Highway Alignment Optimization Research Articles

Highway Alignment Optimization Design Method Based on Multi-Objective Particle Swarm Optimization

Highway alignment design is a nonlinear multi-objective optimization problem. Due to the uncertainty and complexity of the constraints, it is challenging to develop a suitable model for 3D road alignment design. To comprehensively consider the constraints and realize the intelligent design, this study puts forward a novel highway alignment model to optimize the horizontal and vertical alignment design, in which the length utility cost and structure construction cost are projected into the optimization space. Finally, the numerical solution is carried out by MOPSO on MATLAB platform. The results show that this method can effectively solve the problem of highway alignment design under the condition of realizing the highway design specifications, shortening the design cycle, and improving the design quality, which verifies the feasibility of the optimization algorithm for the horizontal and vertical alignment optimization design of highway.

Study on Highway Alignment Optimization Considering Rollover Stability Based on Two-Dimensional Point Collision Dynamics

In order to reduce the influence of unreasonable road alignment design on vehicle driving safety, a study on road alignment optimization and vehicle driving safety based on two-dimensional point collision dynamics was carried out. First, through the two-dimensional point collision dynamics model, the relationship of the kinematic parameters before and after vehicle collision was deduced. Second, according to the vehicle–road coupling dynamic model analysis after collision, the safety threshold between the radius of the circular curve and the road superelevation was derived by taking vehicle rollover as the critical condition. Next, the road alignment optimization scheme based on vehicle rollover stability after collision was proposed. Finally, the rationality of the optimization scheme was verified by PC-Crash simulation. The simulation results showed that the proposed optimization scheme of the minimum radius and superelevation of the circular curve meets the safety requirements of vehicle rollover. This study optimized the relevant indicators of the road alignment under the premise of ensuring vehicle rollover stability and provides a reference for the improvement and optimization of road alignment design. It also has important guiding significance for the formulation of vehicle driving safety management measures.

Highway Alignment Optimization: An Integrated BIM and GIS Approach

Highway infrastructure plays an important role in assuring the proper function of the nation’s transportation. Highway alignment is an essential part of the highway planning and design phase, which has significant effects on the surroundings. Identifying optimal highway routes while using traditional methods requires significant time, cost, and effort, since it requires a comprehensive assessment of multiple factors, such as cost and environmental impacts. This study proposes an approach for managing highway alignment in the context of a larger landscape that integrates building information modelling (BIM) and geographic information system (GIS) capabilities. To support this integration, semantic web technologies are used to integrate data on a semantic level. Moreover, the approach also uses genetic algorithms (GAs) for optimizing highway alignments. A fully automated model is developed that enables data interoperability between BIM and GIS systems and also allows for data exchange between the integration model and the optimization algorithm. The model enables the full exploitation of features of the project and its surroundings for highway alignment planning. The proposed model is also applied to a real highway project to validate its effectiveness. The visualization model of the highway project and its surroundings provides a realistic three-dimensional image that produces a comprehensive virtual environment, where the project could be effectively planned and designed. That can help to reduce design errors and miscommunication, which, in turn, reduces project risks. Moreover, geological and geographical analyses help to identify geohazards and environmentally sensitive regions. The proposed model facilitates highway alignment planning by providing a cross-disciplinary approach to close the gap between the infrastructural and geotechnical planning processes.

Potentialities of a Highway Alignment Optimization Method in an I-BIM Environment

The BIM (Building Information Modeling) approach potential in the civil engineering field opened novel scenarios in the design idea concept, from planning to executive and constructive phases. The related advantages are numerous and not only limited to a real-time interaction among the involved subjects, that can actually operate in an optimized 3D shared environment. Owing to the sharing information philosophy and to the features of various "smart objects" combined in the project, this innovation reduces potential errors and increases the effectiveness of the design solution in terms of both functionality and cost. Despite these advantages, the highway alignment design problem remains very complicated and not easy to solve without appropriate supporting tools. In recent years, several efforts have been spent in defining highway optimization procedures for helping designers in the selection of an optimal solution in compliance with numerous different constraints. Introducing these procedures in a BIM environment may represent a crucial step in the improvement of the highway design procedures, exploiting the full representation and modelling potential of the approach. In this paper, the authors present the advantages of a 3D highway alignment optimization algorithm, based on the Particle Swarm Optimization method, and its possible implementation in a BIM platform. A proper I-BIM environment can exploit the potential of the alignment optimization algorithms, simplifying the analysis of the different solutions, the final representation and the eventual manual modifications.

