Using GIS to Create Demand Response Service Schedule Zones and Times
Corresponding Author: Jeremy Scott, Institute for Transportation Research and Education
Presented By: Jeremy Scott, Institute for Transportation Research and Education
Abstract
Scheduling demand response trips on a daily basis can be a daunting and time-consuming task. GIS can be used to simplify this process by creating service schedule zones using the geographical features in a transit system’s service area. The spatial and temporal components of a rider demand can be leveraged to group trips together to create the service schedule times.
This presentation will describe the GIS tools and process that were used to develop the service zones and the timing of service to the zones. A GIS model was created that takes the geographic features in the service area, rasterizes the layers, and then sums the raster layers together to create a set of least cost paths that form the foundation of the zone boundaries. A python script was built to aggregate the ridership demand and calculate the optimal central zone. These two shapefiles are then combined together to create one set of zone boundaries.
After creating the zones, another GIS model was created to spatially join the zones to each customer’s origin and destination. The results of the spatial join are then used to create a matrix that aggregates the number of trips between every zone combination and the time of day. The final schedule is created by grouping trips that have origins and destinations that are spatially and temporally similar.
This method has been applied to Lee County, NC, where the transit system has experienced increases in administrative and operational efficiency as a result of the process. In addition, the customers are better able to visualize how transit operates in their community and plan their daily travel needs around the schedule.