Jump to the tool
So, you have some bus routes in your community, and they’re pretty popular. They run super efficiently and help a lot of residents get to the grocery store, to the office, and to other points of interest across town. Nice work! But busy routes aside, we bet that there are plenty of others that aren’t as bustling, commuter trains that could stand to carry some bigger crowds , or parts of your town that are just plain underserved. No city reaches every single resident with public transportation — and that’s a reality that on-demand technology can help solve. It’s time to work together on filling the gaps, and we built a cool tool to show you what it might look like.
First, some basics. Let's get started.
Ellie lives near a high-frequency bus route and wants to go to the grocery store, which is also on the bus route. She looks at the schedule, and the bus comes in five minutes. Easy! Ellie jumps on the bus and is grocery shopping in no time. But let’s be honest: Ellie’s ride was pretty unique. Not everyone lives a few steps from the most popular bus route in town. Moreover, Ellie travels to and from different places around town — it’s not always as simple as the ride to the grocery store. For most other trips, Ellie drives or hails a single-occupancy vehicle. But with an on-demand transportation network, Ellie could easily choose how to take mass transit anywhere in the city. Imagine two systems working together, automatically calculating which vehicle — an on-demand shuttle or a fixed-route bus — is best-suited to fulfill the trip request based on vehicle ETA, walking distance to the nearest bus stop, and other factors. Sam lives six blocks from the bus stop and wants to visit Ellie, who lives across town. He opens his transit app and calculates the route. With Sam’s office on a bus route, the app normally suggests taking the bus home from work. But the ride to Ellie’s place isn’t a straight shot, and even if it was, the next bus isn’t going to arrive for 20 minutes. A shared shuttle, however, is just eight minutes away, it can meet Sam a block from his apartment, and it’s carrying two other passengers headed in the same direction. The app suggests the shuttle, and Sam is rolling in no time. Ta-da! More efficient rides. Sam avoids driving to Ellie’s or hailing a single-occupancy vehicle. Plus, with the algorithm suggesting the best route, trips are not unnecessarily duplicated, thereby minimizing traffic, maximizing resources, and increasing overall system efficiency.
Time to go big.
Now let’s see how combining on-demand technology with fixed routes can work together at scale. We created this transit toy model to let you play around with visualizing your own transit network. Integrated transit systems work well, because they take what’s working and, simply put, make the overall network run even better. Using the tool below, you can see what a basic network might look like if it maintained one popular train or bus route, and then added on-demand microtransit to the mix. Use the sliders below to see how the new on-demand service might perform at various supply and demand levels, with representative limits on detours, fleet sizes, and vehicle capacities. [via-sim-embed id="tool_2"]
Your fleet, your rules.
- Buses: How many fixed route buses are in your public transportation network?
- Bus walk: How many minutes do you expect people to reasonably walk to a bus station? Passengers who are further away than your maximum walking distance will take an on-demand shuttle instead.
- Vans: How many on-demand vehicles are in your fleet?
- Demand: How many requests do you expect potential riders to make? Naturally, we want to be able to serve as many ride requests as possible.
So, how’d ya do?
Based on the choices you made when playing with the models, did you learn anything about how they affected the service? Here are a few things to consider:
- Wait time: How long did passengers have to wait for a ride given the level of demand and number of vehicles in your fleet?
- Rides served: How many people who requested a ride were given an option that they accepted, and then completed?
- Utilization (rides per vehicle hour): How efficient was the use of vehicles in your new on-demand fleet?
Now that you’ve scratched the surface, ready to learn more ? Using Via’s proprietary transportation modeling engine ViaViewer , we can work together to simulate a real microtransit deployment in your city. Together with the powerful ViaViewer engine, your knowledge of your community and our experience powering the most vehicles and with the largest number of rides delivered in the industry, we can build a real-world microtransit network that works.
Let’s start building.