Congestion Pricing - Links to Congestion Pricing Home
< Previous | Table of Contents | Next >

4.0 DATA ANALYSIS

The transit test plan focuses on collecting and analyzing bus ridership, park-and-ride lot, and travel-time and on-time performance data. Historical, pre-deployment, and post-deployment data will be used to assess the transit analysis measures of effectiveness. The transit data will also be used in the congestion and other analyses. The data will also be used in combination with survey and focus group results to analyze mode change. Information on the surveys and focus groups is presented in the Minnesota UPA National Evaluation Surveys, Interviews, and Focus Groups Test Plan.

The bus ridership, travel time and on-time performance, and park-and-ride lot use data available from Metro Transit and MVTA reflects a high level of accuracy. Both transit agencies use the data on a regular basis. As a result, both Metro Transit and MVTA personnel inspect the data for outliers and suspect data. Suspect data is checked against other information. For example, Metro Transit personnel use fare collection information to check any suspect APC data. Outliers and suspect data are flagged and discarded or adjusted as appropriate.

Members of the national evaluation team will conduct a second visual inspection of the data received from Metro Transit and MVTA. Any identified concerns will be discussed with Metro Transit and MVTA personnel, and appropriate actions will be taken to adjust or discard suspect data.

Standard statistical techniques will be applied to measures of effectiveness calculated using the transit data. Measures will also be compared with control routes and park-and-ride lots. Examples of measures to be used in the transit, congestion, and other analyses are discussed below.

  • Total ridership by trip. The total ridership by trip on routes will be examined pre- and post-deployment.
  • Total ridership by route. The total ridership by route will be examined pre- and post-deployment. New trips that are added to a route will be documented. Comparisons will also be made with system-wide changes in ridership.
  • Change in ridership by trip. This measure, which is calculated as the total and percentage increase or decrease in ridership by trip, will be computed and compared pre- and post-deployment.
  • Change in ridership by route. This measure, which is calculated as the total and percentage increase or decrease in ridership by route, will be computed and compared pre- and post-deployment.
  • Total utilization of park-and-ride lots. The total number of cars parked at the park-and-ride lots recorded in the one-weekday counts will be compared pre- and post-deployment, along with analyzing historical trends.
  • Change in utilization of park-and-ride lots. This measure, which is calculated as the increase or decrease in use of the park-and-ride lots, will be computed and compared pre- and post-deployment. Park-and-ride vehicle counts will also be compared to bus ridership data from the same park-and-ride lot to calculate any increase in bus riders who access transit by other modes, including carpooling to the park-and-ride lot, being dropped off, walking, and bicycling. Comparisons will also be made with changes in the regional park-and-ride lot use.
  • Bus travel time by trip. Bus travel times per trip will be analyzed pre- and post-deployment.
  • Changes in bus travel time by trip. Changes in bus travel times will be calculated pre- and post-deployment.
  • Changes in bus on-time performance. Bus on-time performance will be recorded and compared pre- and post-deployment. At the simplest level, the number of buses categorized as late arriving in downtown Minneapolis will be examined pre- and post-deployment. More detailed analysis will be conducted using the AVL data from different routes.
  • Changes in bus on-time performance by trip. The change in bus on-time performance by trip will be calculated and analyzed pre- and post-deployment.
  • Changes in bus running times in published schedules. The changes in times in the published schedules will be compared pre- and post-deployment to identify any reductions in travel time realized from the UPA projects.
  • Transit mode share. Ridership data is needed for the calculation of transit mode share. Transit mode share is measured in terms of the proportion of total person throughput carried in the corridor by transit services versus other modes. Person throughput measurement requires obtaining samples of Average Vehicle Occupancy (AVO) data, which is multiplied by associated traffic volumes to obtain person throughput. Thus, transit ridership counts are required for the route sections and time periods covered in the AVO sample process.

The transit ridership data will be aggregated by freeway and roadway segment and by the morning and afternoon peak hours and peak periods for use in the transit analysis, the congestion analysis, and other analyses. The freeway segments include I-35W north of downtown Minneapolis, I-35W south of downtown Minneapolis, and Cedar Avenue. The definition used by Metro Transit for the morning and afternoon peak periods are 6:00 a.m. to 9:00 a.m. and 3:00 p.m. to 6:30 p.m. The transit ridership data will be used in the calculation of average vehicle occupancy (AVO) levels, person throughput, and other related measures in the congestion analysis.