Corridor Based Horizontal Highway Alignment Optimization Using GIS and Genetic Algorithms

Corridor Based Horizontal Highway Alignment Optimization Using GIS and Genetic Algorithms

Highway alignment optimization by using cost and safety criteria

Highway alignment optimization by using cost and safety criteria

A MULTIVARIATE METHODOLOGY FOR DETERMINING THE OPTIMAL HIGHWAY ALIGNMENT CANDIDATE BASED ON GEOGRAPHIC INFORMATION SYSTEM AND ANALYTIC HIERARCHY PROCESS

Research on highway alignment optimization has been quite intensive over the last two decades. Determining the best candidate for highway alignment is one of the most complex highway design stages due to the different effects of various parameters. Hence, in the present study, Analytic Hierarchy Process technique and Geographic Information System are proposed to determine the best highway candidate with special focus on the constraint, cost and safety criteria. The methodology presented in the current research is not limited to the constraint, cost and safety criteria but can be extended to other criteria. This methodology has been implemented on a case study region in northwestern of Iran, and therefore the constraint, cost and safety criteria have been obtained for the case study conditions. The final result of the current paper indicates that the optimal highway candidate obtained with the proposed methodology can concurrently satisfy all relative parameters in highway alignment optimization based on their impact.

A Quantitative Analysis of Sustainability and Green Transportation Initiatives in Highway Design and Maintenance

Sustainability and green transportation initiatives have been widely promoted in highway design and maintenance in recent years. While there are many definitions of sustainability and green transportation, there has mainly been a qualitative description of such initiatives in previous works. In this paper we propose a quantitative analysis of sustainability and green transportation from highway design and maintenance perspective. There is a considerable interaction between highway design and maintenance. For example, a well designed and maintained highway should jointly minimize the initial and life-cycle costs. But, generally a precise account of maintenance life-cycle cost analysis is not performed in the design stages of a highway. In this paper a highway alignment optimization problem is analyzed and evaluated based on the joint minimization of initial and life-cycle costs. An illustrative example is presented

Multi-objective highway alignment optimization incorporating preference information

This paper presents a GIS-based multi-objective optimization model, particularly designed to aid highway engineers and planners in proposing competitive highway alignment alternatives when building a new highway or expanding an existing highway. The proposed model can effectively examine tradeoffs among various objectives that represent possibly conflicting interests of different stakeholders. A Hybrid Multi-Objective Genetic Algorithm, which utilizes designers’ knowledge about the preference of decision makers, is developed to search for a set of Pareto-optimal solutions with an acceptable level of diversity. Two case studies demonstrate the capability of the proposed approach in providing multiple trade-off solutions. The results indicate that the incorporation of preference information, even if preliminary in nature, has great potential to save computation time and improve the quality of the obtained Pareto-optimal set.

Empirical Model with Environmental Considerations in Highway Alignment Optimization

The highway alignment optimization (HAO) process is a complex combinatorial optimization problem in which several conflicting factors, such as highway costs, user preferences, and environmentally sensitive factors, must be simultaneously considered. In previous studies, single-level and bi-level optimization approaches were developed to optimize three-dimensional highway alignments. One drawback of previous approaches is that environmental factors, such as vehicular emissions, were not adequately considered in conjunction with other factors (such as user preferences and highway costs) in the optimization process. This paper builds on our previous studies and proposes two separate approaches for considering environmental emissions in the HAO process. The first approach involves a separate analysis of user and decision-maker preferences, in which a conceptual formulation of various environmental factors is presented. In the second approach, a novel tri-level optimization framework is proposed for optimizing highway alignments. At the upper level, optimization is performed using the traditional criteria of cost minimization. At the intermediate level, total systems emission is calculated. Finally, at the lower level, the user equilibrium traffic flow is optimized. The developed approaches are illustrated through case study examples. The proposed approaches will be beneficial for designing highway alignments when considering environmental emissions. Future studies may make additional refinements to the formulation and sensitivity analyses.

Bidirectional Dynamic Programming Approach for Highway Alignment Optimization

In order to automatically generate the optimal highway alignment and avoid omitting valuable scenarios, a bidirectional dynamic programming approach for alignment optimization was put forward. Firstly we established a three-dimensional search grid in the study area. Then dynamic programming was used to find the best alignments within the vast study area. A double-direction searching strategy was proposed to obtain a group of scenarios ranking by their corresponding comprehensive cost. The alignments were then refined with Powell method so that the resulting alignments could deviate from the grid points to reach better solutions. Examples demonstrated that this approach can obtain global optimal alignment with good diversity.

