3% to 10% improvement in optimization effects when compared to two current cutting-edge optimization algorithms. This work offers a new perspective on road alignment optimization by merging discrete and continuous optimizations, with a discrete component handling optimization accuracy and a continuous component handling real optimization.     

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.     

A Polynomial Parametric Curve (PPC‐CURVE) for the Design of Horizontal Geometry of Highways

Abstract: The use of transition curves in the road design is a solution to make the gradual evolution of curvature and, at the same time, to improve the comfort level of drivers and provide a good visual perception of the curve. Clothoid is the most widely used transition curve in road design so far, because it ensures the continuity of the curvature with the other geometric elements of the alignment. However, several researches allow the use of polynomial functions as an alternative to the clothoid. Such use is permitted in accordance with the verification of allowable vehicle–road dynamics. Polynomial solutions of transition curves can be a valuable alternative for the traditional solutions (first transition curve, circular arc, second transition curve). A fifth‐degree polynomial parametric curve (PPC‐curve) for the design of highway alignment is proposed in this article. An analysis of the theoretical aspects to solve more complex geometrical problems recurring in practical highway geometric design is carried out. With regard to this problem, a shape parameter giving flexibility to the polynomial solution in relation to project needs has also been introduced. To implement the procedure, an original computer program has been developed. Numerical applications have been performed for comparison with the traditional solutions.     

A Hybrid Branch‐and‐Bound and Benders Decomposition Algorithm for the Network Design Problem

Given a set of candidate road projects associated with costs, finding the best subset with respect to a limited budget is known as the network design problem (NDP). The NDP is often cast in a bilevel programming problem which is known to be NP‐hard. In this study, we tackle a special case of the NDP where the decision variables are integers. A variety of exact solutions has been proposed for the discrete NDP, but due to the combinatorial complexity, the literature has yet to address the problem for large‐size networks, and accounting for the multimodal and multiclass traffic flows. To this end, the bilevel problem is solved by branch‐and‐bound. At each node of the search tree, a valid lower bound based on system optimal (SO) traffic flow is calculated. The SO traffic flow is formulated as a mixed integer, non‐linear programming (MINLP) problem for which the Benders decomposition method is used. The algorithm is coded on a hybrid and synchronized platform consisting of MATLAB (optimization engine), EMME 3 (transport planning module), MS Access (database), and MS Excel (user interface). The proposed methodology is applied to three examples including Gao's network, the Sioux‐Falls network, and a real size network representing the city of Winnipeg, Canada. Numerical tests on the network of Winnipeg at various budget levels have shown promising results.     

A Computational Methodology for Assessing the Time‐Dependent Structural Performance of Electric Road Infrastructures

An infrastructure adapted to dynamic wireless recharging of electric vehicles is often referred to generically as Electric Road (“e‐road”). E‐roads are deemed to become essential components of future grid environments and smart city strategies. Several technologies already exist that propose different ways to integrate dynamic inductive charging systems within the infrastructure. One e‐road solution uses a very thin rail with box‐section made of fibre‐reinforced polymer, inside which an electric current flows producing a magnetic field. In spite of the great interest and research generated by recharging technologies, the structural problems of e‐roads, including vibrations and structural integrity in the short and/or long period, have received relatively little attention to date. This article presents a novel computational methodology for assessing the time‐dependent structural performance of e‐roads, including a recursive strategy for the estimation of the lifetime of surface layers. The article also reports some numerical findings about e‐roads that will drive further numerical analyses and experimental studies on this novel type of infrastructure. Finally, numerical simulations have been conducted to compare an e‐road with a traditional road (“t‐road”), in terms of static, dynamic and fatigue behavior.     

Comparing Delay Minimization and Emissions Minimization in the Network Design Problem

Abstract: Traditionally, transportation road networks are designed for minimal congestion. Unfortunately, such approaches do not guarantee minimal vehicle emissions. To fill this apparent gap in network design research, an emissions network design problem and solution method is proposed in this article for the purposes of comparing to the traditional network design results. Three air pollutants are considered on two road networks. The model is formulated as a bi‐level optimization problem and a solution is approximated using a genetic algorithm. The influence of demand uncertainty is also incorporated into the model. Designing for minimal congestion tends to increase emissions of criteria air pollutants. However, not adding capacity to a road network also increases emissions of pollutants. Therefore, an optimization problem and solution method, such as the emissions network design problem and solution method presented here, is useful for identifying capacity additions that reduce vehicle emissions. It is also useful for understanding the tradeoffs between designing a network for minimal congestion versus minimal vehicle emissions.     

