Origin-Destination Pairs are the foundation of so many of the analyses completed by transportation planning professionals. When we designed and built our newest app, the OD Flow Explorer, which is launching this week, we aimed to solve 3 distinct challenges we heard from customers around the country:
- Turning individual trip data into OD tables and matrices for a desired set of census or custom geographies can be time consuming and tedious work.
- Often, the OD data provided by data companies does not have the additional detail — breakdowns by mode, purpose, time of day, or trip taker income — that would enable the type of detailed analyses, like equity studies, that agencies are currently prioritizing.
- Obtaining insight from OD data, as well as using it in presentation and reports, requires turning it into compelling visualizations.
With the OD Flow Explorer, we’re addressing each of these pain points. The App quickly visualizes up to hundreds of thousands of OD pairs in an interactive map-based interface, and incorporates all of the custom geography and trip filter features available in the Replica platform. Both the data and the map can be downloaded, and individual analyses can be shared with other team members.
To demonstrate the power of this tool in action, we’ve generated side-by-side maps comparing OD flows for automobiles vs. public transit in 2 different cities from around the country. These types of analyses can support the hundreds of bus network redesigns happening around the country to adapt transit agencies and their service for a post-pandemic world.
Pittsburgh: Even just a quick glance between the automobile and public transit ODs in Pittsburgh show clear differences. While both maps show more activity between Downtown and the East side, it's easy to see how concentrated transit trips are in just a few census tracts, as well as to identify high-priority areas for new transit lines.
Oahu: In Oahu it's clear how concentrated transit trips are both in downtown Waikiki, and in Wahiawa in the middle of the island. The map highlights areas where additional transit might relieve some of the country's worst congestion.
We're excited to explore a whole range of use cases with customers with this tool going live. Here's a few we are most excited about:
- Mode Shift: Identify and visualize high-volume car OD pairs that are 1-3 miles in distance and are good candidates for active mode shift
- Transit Effectiveness: Compare car and transit ODs by top percentile trips to find mismatches and identify latent transit demand
- VMT Analysis: Use OD flows split by trip purpose to identify pairs where commutes are causing a disproportionate impact on an area's VMT
If you'd like to pilot these use cases, or one of your own priorities with which this tool could help, reach out.
