If you look at any transit map for any agency you’re going to see routes that just don’t make sense. Why doesn’t that bus stop closer to the school? Why aren’t there accessible stops near the hospital? What is this loop around…nothing?
And the answer is always the same—the routes haven’t been updated for years. Why haven’t routes changed? Because it’s a herculean task to figure out how to take what you have now, make it into something better, without triggering a domino effect of problems down the line. As one agency put it to us, they just couldn’t wrap their heads around even where to start much less how to get there.
And the biggest challenge is getting a handle on all the data feeding into the system and using it to make data-driven decisions and not let the loudest voices get the best routes.
With the right data and the right tools to understand the data; the job is still hard, but it’s a lot less daunting. Modern, transit-oriented data analysis tools make it a lot easier to see where buses are missing each other by a few minutes or what are the real causes of On Time Performance and Service Delivery issues. And most importantly, be able to clearly present the data and decisions to all your stakeholders so everyone understands how you came to your conclusions.
Listen to our whole conversation on Inside Trapeze with Tris Hussey:
No community stays the same forever. Sure, established neighborhoods might be in the same places, but now your city has sprawled across more of your city and neighboring towns. Now you need to deal with people coming into new and different parts of your city as the “downtown core” is less important than outlying areas.
Maybe the old industrial area is a new riverside neighborhood with homes, schools, businesses, and entertainment. Or the factory that used to bring hundreds of people into one part of town is gone, but your buses still go there and circle empty buildings.
As your community changes, service needs to change too. New fixed-route lines, introducing light rail, adding bus rapid transit to accommodate where people live, work, learn, and play. This is the goal for any agency—give the community a public transit system that gets them where they need to go.
But that’s easier said than done, right?
Where is there extra capacity in the system? How has your population and land use changed over time? What’s the same and what’s different? Can you just add more buses or do you need to reimagine how your system and agency serve your community?
Planners and schedulers need to answer these questions before they can begin their work, but getting those answers is the tough part. Getting to these answers relies on integrating more datasets with your transit data to understand your community today and tomorrow.
And then being able to look at the data in new and useful ways.
When you look at how your routes are performing, a lot of agencies look to On Time Performance (OTP) as the key measure. When a route’s OTP starts dropping, are you only seeing a symptom and not the real cause? You see buses are off schedule at this stop, but why? Is the problem at that stop or the one before it? You adjust the schedule to get things on track, but things only get worse. When you look at a service delivery report, you see you’re only at 70%. Some stops are missed and runs get so off kilter the only option is to skip stops and start over few hours. Why?
Getting to these answers means going beyond the simple, surficial answers and looking at your run cuts and blocks. It’s looking at data from “problem” stops and all the stops before it to see how something as simple as school letting out slows down a bus leaving a stop.
It comes down to putting the community data with route data with driver schedules to stop-level data to uncover what’s going on and what to do about it.
It’s going beyond symptoms to digging out the root causes of route problems.
We’ve all seen transit maps that look like tangled spaghetti. Routes go all over the map, cross over and around each other, and sometimes don’t seem to make sense where they are actually going. The goal is untangling the route spaghetti and making a system that works smoothly and efficiently for as many people as possible. You don’t want buses going to areas without riders. You don’t want people to miss convenient connections by a couple minutes and need to wait 15, 20, 30 minutes for the next bus.
Riders want fast, efficient rides with the fewest transfers and least amount of waiting.
We know how route spaghetti happens. A community lobbies for a stop around a community center or shopping or a school. Then those schools and stores and community centers close or move. Or a stop is moved for a construction project that never happens. Routes are added, changed, and adapted for valid reasons, but as time has passed and those reasons aren’t valid anymore.
The routes that made sense 20 years ago, are layered with routes from 10 years ago, and maybe even historical routes that date back to horse-drawn trollies or train schedules. Over time you have a mess that no one can really understand, everyone knows is inefficient, but no one can justify the time and resources to fix it.
As cities like Baltimore, New Orleans, and New York City found, wiping the map clean and starting over is sometimes the only choice. Maybe that’s for the best, but not something you can do often. That’s a once a decade kind of project. Then the question becomes, once we untangle our route spaghetti, how do we maintain it?
Instead of repeatedly hitting the route and schedule reset button, it’s better to make small, incremental changes to your schedule. Maybe you’re fixing route spaghetti all at once and want to adapt more organically. Maybe you can’t fix the whole thing, but you want to make slow and steady progress over time.
Trapeze Mobility Planning and Scheduling (MPS) and ViewPoint let you organize and make sense of all the data from your communities, your routes, your schedules, then start to iterate your schedules. Try fixing operator break times and see if that helps service delivery. Adjust timing of buses around schools and shift changes to account for brief ridership peaks. Get rid of regular service to a less traveled area, but replace it with microtransit so the people who still rely on the old route can make connections to important transit hubs.
Once you can model what service could look like, you have the power to create new opportunities for your communities.
This is all fixing the right now and escaping the past, but what about tomorrow? What will the region look like in 5, 10, 20, 30 years? What can you project into the future with some certainty so you can make real decisions today that won’t be tomorrow’s route spaghetti?
Connecting your demographic data with analytical models give you tools for all your “what if…” questions. You can look at solutions based on various scenarios and create long-term plans from those. How will population growth and development influence converting to a zero emissions fleet? Are your plans for how many buses you need going to hold up? Will adding light rail connecting communities be more cost-effective than creating a bus rapid transit solution in the same are? Could microtransit bridge a gap while demand increases for regular fixed-route schedules?
These are the answers that ViewPoint and MPS together can model and present to everyone from internal stakeholders to the public with confidence.
We all want to do our jobs better. We want to find the answers to the questions that let us create the public transit system the community will use because it’s fast, efficient, and convenient. And to do all this you need to go beyond static reports. You need to move from one-size-fits-all dashboards to data analysis solutions you can mold and adapt to your needs.
Combining ViewPoint with MPS…and then with EAM, MOD, and WM give you unparalleled analysis tools you will enjoy using. You’ll be able to ask real questions and find real answers, without spending days just getting your data in order.
Go from “I’ll get back to you with that answer” to “I have that answer right here” without needing a degree in data science or fighting with spreadsheets.
Learn how we can bring your planning and scheduling to the future of transit.
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