Time‐Dependent Discrete Network Design Frameworks Considering Land Use

Abstract: This article proposes optimization frameworks for discrete road network design considering the land‐use transport interaction over time. Unlike existing models, the optimization frameworks can determine the optimal designs automatically without trial‐and‐error once the objective(s) is/are clearly defined. Moreover, these frameworks allow the evaluation of the impacts of the optimal designs on the related parties including landowners, toll road operators, transit operators, and road users, and help network planners and profit‐makers with decision making by eliminating many alternative designs. A numerical study is set up to examine road network design's effects on these related parties under three road construction schemes: exact cost recovery, build‐operate‐transfer, and cross‐subsidization. The results show that the changes in landowner profits are not the same after implementing any scheme. These unequal changes raise the issue of the landowner equity. This implies that the government has to consider trade‐offs between parties’ objectives carefully.     

A bi‐level model to optimize road networks for a mixture of manual and automated driving: An evolutionary local search algorithm

This paper presents a bi‐level model to optimize automated‐vehicle‐friendly subnetworks in urban road networks and an efficient algorithm to solve the model, which is relevant for the transition period with vehicles of different automation levels. We formulate the problem as a network design problem, define solution requirements, present an effective solution method that meets those requirements, and compare its performance with two other solution algorithms. Numerical examples for network of Delft are presented to demonstrate the concept and solution algorithm performances. Results indicate that our proposed solution outperforms competing ones in all criteria considered. Furthermore, our findings show that the optimal configuration of these subnetworks depends on the level of demand; lower penetration rates of automated vehicles call for less dense subnetworks, and thereby less investments. Nonetheless, a large proportion of benefits are already achievable with low‐density subnetworks. Denser subnetworks can deliver higher benefits with higher penetration rates.     

环境因素下城市交通离散网络设计问题中确定最大OD需求量的优化模型及求解算法

在考虑环境因素的情况下将广义备用能力的概念与城市交通离散网络设计问题结合在一起,一方面要求整个交通网络可以容纳的OD需求量与车辆尾气排放总量之差最大;另一方面,通过在交通网络中添加新的路段来提高整个交通网络的OD需求量。文中给出了环境因素下城市交通离散网络设计问题中确定最大OD需求量的优化模型。在分支定界思想的基础上设计了求解该模型的启发式算法。最后,通过简单的算例,说明该算法是可行并且有效的。     

Statistisch begründete Festigkeitskennwerte genieteter Bauteile – statische Festigkeit und Wöhlerlinienkatalog

Statistically founded strength values of riveted members – static strength and fatigue life classification of constructional details. The assessment of the load‐carrying capacity and of the remain‐ing fatigue life of existing railway and road bridges has gained an increasingly significant role over the last years. Thus, the problem of determining adequate strength values of riveted members of older steel bridges once again arose during the elaboration of the ONR 24008 specification. In the course of a research project initiated by the Austrian Federal Railways (ÖBB), results of static and fatigue tests carried out on riveted members were evaluated statistically. With regard to fatigue test data, a classification of riveted details with consideration of different constructional details proved to be sensible and to lead to more consistent S‐N design curves. Tables containing static strength values and a catalogue of S‐N design curves based on constructional detail classifications represent the result of the research project.     

Optimal maintenance strategies for bridge networks using the supply and demand approach

This paper presents a probability-based approach for optimising the management of bridge networks. Most of the Bridge Management Systems are focused on condition features to ensure a minimum safety level for each individual bridge. Their location on the road network, the consequences of inadequate service due to maintenance actions are therefore not taken into consideration. These multiple criteria should be considered when scheduling maintenance activities. To overcome these limitations, a probabilistic supply and demand strategy is proposed for determining the optimal maintenance planning for each interconnected bridge. The problem is solved with genetic algorithms. One objective function is first introduced, corresponding to the summation of all the maintenance, failure, and user costs. Then, two conflicting objective functions are considered, the total user costs and the maintenance and rehabilitation costs. Safety and serviceability aspects are taken into account in the methodology and the theoretical and numerical developments are applied on a part of the French national network.     

