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Proceedings of the 13th Asia Pacific Transportation Development Conference, held in Shanghai, China, May 27-30, 2020. Sponsored by the International Chinese Transportation Professionals Association, Shanghai University of Engineering Science, and the Construction Institute of ASCE.This collection contains 86 peer-reviewed papers on the construction, management, and maintenance of sustainable transportation systems.Topics include: transportation planning and systems development; infrastructure design and construction; transportation systems management and maintenance; multi-modal systems; urban railway planning and management; intelligent maintenance technologies for rail transit systems; rail noise and vibration control; sustainability and environmental and public health; and autonomous and connected vehicles.This proceedings will be of interest to practitioners and researchers addressing the design, construction, and maintenance challenges of advanced transportation systems.

Proceedings of the 13th Asia Pacific Transportation Development Conference, held in Shanghai, China, May 27-30, 2020. Sponsored by the International Chinese Transportation Professionals Association, Shanghai University of Engineering Science, and the Construction Institute of ASCE.This collection contains 86 peer-reviewed papers on the construction, management, and maintenance of sustainable transportation systems.Topics include: transportation planning and systems development; infrastructure design and construction; transportation systems management and maintenance; multi-modal systems; urban railway planning and management; intelligent maintenance technologies for rail transit systems; rail noise and vibration control; sustainability and environmental and public health; and autonomous and connected vehicles.This proceedings will be of interest to practitioners and researchers addressing the design, construction, and maintenance challenges of advanced transportation systems.

• Planning. Overview. Alternatives. Multiple use and joint development. Preliminary design. Mapping. Construction materials and foundations. Water. Pavements. Environment. Geometry. Final design. Earthwork. Drainage and erosion control. Structures. Intersections and interchanges. Roadside. Right-of-way. Plans, specifications and estimates. Construction. Contracts and risk management. Construction items. Safety. Inspection. Operation. Traffic. Maintenance. Intelligent Vehicle Highway Systems (IVHS).
• (source: Nielsen Book Data)

With greater emphasis now being placed on rebuilding and refitting of highways, rather than new construction, design of highways needs to be compatible with the surroundings more than ever. Most highway designers and builders have been educated and trained as engineers; hence they tend to be concerned with the components of design and operation. This volume employs a broader outlook to explain the complete highway project, addressing concerns such as aesthetic values, economies of scale, purpose of the facility, and adaptation of original planning concepts. With this emphasis on the complete picture, it aims to help professionals in the highway community to adapt to future advances in the field.
(source: Nielsen Book Data)

