Artificial Intelligence in Highway Location and Alignment Optimization

Length: 200 pages
Edition: 1
Language: English
Publisher: World Scientific Publishing Co
Publication Date: 2020-09-30
ISBN-10: 9813272805
ISBN-13: 9789813272804
Sales Rank: #6588759 (See Top 100 Books)

This monograph provides a comprehensive overview of methods for searching, evaluating, and optimizing highway location alignments using genetic algorithms (GAs), a powerful Artificial Intelligence (AI) technique. It presents a two-level programming structure to deal with the effects of varying highway location on traffic level changes in surrounding road networks within the highway location search and alignment optimization process. In addition, the proposed method evaluates environmental impacts as well as all relevant highway costs associated with its construction, operation, and maintenance. The monograph first covers various search methods, relevant cost functions, constraints, computational efficiency, and solution quality issues arising from optimizing the highway alignment optimization (HAO) problem. It then focuses on applications of a special-purpose GA in the HAO problem where numerous highway alignments are generated and evaluated, and finally the best ones are selected based on costs, traffic impacts, safety, energy, and environmental considerations. A comprehensive review of other promising optimization methods for the HAO problem is also provided in this monograph.

Readership: The monograph is a valuable reference for graduate and postgraduate researchers who seek to solve transportation system and network optimization problems using Artificial Intelligence techniques.

