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From page 15... ... 15 Based on the literature and industry knowledge, the major factors traditionally influencing transit ridership are changes in service levels, population, and transit-dependent population. For each mixed traffic and dedicated ROW cluster, a trend analysis was performed to examine the relationship between transit ridership and these three factors. Read the entire page →
From page 16... ... 16 Analysis of Recent Public Transit Ridership Trends particularly in the Rust Belt, have lost population. According to a study by Driscoll et al. Read the entire page →
From page 17... ... National Ridership Trends 17 Mixed Right-of-Way Cluster 3 -- Sprawling small towns Mixed Right-of-Way Cluster 4 -- Sprawling metropolis Mixed Right-of-Way Cluster 5 -- Dense metropolis Figure 6. (Continued) Read the entire page →
From page 18... ... 18 Analysis of Recent Public Transit Ridership Trends highly homogeneous. The 62% of regions that have less than a million in population and less than 5 million unlinked transit passenger trips seem to be uniformly distributed. Read the entire page →
From page 19... ... National Ridership Trends 19 Mixed Right-of-Way Cluster 3 -- Sprawling small towns Mixed Right-of-Way Cluster 4 -- Sprawling metropolis Mixed Right-of-Way Cluster 5 -- Dense metropolis 2012–2016 % Change in Population 2012–2016 % Change in Population 2012–2016 % Change in Population Figure 7. (Continued) Read the entire page →
From page 20... ... 20 Analysis of Recent Public Transit Ridership Trends all grew by less than 7%. In both clusters, however, transit ridership change seems unaffected by the decline in population. Read the entire page →
From page 21... ... National Ridership Trends 21 Mixed Right-of-Way Cluster 1 -- Mid-sized transit-oriented 2012 % Zero-Vehicle Households 2012 % Zero-Vehicle Households 2012 % Zero-Vehicle Households Mixed Right-of-Way Cluster 2 -- Mid-sized auto-oriented Mixed Right-of-Way Cluster 3 -- Sprawling small towns Figure 8. Transit ridership vs. Read the entire page →
From page 22... ... 22 Analysis of Recent Public Transit Ridership Trends Besides these outliers, there is a slight positive trend in all three clusters. However, it is apparent that the proportion of zero-vehicle households accounts for a small share of variation in transit ridership. Read the entire page →
From page 23... ... National Ridership Trends 23 Unlike the 2012 analysis, there is a relationship between the change in transit ridership and the change in zero-vehicle households in Cluster 4 (sprawling metros) and Cluster 5 (dense metros) Read the entire page →
From page 24... ... 24 Analysis of Recent Public Transit Ridership Trends Mixed Right-of-Way Cluster 4 -- Sprawling metropolis Mixed Right-of-Way Cluster 5 -- Dense metropolis Mixed Right-of-Way Cluster 3 -- Sprawling small towns 2012–2016 % Change in % Zero-Vehicle Households 2012–2016 % Change in % Zero-Vehicle Households 2012–2016 % Change in % Zero-Vehicle Households Figure 9. (Continued) Read the entire page →
From page 25... ... National Ridership Trends 25 Transit Service -- Mixed Traffic Modes The amount of service provided is one of the few levers available for transit agencies to affect ridership. It is therefore important to evaluate the relationship between ridership and service levels both at a point in time and as a change over time. Read the entire page →
From page 26... ... 26 Analysis of Recent Public Transit Ridership Trends Mixed Right-of-Way Cluster 1 -- Mid-sized transit-oriented Mixed Right-of-Way Cluster 2 -- Mid-sized auto-oriented Mixed Right-of-Way Cluster 3 -- Sprawling small towns Figure 10. Transit ridership vs. Read the entire page →
From page 27... ... National Ridership Trends 27 There are, however, outliers such as Chico, CA; Huntsville, AL; and Elizabethtown, KY, where ridership increased despite slight reductions in transit service levels and regions such as Fayetteville, MO; Baton Rouge, LA; and Port St. Lucie, FL, where vehicle revenue miles increased by more than 75% but transit ridership did not substantially increase. Read the entire page →
From page 28... ... 28 Analysis of Recent Public Transit Ridership Trends Mixed Right-of-Way Cluster 1 -- Mid-sized transit-oriented Mixed Right-of-Way Cluster 2 -- Mid-sized auto-oriented Mixed Right-of-Way Cluster 3 -- Sprawling small towns 2012–2016 % Change in Vehicle Revenue Miles 2012–2016 % Change in Vehicle Revenue Miles 2012–2016 % Change in Vehicle Revenue Miles Figure 11. Change in transit ridership vs. Read the entire page →
From page 29... ... National Ridership Trends 29 downward with San Bernardino, CA, which increased vehicle revenue miles by 28%, still losing 11% of ridership. Regions in Cluster 5 exhibit no relationship between change in transit ridership and transit service levels. Read the entire page →
From page 30... ... 30 Analysis of Recent Public Transit Ridership Trends Ridership Trends Analysis for Dedicated Right-of-Way Modes In this section, the analysis of population, zero-vehicle households, and service levels in 2012 and the changes in each from 2012 to 2016 is repeated for dedicated ROW transit modes. A critical difference with mixed traffic modes is that regions operating transit in its own lane are typically much larger and there are a limited number of regions operating dedicated ROW. Read the entire page →
From page 31... ... National Ridership Trends 31 rider ship and change in population is also moderately strong. Except for Minneapolis, MN; Seattle, WA; and Houston, TX -- which have expanded their rail systems -- ridership and population change seems to have a linear and positive relationship across clusters. Read the entire page →
From page 32... ... 32 Analysis of Recent Public Transit Ridership Trends Vehicle Revenue Miles -- Dedicated Right-Of-Way Modes Transit agencies have relied on dedicated ROW modes in recent years to increase transit ridership. Between 2012 and 2016, total transit vehicle revenue miles in the United States have increased by 7.5% for dedicated ROW modes. Read the entire page →
From page 33... ... National Ridership Trends 33 Figure 16. Transit ridership vs. Read the entire page →
From page 34... ... 34 Analysis of Recent Public Transit Ridership Trends to the 265% increase in transit service. Seattle, WA, and Minneapolis, MN, had much greater gains in ridership for more modest increases in service. Read the entire page →
From page 35... ... National Ridership Trends 35 change in population for dedicated ROW modes because these modes provide a fast and reliable service, which is more competitive with private vehicles in congested cities. While there is a clear relationship between transit ridership and transit service levels at a point in time for both mixed traffic and dedicated ROW modes, the change in ridership is much more closely associated with change in service levels for dedicated ROW modes than for mixed traffic modes. Read the entire page →

From page 15...

... 15 Based on the literature and industry knowledge, the major factors traditionally influencing transit ridership are changes in service levels, population, and transit-dependent population. For each mixed traffic and dedicated ROW cluster, a trend analysis was performed to examine the relationship between transit ridership and these three factors.