• Preface.Acknowledgment.About the Authors
• .1. Introduction
• .2. Introduction to Wavelet Analysis.2.1 Introduction.2.2 Basic Concept of Wavelets and Wavelet Analysis.2.2.1 What is a Wavelet?.2.2.2 Wavelet Analysis.2.2.3 Types of Wavelets and Wavelet Transforms.2.3 Mathematical Foundations.2.3.1 Sets and Spaces.2.3.2 Sequence and Function Spaces.2.3.3 Independent and Basis Sets.2.3.4 Metric, Normed and Inner Product Spaces.2.3.5 The L2(R) and L2(Z) Spaces.2.3.6 Orthogonality.2.4 The Discrete Wavelet Transform (DWT).2.5 Multi-resolution Analysis.2.6 Wavelet Bases.2.6.1 Constructing Wavelet Bases.2.6.2 Example Wavelet Systems.2.7 Computing the DWT.2.7.1 Pyramid Algorithm.2.7.2 Practical Considerations
• .3. Feature Extraction for Traffic Incident Detection Using Wavelet Transform and Linear Discriminant Analysis.3.1 Introduction.3.2 Incident Detection Algorithms.3.3 Discrete Wavelet Transform (DWT) of Traffic Signals.3.4 Linear Discriminant Analysis (LDA).3.5 Data Acquisition.3.6 Results
• .4. Adaptive Conjugate Neural Network-Wavelet Model for Traffic Incident Detection.4.1 Introduction.4.2 Improving Traffic Incident Detection.4.3 Adaptive Conjugate Gradient Neural Network Model.4.4 Incident Detection Results Using Various Approaches.4.4.1 LDA.4.4.2 DWT and LDA.4.4.3 ACGNN.4.4.4 DWT, LDA, and ACGNN.4.5 Effect of Data Filtering Using DWT.4.6 Relative Contribution of DWT and LDA for Feature Extraction.4.7 Effects of Freeway Geometry on Incident Detection.4.7.1 Effect of Curvature.4.7.2 Effect of Number of Lanes.4.8 Conclusion
• .5. Enhancing Fuzzy Neural Network Algorithms Using Neural Networks.5.1 Introduction.5.2 Discrete Wavelet Transform.5.3 Architecture.5.4 Training of the Network.5.5 Filtering of the Traffic Data Using DWT.5.6 Incident Detection Results
• .6. Fuzzy-Wavelet Radial Basis Function Neural Network Model for Freeway Incident Detection.6.1 Introduction.6.2 A New Traffic Incident Detection Methodology.6.3 Selection of Type and Number of Traffic Data.6.4 Wavelet-Based De-noising.6.5 Fuzzy Data Clustering.6.6 Radial Basis Function Neural Network Classifier.6.7 Fuzzy-Wavelet RBFNN Model for Incident Detection.6.8 Example.6.8.1 Training of Algorithm.6.8.2 Testing of Algorithm Using Simulated Data.6.8.3 Testing of Algorithm Using Real Data.6.9 Conclusion
• .7. Comparison of Fuzzy-Wavelet RBFNN Freeway Incident Detection Model with California Algorithm.7.1 Introduction.7.2 California Algorithm #8.7.3 Evaluation of the Model.7.3.1 Introduction.7.3.2 Evaluation Criteria.7.3.3 Traffic Data.7.3.4 Training and Calibration.7.3.5 First Simulation Test - Parametric Evaluation.7.3.6 Second Simulation Test - Freeway with On- and Off-Ramps.7.3.7 Test Using Real Data.7.4 Concluding Remarks
• .8. Incident Detection Algorithm Using Wavelet Energy Representation of Traffic Patterns.8.1 Introduction.8.2 Freeway Incident Detection and Patterns in Traffic Flow.8.2.1 Single-Station Versus Two-Station Incident Detection Approaches.8.2.2 Upstream and Downstream Flow Patterns.8.3 Discrete Wavelet Transform and Signal Energy.8.4 Traffic Pattern Feature Enhancement and De-noising.8.5 Pattern Classification Using Radial Basis Function Neural Networks.8.6 Wavelet Energy Freeway Incident Detection Algorithm.8.7 Model Testing.8.7.1 Introduction.8.7.2 Training.8.7.3 First Test Using Simulated Data: Two-lane Freeway.8.7.4 Second Test Using Simulated Data: Three-lane Freeway.8.7.5 Third Test Using Simulated Data: Compression Waves.8.7.6 Fourth Test Using Real Data: FSP Project's I-880 Database.8.7.7 Result Summary and Comparison.8.8 Conclusion
• .9. Parametric Evaluation of the Wavelet Energy Freeway Incident Detection Algorithm.9.1 Introduction.9.2 Factors to Consider in Rural Freeway Incident Detection.9.3 Evaluation and Parametric Investigation.9.3.1 Goals.9.3.2 Data.9.3.3 Training and Calibration.9.4 Parametric Evaluation Using Simulated Data on Typical Urban Freeways.9.5 False Alarm Performance in the Vicinity of On- and Off-Ramps.9.6 Evaluation on Rural Freeways.9.7 Evaluation Using Real Data.9.8 Performance Summary and Conclusion
• .10. Case-Based Reasoning Model for Work Zone Traffic Management.10.1 Introduction.10.2 Work Zones and Traffic Management.10.3 Case-Based Reasoning.10.4 Objectives.10.5 Scope and Categorization of Parameters.10.5.1 Work Zone Type.10.5.2 Work Zone Layout.10.5.3 Work Characteristics.10.5.4 Traffic flow characteristics.10.5.5 Phases of Work.10.5.6 Traffic Control Measures.10.5.7 Road User Cost.10.6 A Four-Set Case Model for the Work Zone Traffic Management Domain.10.7 Hierarchical Object-Oriented Case Model.10.8 Case Representation.10.9 Similarity Measures.10.10 Case Retrieval.10.11 Creation of the Case Base.10.12 Creation of Work Zone Traffic Control Plans Using the CBR System.10.13 Illustrative Examples.10.13.1 Example 1.10.13.2 Example 2.10.13.3 Example 3.10.14 Conclusion
• .11. Mesoscopic-Wavelet Freeway Work Zone Flow and Congestion Model.11.1 Introduction.11.2 Macroscopic Models.11.3 Microscopic Models.11.4 A Mesoscopic Flow Model for a Freeway Work Zone.11.5 Traffic Feature Enhancement Using Discrete Wavelet Transform.11.6 Concluding Remarks.References.Index.
• (source: Nielsen Book Data)

