VISUALIZING HUMAN SERVICE TRANSPORTATION TRIP DATA IN TIME AND SPACE
When demanding a more efficient public transportation system, Elected officials often talk of witnessing multiple paratransit or other accessible vehicles lined up on the curb in front of the Hospital, each picking up or dropping off a single passenger. The assumption that many elected leaders have is that vehicle capacity could be used more effectively if more customers were grouped. For years this has been the rationale behind major federal and state initiatives to improve coordination of human-service transportation programs. Indeed, much of my professional career has focused on implementing programs that improve coordination of limited transportation resources.
While I generally agree that HST programs often can be better coordinated, today I want to highlight an important piece of the puzzle that is often overlooked. In doing so, I hope to provide some tools for thinking more clearly about identifying opportunities to coordinate human service transportation programs.
MAPPING DATA IN TIME AND SPACE
Coordination is a multi-dimensional problem that takes place in both time and space. Sometimes transit planners create maps using Geographic Information Systems (AKA, GIS) showing the overlapping lines of passengers’ origins and destinations to demonstrate the extent to which trips overlap. Here’s an example showing one-day’s worth of trips from three human service transportation agencies in the Denver area:
The problem with these kinds of maps is that they only show one dimension of a multi-dimensional problem. Trips take place in both time and space. A map like this makes the problem look much easier to solve than it really is. While many of these trips appear to overlap with one another, only a small fraction of the trips happen in the same time and space.
A better way to represent this information is with a time-enabled map. Here’s a video showing a similar dataset, but this time, the data is represented over time.
As in the first map, each colored line represents a different agency’s customers. But this time, green and red dots are placed at the pick-up and drop-off points, respectively, to show direction of travel. The data is shown in sequential 15 minute slices of time. So, as before, we can see the spatial dimension of the data but also the temporal dimension and the direction of travel.
In order for HST agencies to coordinate trips, the other trip needs to be on the way. In order to determine if a trip is on the way, we need to know direction of travel and time of day. ESRI’s time-slider function provides a simple method for visualizing both time and space in GIS.
I made these maps using ESRI’s time-slider function in ArcGIS 10.1. This was accomplished by creating a time-stamp field in my spatial database and then animating the map in 15-minute intervals. If you are interested in seeing a step-by-step tutorial, let me know by leaving a comment.
POTENTIAL USES FOR TIME-ENABLED, SPATIAL MAPS
Here are at least two ways a map like this could be used:
Identifying ride-sharing opportunities: Historic or next-day data from HST providers can be observed to identify visual patterns for potential coordination opportunities. The human eye may be more effective at identifying opportunities for coordination than the best computerized ride-sharing algorithm.
Dispelling myths about the inefficiencies of HST services: When we see a line of vans at the hospital we tend to think what we are seeing is an inefficient system. What we cannot see from the curb is the other end of each of the trips. Time-enabled spatial maps enable us to visualize a much richer picture of the coordination landscape potentially leading to more accurate perceptions about the true opportunities to coordinate human service transportation programs.