Transportation Infrastructure in Alabama Tools for Solutions This research was sponsored by the U.S. Department of Transportation, Federal Transit Administration, Project No. AL-26-7262-00. The Center for Management and Economic Research The University of Alabama in Huntsville 1 This research is the result of the professional efforts of the following team: William R. Killingsworth, Ph.D. Director, Center for Management and Economic Research Gregory A. Harris, Ph.D., P.E. Principle Research Engineer, Center for Management and Economic Research Michael D. Anderson, Ph.D. Associate Professor, Civil and Environmental Engineering, UAH Phillip A. Farrington, Ph.D. Professor, Industrial & Systems Engineering, Engineering Management, UAH Lauren C. Jennings Research Scientist, Office for Freight, Logistics and Transportation Sharla A. Mondesir Research Scientist, Office for Freight, Logistics and Transportation Sarah M. Marcott Student Assistant, Center for Management and Economic Research Niles C. Schoening, Ph.D. Professor, College of Administrative Science, Economics, UAH Bernard J. Schroer, Ph.D. Principal Research Scientist, Office for Freight, Logistics and Transportation Heather R. Shar, EIT Research Scientist, Office for Freight, Logistics and Transportation Sherry Starling Research Scientist, Center for Management and Economic Research James J. Swain, Ph.D. Professor, Industrial & Systems Engineering, Engineering Management, UAH Jeff Thompson Principal Research Scientist, Center for Management and Economic Research Karen Yarbrough Research Scientist, Center for Management and Economic Research 2 Table of Contents Executive Summary……………………………………………………………………… 5 1. Development of a Freight Forecasting Methodology Utilizing Industry Sector Analysis………………………………………………………………………………… 20 1.1 The State of Freight Data……………………………………………………….. 20 1.2 A Freight Planning Framework…………………………………………………. 22 1.2.1 Traditional Transportation Planning……………………………………. 22 1.2.2 A New Approach to Freight Forecasting……………………………….. 25 1.2.3 Planning Factors………………………………………………………….. 27 1.2.4 Freight Data……………………………………………………………….. 28 1.2.5 Disaggregation Filter……………………………………………………… 29 1.2.6 Growth Projections………………………………………………………... 31 1.2.7 The Gravity Distribution Model…………………………………………... 32 1.2.8 Statewide Multi-Modal Discrete Event Simulation…………………….. 32 1.2.9 System Performance Measures…………………………………………. 33 1.2.10 FPF Summary……………………………………………………………... 33 1.3 Supply Side and Demand Side Freight Data Development…………………. 33 1.3.1 Analysis of Supply Side Freight…………………………………………. 34 1.3.2 Analysis of Final Demand Sector……………………………………….. 43 1.4 Chapter References……………………………………………………………… 45 2. Refinement and Application of the Alabama Transportation Infrastructure Model…………………………………………………………………………………… 46 2.1 Verify Hourly Output of Model with DOT Vehicle Counts……………………. 48 2.2 Verify Model Response to Changing Truck Traffic…………………………… 54 2.3 Develop Origin and Destination Rail Information…………………………….. 58 2.4 Develop Origin and Destination Waterborne Information……………………. 62 2.5 Work with MPO’s to Develop Freight Information by City/Area……………... 64 2.6 Develop and Validate Intermodal Traffic Volumes…………………………… 66 2.7 Model Capacity Restrictions…………………………………………………….. 68 2.8 Model Enhancements…………………………………………………………… 69 2.9 Chapter References……………………………………………………………… 71 3. Development of the System Dynamics Model of the Alabama Transportation Infrastructure…………………………………………………………………………... 74 3.1 Alabama Historical Population…………………………………………………... 74 3.2 Population Trends and School Enrollment in Alabama………………………. 77 3.3 Alabama Industry Employment………………………………………………….. 79 3.3.1 Agriculture & Natural Resources………………………………………… 79 3.3.2 Basic Manufacturing……………………………………………………… 80 3.3.3 Advanced Manufacturing………………………………………………… 81 3.3.4 Service Industry…………………………………………………………… 82 3.3.5 Knowledge Industry………………………………………………………. 85 3.4 Historical Growth in Interstate Traffic…………………………………………... 87 3.5 Model Outlook for Interstate Traffic…………………………………………….. 89 3.6 Description of the Model Used to Investigate Likely Trends in Population and Workforce…………………………………………………………………….. 93 3 3.6.1 Population………………………………………………………………….. 94 3.6.2 Education…………………………………………………………………... 96 3.6.3 Workforce………………………………………………………………….. 97 3.6.4 Transportation…………………………………………………………….. 98 3.7 Interrelationships…………………………………………………………………. 100 3.8 Comparison of the Model Output with Historical Data……………………….. 100 3.9 Likely Future Trends in Population, Workforce, Etc………………………….. 106 3.10 Conclusions………………………………………………………………... 113 3.11 Chapter References………………………………………………………. 113 4. Establishment of an Online Information Warehouse for Transportation Related Data and Research Publications for Alabama and the Tennessee Valley Region………………………………………………………………………………….. 