This book shows how wavelets can be used to enhance computational intelligence for chaotic and complex pattern recognition problems. By integrating wavelets with other soft computing techniques such as neurocomputing and fuzzy logic, complicated and noisy pattern recognition problems can be solved effectively. The book focuses on applications in intelligent transportation systems (ITS) where a number of very complicated pattern recognition problems have eluded researchers over the past few decades. Advancing the frontiers of computational intelligence, this book describes ingenious computational models based on novel problem solving and computing techniques such as Case-Based Reasoning, Neurocomputing, and Wavelets, and presents examples to illustrate their importance and use.It presents a multi-paradigm intelligent systems approach to the freeway traffic incident detection and construction work zone management problems. It advocates application and integration of wavelets, neural networks and fuzzy logic for modeling the complex traffic flow behaviors leading to effective and efficient control and management solutions. It presents efficient, reliable, and robust algorithms for automatic detection of incidents on freeways. "Wavelets in Intelligent Transportation Systems" is an invaluable resource for computational intelligence researchers and transportation engineers involved in the application of advanced computational techniques for ITS.
(source: Nielsen Book Data)

• 0001; 0002; 0003; 0004; 0005; 0006; 0007; 0008; 0009; 0010; 0011; 0012; 0013; 0014; 0015; 0016; 0017; 0018; 0019; 0020; 0021; 0022; 0023; 0024.

This collection contains 20 peer-reviewed papers on pavement innovation and sustainability presented at the International Conference on Highway Pavements and Airfield Technology 2017, held in Philadelphia, Pennsylvania, August 27-30, 2017.