高速公路设计中降低工程造价的探讨

分析了山西省高速公路工程造价偏高的原因,指出公路勘察设计是公路建设过程中的重要环节,对于公路建设质量和工程投资起控制作用,从设计角度探讨了高速公路降低工程造价的措施,从而解决建设资金不足的问题。     

Neural Network–Spreadsheet Integration for Earth-Moving Operations

Abstract: This paper examines the potential to combine trained artificial neural networks with application development software to expand their applicability to construction management problems. The problem of determining optimal equipment combinations for the dozer/scraper earth-moving team, under various physical conditions of the haul road, was chosen for its limited scope and lack of effective solution methods currently available. An introduction to the problem provides the current state of technology for handling this problem. The problem is analyzed to determine the information and resource requirements as well as the input and output forms that would be desirable for such a program. The paper proceeds through the design process and development of the program schematic. Programming of the system is examined, including the development process used to train the neural network, conversion of the network to a spreadsheet form, and spreadsheet manipulation of the network outputs. The paper concludes with recommendations for expansion of the program for more complex haul road conditions and equipment types.     

Minimum‐weight design of high‐rise structures subjected to flexural vibration at a desired natural frequency

In this paper, a parametric approach for design of high‐rise structures subjected to flexural vibration is proposed. The optimization problem is formed based on a preselected value for the fundamental natural frequency, and it is formulated for minimum structural weight. In a two‐step approach, first, an alternative formulation aimed at maximizing structural stiffness that in turn maximizes structure's fundamental frequency is introduced. Then, optimized results are used in obtaining a closed‐form solution of the actual problem. Because the resulting equations are rather complicated, approximate forms are developed in order to simplify the design process. In all relations, contributions from shear forces to lateral displacement are assumed to be negligible; hence, bending resistance is the only design variable, and its optimal value is computable using simple relations. Two numerical examples are presented in order to illustrate the efficiency of this method in practice.     

Optimal drift design of tall reinforced concrete buildings with non‐linear cracking effects

This paper presents an efficient, computer‐based technique for the optimum drift design of tall reinforced concrete (RC) buildings including non‐linear cracking effects under service loads. The optimization process consists of two complementary parts: an iterative procedure for the non‐linear analysis of tall RC buildings and a numerical optimality criteria (OC) algorithm. The non‐linear response of tall RC buildings due to the effects of concrete cracking is obtained by a series of linear analyses, the so‐called direct effective stiffness method. In each linear analysis, cracked structural members are first identified and their stiffness modified based on a probability‐based effective stiffness relationship. Stiffness reduction coefficients are introduced as measures of the remaining stiffness for structural elements after cracking. A rigorously derived OC method is developed to solve for the minimum weight/cost design problem subject to multiple drift constraints and member sizing requirements. A shear wall‐frame example is presented to illustrate the application of this optimal design method. The design results of the optimized structure with cracking effects are compared to those of the linear‐elastic structure without concrete cracking. Copyright © 2005 John Wiley & Sons, Ltd.     

Lateral drift constrained structural optimization of an actual supertall building acted by wind load

Recent trends towards constructing taller and increasingly slender buildings imply that these structures are more sensitive to wind excitation. This paper presents a technique for the wind‐resistant optimal design of supertall buildings with a complex structural system including concrete‐filled steel tube columns, shear walls, and various types of beams and columns. In each optimal design cycle, the dynamic wind load acting on a building is transformed into a set of multiple‐oriented equivalent static wind loads, which converts the optimal design for a building acted by dynamic loads into a simpler optimal design problem that considers only static loads. The objective function and constraint functions are explicitly formulated for various types of frame and area members, and consequently, the optimal design problem is mathematically modeled. The optimality criteria method is employed to seek a solution to the optimal design problem. A 68‐story actual supertall building with a height of 303 m is considered for a case study. The obtained results show that the presented technique is capable of giving a good numerical optimal solution for practical use. The technique and results obtained from this study are valuable for academic and professional engineers involved in wind engineering and structural design.     

通风路基主要影响因素及应对措施研究

 结合实测资料,通过模拟计算从传热角度就通风路基降温效能的主要影响因素进行分析。研究发现,在管道通风路基中,管间土体存在较强的热流向下传热,通风管间距是影响降温效能的重要因素之一。在公路沥青路面条件下,由于路面的强烈吸热作用,通风路基的降温效能被极大削弱,环境升温和设计不当都可能造成工程措施的失效。针对这一问题,提出宽幅通风新型工程措施。模拟计算结果表明,该种新型路基具有高效、快速的降温效能。在沥青路面条件下,该种措施实施3 a后,－3 m深度的地温就已低于原天然地表下的温度,冻土人为上限在快速达到路堤底部约－0.5 m深度后,完全维持稳定。该种措施还成功解决路基地温场的非对称性难题,进一步增强路基的长期稳定。这些结果对我国多年冻土区高等级公路的建设和关键工程问题的解决具有重要意义。