Cover page
Title page
Copyright
About the Authors
Contents
Part I: Overview of Highway Location and Alignment Optimization Problem
    Chapter 1: Introduction
        1.1 Background
        1.2 Highway Alignment Optimization Problems
        1.3 Organization of the Monograph
    Chapter 2: Highway Cost and Constraints
        2.1 Initial Construction Costs
        2.2 Highway Maintenance Costs
        2.3 User Costs
        2.4 Environmental and Socio-economic Impacts
        2.5 Highway Constraints
            2.5.1 Geometric Constraints
            2.5.2 Geographical and Environmental Constraints
    Chapter 3: Review of Artificial Intelligence-based Models for Optimizing Highway Location and Alignment Design
        3.1 Genetic Algorithms-based Optimization Models
            3.1.1 Highway Alignment Optimization (HAO) Models by the UMD Research Team
            3.1.2 Other Models that Use Genetic Algorithms for Optimizing Highway Alignments
        3.2 Other Artificial Intelligence-based Optimization Models
            3.2.1 Swarm Intelligence-based Models
            3.2.2 Neighborhood Search Heuristic
        3.3 Other Methods Tried with AIs for Optimizing Highway Alignments
            3.3.1 Distance Transform
            3.3.2 Multi-objective Optimization
            3.3.3 Multiple Path Optimization
            3.3.4 Other Objectives Considered
            3.3.5 Summary
Part II: Highway Alignment Optimization with Genetic Algorithms
    Chapter 4: Modeling Highway Alignments with GAs
        4.1 Representation of Highway Alignments with GAs
        4.2 Modeling Horizontal Alignments
            4.2.1 Horizontal Alignment Generation Procedure
        4.3 Modeling Vertical Alignments
        4.4 Modeling Highway Endpoints
            4.4.1 Determination of Highway Endpoints
            4.4.2 Highway Endpoint Determination Procedure
            4.4.3 GA Operators for Endpoint Generation
        4.5 Modeling Highway Structures
            4.5.1 Small Highway Bridges for Grade Separation
            4.5.2 Structures for Highway Junction Points with Existing Roads
    Chapter 5: Highway Alignment Optimization Formulation
        5.1 Objective Function
        5.2 Constraints
        5.3 Integrating GAs and Geographic Information System
        5.4 Highway Cost Formulation
            5.4.1 Highway Agency Cost
            5.4.2 User Cost
            5.4.3 Penalty and Environmental Costs
            5.4.4 Life-cycle Cost
    Chapter 6: Constraint Handling for Evolutionary Algorithms
        6.1 Direct Constraint Handling
            6.1.1 Elimination Method
            6.1.2 Repairing Method
            6.1.3 Preserving Method
            6.1.4 Decoding Method
            6.1.5 Locating the Boundary of the Feasible Regions
        6.2 Indirect Constraint Handling (Penalty Approaches)
            6.2.1 Death Penalty
            6.2.2 Static Penalty
            6.2.3 Dynamic Penalty
            6.2.4 Adaptive Penalty
        6.3 Handling Infeasible Solutions of GA-based Highway Alignment Optimization
    Chapter 7: Highway Alignment Optimization Through Feasible Gates
        7.1 Research Motivation of Feasible Gates
        7.2 Feasible Gates for Horizontal Alignments
            7.2.1 User-defined Horizontal Feasible Bounds
            7.2.2 Representation of Horizontal Feasible Gates
            7.2.3 Horizontal Feasible Gate Determination Procedure
            7.2.4 User-defined Constraints for Guiding Feasible Alignments
        7.3 Feasible Gates for Vertical Alignments
            7.3.1 Road Elevation Determination Procedure
        7.4 Example Study
        7.5 Summary
    Chapter 8: Prescreening and Repairing in Highway Alignment Optimization
        8.1 Research Motivation of Prescreening and Repairing
        8.2 Prescreening and Repairing for Alignments Violating Design Constraints
            8.2.1 P&R Basic Concept
            8.2.2 Determination of Design Constraint Violations
        8.3 Example Study
        8.4 Summary
Part III: Optimizing Simple Highway Networks: An Extension of Genetic Algorithms-based Highway Alignment Optimization
    Chapter 9: Overview of Discrete Network Design Problems
        9.1 Bi-level Discrete Network Design Problems
            9.1.1 Upper-level DNDP
            9.1.2 Lower-level DNDP
        9.2 Comparison of Highway Alignment Optimization and Discrete Network Design Problems
    Chapter 10: Bi-level Highway Alignment Optimization within a Small Highway Network
        10.1 Bi-level HAO Concept
        10.2 Upper Level of Bi-level HAO
            10.2.1 Highway Agency Cost for Bi-level HAO
            10.2.2 Highway User Cost for Bi-level HAO
            10.2.3 Penalty and Environmental Costs
        10.3 Lower Level of Bi-level HAO
            10.3.1 User and System Optimal Traffic Assignment Problems
            10.3.2 Determination of Traffic Reassignment
        10.4 Bi-level HAO Model Structure
        10.5 Inputs Required for Lower Level of Bi-level HAO
            10.5.1 Highway Network and O/D Trip Matrix
            10.5.2 Travel Time Functions
        10.6 Summary and Future Work
    Chapter 11: Bi-level HAO Model Application Example
        11.1 Example Description
        11.2 Optimized Alternatives
        11.3 Summary
Part IV: Highway Alignment Optimization Model Applications and Extensions
    Chapter 12: HAO Model Application in Maryland Brookeville Bypass Project
        12.1 Project Description
        12.2 Data and Application Procedure
            12.2.1 Horizontal Map Digitization
            12.2.2 Vertical Map Digitization
            12.2.3 Tradeoffs in Map Representation for Environmental Issues
            12.2.4 Description of Model Inputs and Outputs
        12.3 Optimization Results
            12.3.1 Optimized Alignments with Different Numbers of PI’s
            12.3.2 Goodness Test
        12.4 Sensitivity of Optimized Alignments to Other Major Input Parameters
            12.4.1 Sensitivity to the Model’s Objective Function
            12.4.2 Sensitivity to Design Speed
            12.4.3 Sensitivity to Elevation Resolution
            12.4.4 Sensitivity to Cross-section Spacing
    Chapter 13: HAO Model Application in US 220 Project in Maryland
        13.1 Project Description
        13.2 Projection Preparation
            13.2.1 Spatial Data
            13.2.2 Project Segmentation
            13.2.3 Geometric Design Specification
        13.3 Optimization Results
    Chapter 14: HAO Model Application to Maryland ICC Project
        14.1 Project Description
            14.1.1 Overview of the ICC Study
            14.1.2 Description of HAO Model Application to ICC Project
        14.2 Input Data Preparation
            14.2.1 Road Network
            14.2.2 Traffic Information
            14.2.3 GIS Map Preparation
            14.2.4 Important Input Parameters
        14.3 Optimization Results
            14.3.1 Determination of Traffic Reassignments
            14.3.2 Optimized Alignments
            14.3.3 Goodness Test
    Chapter 15: Related Developments and Extensions
        15.1 Related Developments
        15.2 Extensions
Appendix A: Notation Used in the Monograph
Appendix B: Traffic Inputs to the HAO Model for the ICC Case Study
References
Index