Master Transportation Plan Task 4: Gap Analysis and Needs Network
destinations were selected based on their significance to the community: • High schools • Universities and college campuses • Veterans’ health administration and medical facilities • Nursing homes • Hospitals • SNAP retailers • Employers
Using a custom Python script, the number of these key destinations in each walkshed (0.25 mile, 0.5 mile, and 1 mile) was quantified. In addition, the population of each block group intersecting the walksheds was calculated to understand how many residents were potentially affected by access conditions. 3.5.2.4.3 Identifying Transit-Supportive Areas To determine where transit demand may be highest, the analysis identified transit-supportive areas based on population density. Using 2023 census data, population densities were calculated at the block group level and categorized into quartiles. Block groups in the top quartile were defined as those exceeding 6,200 residents per square. 3.5.2.5 Evaluation of Transit Network Performance Beyond spatial and temporal coverage gaps, evaluating the performance of the existing transit network helps identify opportunities to improve efficiency, reliability, and rider experience. This assessment examines how well the current network is functioning using a series of key performance metrics, with a focus on identifying underperforming routes, zones, or service patterns. These metrics also provide a basis for benchmarking Fort Worth’s system against peer transit agencies to understand how Trinity Metro compares and where improvement is most critical. 3.5.2.5.1 Peer Benchmarking As part of this evaluation, Trinity Metro’s performance was compared to a set of peer transit agencies of similar size, operating context, and ridership profile. Benchmarking offers insight into how Fort Worth’s system performs relative to those of its regional partners, and it helps set realistic targets for improvement. The agencies chosen for this review were: • DART, Dallas, TX
• CapMetro, Austin, TX • VIA, San Antonio, TX 3.5.2.5.2 System Productivity
System productivity was assessed by comparing the number of unlinked passenger boardings per revenue service hour across each agency and mode. This metric reflects how efficiently each system
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