Master Transportation Plan Task 4: Gap Analysis and Needs Network
3.7 Freight Gap Analysis 3.7.1 Approach Overview The purpose of the freight gap analysis was to identify infrastructure and operational deficiencies that limit the efficiency, safety, and inter- and intra-regional freight movement connectivity. The methodology highlights intercity and regional gaps in network continuity, last-mile access to key freight generators, and performance constraints and safety challenges to guide targeted investment in high- priority freight corridors. 3.7.2 Methodology To analyze freight network connectivity and gaps, the process focused the data collection effort to establish and understand existing freight conditions at a local, city, and regional basis. The analysis began by mapping the designated freight network, including: • National Highway Freight Network • Texas Department of Transportation-designated truck routes • Federal Highway Administration intermodal connectors • Intermodal and rail facilities (e.g., terminals, rail yards, transload centers) Following the establishment of the existing conditions, the process began with evaluation of three core components of last-mile connectivity, inter-city and regional trips, and freight safety. Freight business clusters were identified through a preliminary top trip pair analysis and intermodal and rail facilities point data for last-mile connectivity analysis. With the use of Replica roadway freight trip data, travel sheds were created around clusters to identify locations where freight activity is concentrated but not well-served by existing infrastructure, highlighting underserved freight-generating areas or intermodal facilities with poor last-mile access or operational challenges, such as freight dispersion to local or collector roads. The freight clusters Replica trip volume data was collected along with O/D data to analyze routing patterns to and from U.S. Census Bureau Tracts in (local) and outside (regional) the City of Fort Worth. The combination of freight activity clusters and O/D Census Tract Pairs were used to identify roadway facilities and freight clusters with the greatest freight activity. The final confirmation to support this effort was the identification of the top industrial, manufacturing, and warehousing employers for their proximity to the freight activity. Access to freight-generating businesses was then evaluated at an intercity and intra-regional and by assessing network access to major industrial areas, warehouses, ports, rail yards, and distribution hubs. With use of Replica freight trip and volume data, the team directly analyzed trips between freight clusters and freight corridors. The analysis identified freight O/D pairs at the census tract level and by routing paths and access efficiency based on quantifying real-world access times to identify spatial clusters with poor intercity and regional connectivity. Using the shortest route tool in Google Maps, the team then identified inefficiencies in primary and alternative routes, such as circuitous routes, reliance on local roads, or access limitations. Freight volume, LOS, and congestion patterns were used to assess truck volumes and projected freight demand on key corridors. The NCTCOG TDM and/or Replica
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