New highway geometric design methods for minimizing vehicular fuel consumption and improving safety

This paper proposes separate computational methods for evaluating (1) fuel efficiency, (2) sight distance deficiencies and (3) expected accident costs for a given highway alignment, depending on its detailed geometric characteristics. A fuel consumption model is developed based on two important concepts: (i) variability in the amount of fuel consumed by vehicles depending on variability in highway geometry and (ii) minimization of the fuel consumption by ensuring conditions suitable for driving at cruising speed. The methods estimate the fuel consumption by integrating vehicle propulsive force necessary to maintain the cruising speed from the beginning to the end of an alternative highway being evaluated. A sight distance model that not only automatically calculates available sight distance (ASD) and stopping sight distance (SSD), but also evaluates sight distance deficiency of alternative alignments is proposed. The total sight distance deficiency of an alternative alignment is estimated based on (i) the length of the road segments where ASD<SSD and (ii) the significance of sight distance restriction. A crash prediction model proposed in the Highway Safety Manual (HSM) is adopted to evaluate and compare alternative alignments from safety perspective. A case study is presented to demonstrate the effectiveness of the developed methods. These methods will be integrated into a highway alignment optimization model (HAO) previously developed by the authors to evaluate numerous possible alternative alignments of a new highway system through tradeoffs among various relevant decision criteria. Those criteria may include vehicle fuel efficiency, sight distance, and safety, besides various cost factors, such as the construction cost, maintenance cost, user cost, and environmental impact cost. Such an integrated modeling framework will help evaluate green and environmentally sustainable highways. Many extensions of the work remain to be worked in the future, for example: (1) the effects of gain in propulsive force when traveling down from the crest of a curve; and (2) variability in fuel consumption rate based on vehicle type, gradient, critical length of grade, weather, and other factors.

Improving the Computational Efficiency of Widening Highway Approach

In this paper we propose a stepwise genetic algorithms approach for optimizing highway alignments for improving computational efficiency and quality of solutions. Our previous work in highway alignment optimization has demonstrated that computational burden is a significant issue when working with a geographic information system (GIS) database requiring numerous spatial analyses. For solving real-world problems working directly with real maps through a GIS is highly desirable. Furthermore, saving computation time can enhance adoptability of a model especially when a study area is relatively large, or involves many sensitive properties, or if locating complex structures such as intersections, bridges and tunnels is necessary. It is well acknowledged that in many optimization processes subdividing large problems into smaller pieces can decrease the computation time and produce a better solution. In this research two different population sizes are used to develop a stepwise alignment optimization when employing genetic algorithms in suitably subdivided study areas. An example study shows that the proposed stepwise optimization gives more efficient results than the existing methods and also improves quality of solutions.

The Efficient Applicability of Highway Alignment Optimization Models

The total engineering geology approach is applied to a roadway pilot project in the tidal deposits of the Western Netherlands.Its benefit as compared to the conventional geotechnical site investigation is demonstrated.Combining laser scanner altimetry data that is readily available to low cost GEM-2 electromagnetic surveys, allows for the refinement of the local geological model. Small and large scale heterogeneities have been detected in this study. Their existence has been confirmed by a line of closely spaced CPTs. On the basis of laser altimetry and GEM-2 signature, the identified heterogeneities are classified. Only a limited set of heterogeneities representative of the different classes requires a further detailed investigation. Aspects of feasibility, accuracy, and cost-effectiveness have a need for further research.

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.

Applicability of Genetic and Ant Algorithms in Highway Alignment and Rail Transit Station Location Optimization

The emergence of artificial intelligence (AI)-based optimization heuristics like genetic and ant algorithms is useful in solving many complex transportation location optimization problems. The suitability of such algorithms depends on the nature of the problem to be solved. This study examines the suitability of genetic and ant algorithms in two distinct and complex transportation problems: (1) highway alignment optimization and (2) rail transit station location optimization. A comparative study of the two algorithms is presented in terms of the quality of results. In addition, Ant algorithms (AAs) have been modified to search in a global space for both problems, a significant departure from traditional AA application in local search problems. It is observed that for the two optimization problems both algorithms give almost similar solutions. However, the ant algorithm has the inherent limitation of being effective only in discrete search problems. When applied to continuous search spaces ant algorithm requires the space to be sufficiently discretized. On the other hand, genetic algorithms can be applied to both discrete and continues spaces with reasonable confidence. The application of AA in global search seems promising and opens up the possibility of its application in other complex optimization problems.