• chapter Pavement life cycle assessment: A comparison of American and European tools / J. Santos, S. Thyagarajan, E. Keijzer, R. Flores and G. Flintsch
• chapter Lessons learned in developing an environmental product declaration program for the asphalt industry in North America / A. Mukherjee and H. Dylla
• chapter Current difficulties with creation of standardized digital climate calculations for infrastructural projects / L. Stromberg
• chapter Development of an environmental Life-Cycle Assessment (LCA) protocol for flexible pavements that integrates life-cycle components to a proprietary software / F. Osmani, M. Hettiwatte, S. Kshirsagar, S. Senadheera and H.C. Zhang
• chapter Review and comparison of freely-available tools for pavement carbon footprinting in Europe / D.L. Presti and G. D�Angelo
• chapter Route level analysis of road pavement surface condition and truck fleet fuel consumption / F. Perrotta, L. Trupia, T. Parry and L.C. Neves
• chapter Impact of PCC pavement structural response on rolling resistance and vehicle fuel economy / D. Balzarini, I. Zaabar and K. Chatti
• chapter Cool pavement LCA tool: Inputs and recommendations for integration / H. Li, J.T. Harvey and A. Saboori
• chapter Rolling resistance and traffic delay impact on a road pavement life cycle carbon footprint analysis / L. Trupia, T. Parry, L.C. Neves and D.L. Presti
• chapter LCA case study for O'Hare International Airport taxiway A&B rehabilitation / J. Kulikowski
• chapter Exploring alternative methods of environmental analysis / A.F. Braham
• chapter An uncoupled pavement-urban canyon model for heat islands / S. Sen and J.R. Roesler
• chapter The importance of incorporating uncertainty into pavement life cycle cost and environmental impact analyses / J. Gregory, A. Noshadravan, O. Swei, X. Xu and R. Kirchain
• chapter Functional unit choice for comparative pavement LCA involving use-stage with pavement roughness Uncertainty Quantification (UQ) / M. Ziyadi, H. Ozer and I.L. Al-Qadi
• chapter Role of uncertainty assessment in LCA of pavements / S. Inti, M. Sharma and V. Tandon
• chapter Calculation method of stockpiling and use phase in road LCA: Case study of steel slag recycling / O. Yazoghli-Marzouk, M. Dauvergne, W. Chebbi and A. Jullien
• chapter Concrete pavement life cycle environmental assessment and economic analysis: A manitoba case study / M. Alauddin Ahammed, S. Sullivan, G. Finlayson, C. Goemans, J. Meil and M. Akbarian
• chapter Life-cycle assessment tool development for flexible pavement in-place recycling techniques / M.K. Senhaji, H. Ozer and I.L. Al-Qadi
• chapter Life-cycle assessment of road pavements containing marginal materials: Comparative analysis based on a real case study / M. Pasetto, E. Pasquini, G. Giacomello and A. Baliello
• chapter Integrated sustainability assessment of asphalt rubber pavement based on life cycle analysis / R. Cao, Z. Leng, M. Shu-Chien Hsu, H. Yu and Y. Wang
• chapter Environmental assessment and economic analysis of porous pavement at sidewalk / X. Chen, H. Wang and H. Najm
• chapter LCCA for silent surfaces / F.G. Pratico
• chapter Life cycle assessment and benchmarking of end of life treatments of flexible pavements in California / A. Saboori, J.T. Harvey, A.A. Butt and D. Jones
• chapter Life cycle assessment of pavements under a changing climate / O. Valle, Y. Qiao, E. Dave and W. Mo
• chapter Capitalizing green pavement: A method and valuation / X. Liu, D. Choy, Q. Cui and C.W. Schwartz
• chapter A methodology for sustainable mechanistic-empirical pavement design / N. Soliman and M. Hassan
• chapter Energy consumption and Greenhouse Gas Emissions of high RAP central plant hot recycling technology using Life Cycle Assessment: Case study / Y. Lu, H. Wu, A. Liu, W. Ding and H. Zhu
• chapter Implementation of life cycle thinking in planning and procurement at the Swedish Transport Administration / S. Toller and M. Larsson
• chapter Emission-controlled pavement management scheduling / U.D. Tursun, R. Yang and I.L. Al-Qadi.

An increasing number of agencies, academic institutes, and governmental and industrial bodies are embracing the principles of sustainability in managing their activities and conducting business. Pavement Life-Cycle Assessment contains contributions to the Pavement Life-Cycle Assessment Symposium 2017 (Champaign, IL, USA, 12-13 April 2017) and discusses the current status of as well as future developments for LCA implementation in project- and network-level applications. The papers cover a wide variety of topics: - Recent developments for the regional inventory databases for materials, construction, and maintenance and rehabilitation life-cycle stages and critical challenges - Review of methodological choices and impact on LCA results - Use of LCA in decision making for project selection - Implementation of case studies and lessons learned: agency perspectives - Integration of LCA into pavement management systems (PMS) - Project-level LCA implementation case studies - Network-level LCA applications and critical challenges - Use-phase rolling resistance models and field validation - Uncertainty assessment in all life-cycle stages - Role of PCR and EPDs in the implementation of LCA Pavement Life-Cycle Assessment will be of interest to academics, professionals, and policymakers involved or interested in Highway and Airport Pavements.
(source: Nielsen Book Data)

• Part I Pavement design and management principles
• Part II Pavement design procedures for new construction or reconstruction
• Part III Pavement design procedures for rehabilitation of existing pavements
• Part IV Mechanistic-empirical design procedures.

This 13th Edition of the AASHTO Provisional Standards contains a complete set of 41 provisional materials specifications and test methods. All Provisional Standards are approved for publication by the AASHTO Highway Subcommittee on Materials. Provisional Standards are standards which have been adopted by the Highway Subcommittee on Materials on a temporary basis for a maximum of eight years. A chronology of the year-to-year status of the Provisional Standards during the past eight years is included. At any time during the eight-year period, the Subcommittee can ballot to convert a Provisional Standard into a Full Standard. The Subcommittee, so far, has converted 58 Provisional Standards into Full Standards. These Standards are now regularly published in the AASHTO Standard Specifications for Transportation Materials and Methods of Sampling and Testing.