114 4.1 Population, Infrastructure, and Economic Activity (P-I-E) Data……………... 114 4.2 Data Found Under Each Main Heading of the P-I-E Data Section of the Online Information Warehouse………………………………………………….. 115 4.3 Presentations, Publications, and Reports……………………………………... 124 4.4 Project Images……………………………………………………………………. 125 4.5 Conclusion………………………………………………………………………… 127 5. Conclusions and Next Steps………………………………………………………… 128 5.1 Current Research Streams………………………………………………………. 128 5.1.1 Freight Forecasting, Planning and Analysis……………………………. 129 5.1.2 Transportation Systems Modeling and Simulation……………………. 129 5.1.3 Interrelationships Between Population, Infrastructure, and Economic Activity……………………………………………………………………… 130 5.1.4 Productivity Enhancements in Transportation, Logistics, and Supply Chains……………………………………………………………………… 131 5.2 Next Steps………………………………………………………………………… 131 5.2.1 Development of Freight Analysis Zones………………………………... 131 5.2.2 Expansion and Enhancement of the Alabama Transportation Infrastructure Model (ATIM)……………………………………………… 133 5.2.3 Modeling Intermodal Operations Using Discrete Event Simulation…. 134 5.2.4 Continuous Improvement in Logistics & Transportation Systems…… 134 5.2.5 Support the Online Information Warehouse for Alabama and the Tennessee Valley Region……………………………………………….. 134 Table of Tables……………………………………………………………………………. 135 Table of Figures…………………………………………………………………………… 136 Appendix A: Current and Projected Industry Truckloads and Value of Shipments by County Appendix B: Preliminary Freight Model Validation Using Extreme-World Scenario Construction Appendix C: Alabama Commission on Infrastructure: Sustaining and Creating Economic Prosperity Appendix D: Transportation Legislation Introduced Appendix E: Papers Submitted and Published 4 Executive Summary In the decade of the 90’s the need to integrate freight into the policy, planning and programming activities of State Departments of Transportation (DOTs) and metropolitan planning organizations (MPOs) became very apparent as global manufacturing, outsourcing, and off shoring became more prominent in the global and US economy. Business and community leaders, as well as public sector officials, recognized that the effective and efficient movement of freight is key to a region’s economic competitiveness. Using almost any metric, freight traffic is growing faster than passenger travel. Freight, by it nature, crosses modal boundaries, therefore any analysis method that does not consider multiple modes of transportation, such as truck and rail, are inadequate. However, by better understanding freight needs and issues, it is possible to design and conduct an economical and efficient freight planning process that can be integrated with conventional transportation planning. More than 15 billion tons of freight valued at over $9 trillion traveled on the US transportation infrastructure in 1998. By 2020, freight will have grown by nearly 70 percent and the value of the goods moved will be almost $30 trillion, according to the Federal Highway Administration. This level of activity and growth demands the attention of transportation system planners. Freight data is key to making informed decisions on infrastructure investment and policies issues that affect the effectiveness and efficiency of the freight transportation system. Freight data is critical to the evaluation of options to mitigate congestion, improve economic competitiveness, facilitate the effective use of land planning, optimization of modal activity, improve safety and security, reduce fuel consumption and enhance air quality. Although data by itself does not ensure good decision-making, it is not possible to make informed decisions without valid data. A Transportation Research Board committee formed to investigate and make recommendations on freight data concluded that the present patchwork of uncoordinated and incomplete freight data sources should be reengineered in the context of a national freight data framework that provides for a more integrated approach to freight data collection and synthesis. The committee noted that this would be a multi-year effort and would involve many technical organizational challenges. In response to this need to investigate freight from a multi-modal and comprehensive perspective, researchers at the University of Alabama in Huntsville (UAH) developed a Freight Planning Framework (FPF) shown in Figure ES.1. This framework is a direct freight forecast based upon industry economic activity that offers an improvement to the forecast based upon a percentage of overall traffic flow typically used by transportation planners throughout the U.S. The project research goal was to establish