Applicability of highway alignment optimization models

This paper presents an intelligent optimization tool that assists planners and designers in finding preferable highway alignments, connecting specified endpoints or zones. It integrates genetic algorithms with a geographic information system (GIS) for optimizing highway alignments and processes massive amounts of relevant data associated with highway design and alternative evaluation. To show the applicability of the proposed model to a real-world problem, two actual highway projects in the state of Maryland have been analyzed using the model. An extensive analysis of sensitivity to key model parameters is also conducted to describe the model capabilities. The analysis results show that the model can effectively optimize highway alignments in an area combining complex terrain and various types of natural and cultural land-use patterns, and provide detailed information of optimized alignments as a model output. It is also found that the alignments optimized by the model are quite similar to those obtained through conventional manual methods by a state agency, but the model can greatly reduce the time required for highway planning and design as well as produce lower cost solutions. Finally, the results confirm that all dominating and alignment-sensitive costs should be simultaneously evaluated in the alignment optimization process because many trade-off opportunities exist among those costs. The proposed model can greatly contribute to the productivity of highway planners as well as to the quality of the resulting infrastructure.

Highway Alignment Optimization Using Cost-Benefit Analysis Under User Equilibrium

Usually, selection of a highway alignment depends on an economical route that minimizes alignment sensitive costs, such as construction cost, user cost, right-of-way cost, and earthwork cost. Most of the available highway alignment optimization algorithms do not consider traffic assignment and distribution of traffic as a result of the new road network consisting of the new alignment as well as other pre-existing alignments. Constructing a new highway will ease the traffic in the existing road network. Based on Wardrop’s principle, the users will choose a route that will minimize their travel-time. Users will unilaterally shift to the available routes for their benefit and thus, traffic flow will attain equilibrium. Theoretically, the equilibrium of traffic flow between the existing highway and the newly designed highway alternative can be achieved by a user equilibrium model. A new methodology is developed in this paper to optimize a new three-dimensional highway alignment based on the existing highway alignment system information using a cost-benefit analysis approach. The results are quite promising for new road design and bypass construction since benefit maximization and cost minimization is performed simultaneously while attaining user equilibrium.

An Adaptive Genetic Algorithm Based on Multi-Population Parallel Evolutionary for Highway Alignment Optimization Model

Based on the characteristics of the highway design, this paper transfers all the factors involved in the highway design to a cost-optimized-oriented model and designs a variety parallel genetic algorithm to optimize highway design. While maintaining evolution stability of excellent individual, the algorithm can improve convergence rate and accuracy and avoid premature convergence generated by single-population evolution. To some extent, it makes up generalization-lacking defects of a single species or steady parameters in premature overcoming. Finally, the algorithm is verified with a good result. This algorithm provides a useful method for highway design.

A Multiobjective Analysis of Impacted Area of Environmentally Preserved Land and Alignment Cost for Sustainable Highway Infrastructure Design

Sustainable highway infrastructure design requires a good balance between environment and cost. The available computer-based automated highway alignment optimization algorithms minimize the total highway alignment cost towards obtaining the optimized alignment. These are primarily single-objective optimization approaches with limited capability in considering various cost components and factors that may be dissimilar or conflicting in nature. In these approaches, the impacted area of environmentally preserved land is transformed to monetary value and included in the total highway alignment cost. Also, they have limited capability in yielding a set of alternatives with different levels of trade-off between the total highway alignment cost and impacted area of environmentally preserved land. This leads to the need for developing a model to estimate the impacted area of environmentally preserved land in terms of non-monetary values and use concurrently with total highway alignment cost providing a perspective comparison of highway alignment alternatives. A multiobjective analysis is presented in this paper to consider the impacted area of environmentally preserved land information expressed in non-monetary unit and total highway alignment cost expressed in monetary unit. In this analysis, a genetic algorithm (GA) based multiobjective optimization technique is adopted. The paper describes a special algorithm developed to estimate the impacted area of environmentally preserved land from a Geographic Information System (GIS) based study area map and simultaneous minimization of impacted area of environmentally preserved land and highway alignment cost. A Pareto-optimal front is used to graphically represent the trade-off values of highway alignment cost and impacted area of environmentally preserved land. Finally, the developed methodology is applied to a study area and results are compared with the available single objective highway alignment optimization model output.