TransLoc

A 40 percent fare increase. A 7 percent revenue gain.

That's what new peer-reviewed research (Wake Forest University) found when it modeled a real fare increase on an on-demand transit system, using actual rider-level data instead of a system-wide average.

The reason the math doesn't work: occasional, price-sensitive riders cut their trips substantially. Frequent riders barely change behavior. The losses from one group eat up most of the gains from the other.

The most striking part: total ridership looked stable the whole time. Underneath that flat number, existing riders were leaving and new riders were replacing them, a shift a system-wide dashboard would never catch.

Before raising fares, it's worth modeling the rider-level impact, not just the projected revenue.

Learn more: https://transloc.com/blog/what-a-40-fare-increase-actually-buys-a-transit-agency/

Fixed Route or OnDemand Microtransit? The honest answer: they solve different problems.

Fixed Route works where density and predictable travel patterns support it. OnDemand Microtransit earns its keep in low-density areas, first/last-mile gaps, and overnight windows.

Get the fit wrong, and the data shows it: one pilot hit a fraction of the ridership needed to justify a bus route; another saw its subsidy nearly triple.

We built a five-question framework for making this call with data, not guesswork.

Learn more: https://transloc.com/blog/fixed-route-or-ondemand-microtransit-a-decision-framework/

Not every transit route is a loop.

Many agencies operate services that travel inbound to a destination and outbound on a separate return path. The challenge is making sure operational systems, rider information, and GTFS data accurately reflect how service actually runs.

Our latest blog explores why supporting inbound and outbound routes matters for:

✅ Clearer rider communications
✅ More accurate route representation
✅ Better operational visibility
✅ Consistent GTFS and real-time data

In our experience, the best transit technology adapts to how agencies run service, not the other way around.

Learn more: https://transloc.com/blog/inbound-and-outbound-routes-for-transit-agencies-fixed-route-operations/

A great milestone and an even better example of teamwork.

Recently, teams across TransLoc and our partners collaborated to support a significant project for one of our partner. Getting everything aligned required a tremendous amount of coordination, problem-solving, testing, and persistence.

Projects like this remind you that successful deployments are never the work of one person. They are the result of people with different expertise working toward the same goal.

A huge thank you to our partner for the collaboration, dedication, and effort that helped make this milestone possible.

It's always rewarding to see months of work come together and create something that will support customers today and future deployments down the road.

TransLoc Introduces Long Wait Time Prevention for Transit Agencies

A rider arrives at a stop expecting a bus in a few minutes. Ten minutes later, they're still waiting.

The challenge for many agencies is not knowing that long wait times are a problem. It's identifying where they are happening before they become rider complaints, service reliability concerns, or performance issues.

Our latest blog explores practical ways agencies can use long wait time insights to:

✅ Identify service gaps earlier
✅ Prioritize operational improvements
✅ Improve visibility into rider experience
✅ Support more informed planning decisions

Because reliability is often judged by one simple question:
How long did the rider wait?

Blog: https://transloc.com/blog/long-wait-time-prevention-for-transit-agencies-improve-service-reliability/

Press Release: https://transloc.com/press/long-wait-time-prevention/

TransLoc

Dwell Time Best Practices: Turning Stop-Level Data into Better Service Decisions

A route may appear to run late. The assumption might be traffic. The actual issue might be recurring dwell delays at a handful of high-volume stops.

That is why dwell time matters. Not because it is another metric to track, but because it often explains where reliability starts to break down. Our latest blog explores practical ways transit agencies can use dwell time data to:

- Identify stops creating the biggest delays
- Validate schedule assumptions
- Improve route planning decisions
- Reduce manual reporting and analysis

Better visibility leads to better conversations. Better conversations usually lead to better service.

Learn more: https://transloc.com/blog/dwell-time-best-practices/

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TransLoc has introduced Driver–Dispatch Text Chat (MDT Integrated) within the Driver App, strengthening communication between dispatchers and drivers across fixed route operations.

Communication is a core part of daily service delivery. When it breaks down, the impact shows up quickly during service changes, disruptions, and time‑sensitive updates.

By bringing messaging directly into the Driver App, agencies can improve coordination while keeping communication aligned with existing workflows.
This capability is part of a broader system that brings together DAPC, Driver–Dispatch Text Chat, Schedule Adherence, and Anti‑Bunching in a single workflow.

- Read the Press Release: https://transloc.com/press/driverdispatchchat-driverapp/
- Read the Blog: https://transloc.com/blog/why-driverdispatch-communication-breaks-down-in-daily-operations/
- Learn more about the Driver App: https://transloc.com/solutions/driver-app/

TransLoc at IPMI today.

A lot of the conversations here feel familiar. Teams trying to keep service consistent while everything behind the scenes gets more complex. It usually shows up in small ways. Different answers depending on where you check. Riders asking the driver instead of trusting the system. That gap is what we’ve been talking about.

If you’re here, stop by Booth #627.

Gina Shurtz and Daniel Agerter are there today and tomorrow. Worth comparing notes if you’re working through the same things.

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