Archived Posts

At the beginning of 2021, we took a broad look at ridership throughout 2020 to identify some of the changing trends we were seeing due to the COVID-19 pandemic. We wanted to do this at the end of 2021 as well, but just as things seemed to be reaching a steady state, the rise of the Omicron variant caused another drastic change in ridership trends. These trends steadied out through June 2022, then became greatly impacted by various service disruptions. Therefore, we decided to take a look at ridership again up to June 2021 to explain some of the data and give some thoughts about what we might expect going forward.

How can we understand the demographics of riders across our system, to make equitable transit decisions? Depending on resources available, there are multiple methods transit agencies can use to try to estimate their ridership demographics, both to comply with Title VI and supporting policies and to make better decisions about their system regarding equity. A previous post, "Does U.S. Census Data Predict MBTA Bus Ridership?", summarizes a project which compared the two most common ways transit agencies can estimate ridership for minority and low-income riders: either by conducting a passenger survey to collect demographic information from a sample of riders or using U.S. census data to estimate ridership based on the residential demographics of surrounding stops and routes. Conducting a passenger survey has been – and as confirmed by this blog post is still – the preferred method to understand rider demographics. However, the MBTA continues to use census data as an estimate for certain applications, as it is more easily accessible and less resource-intensive compared to the rider census survey.

The Massachusetts Statewide Bicycle Survey was conducted over the Summer of 2021 to get a holistic picture of the state of biking across Massachusetts and how it was affected by the Covid-19 pandemic. We were interested in how, when, and why people biked both before and during the pandemic, and how they imagined their biking behavior changing in a post-pandemic world. This survey, which was distributed via flyers, email, and word of mouth in partnership with many community organizations, ended up receiving more than 7,000 responses. The respondents were clustered around the immediate Boston area, but we heard from people in nearly every part of the state, and the breadth of responses allowed us to examine how biking differs from region to region.

The MBTA strives to provide good service to riders, but what does providing “good service” really mean? In this post, we will explore this concept as it relates to bus service. For over a decade, the MBTA has been redefining our approach to “good bus service” to better capture the benefits bus service can provide for our riders. We have refined our approach to understanding and measuring this by incorporating additional benefits that a bus route can provide to both passengers and the MBTA system as a whole.

Thank you for taking our second Station Prints Quiz! Let’s take a look at the answers to see which station matched which prints.

OPMI is proud to release the first-ever MBTA Service Delivery Policy Annual Report.

Here on the Data Blog, we previously posted a station prints quiz where readers were given daily ridership graphs for anonymous stations and tasked with identifying which station the graph belonged to (we also provided the answers). With new travel patterns emerging because of the pandemic, we would like to put our readers’ subway knowledge to the test again with another quiz.

Greater Boston's makeup has changed significantly in recent years, with shifting demographics, emerging employment districts, increasing traffic congestion, and changing travel patterns. Meanwhile, up until recently, much of the MBTA bus network had not seen any changes since the 1960s. To remedy this, the MBTA created the Bus Network Redesign, an initiative that aims to completely re-imagine the  bus network to better reflect the travel needs of the region and create a better experience for current and future bus riders.

The COVID-19 pandemic has greatly impacted transit use, changing trends that were previously well-established and static over time. These circumstances have necessitated a new look at our data to investigate transit changes in a thoughtful way. This post will focus on how we’re thinking about changing ridership trends...

While we have focused primarily on transit ridership on this blog, the pandemic has significantly affected all transportation modes. One interesting case is the effect of the pandemic on biking. A so-called “bicycle boom” has been observed during the pandemic so far, as bicycle demand seemed to increase greatly throughout Massachusetts...

We are proud to release the 2021 version of Tracker.

While ridership remains far from normal, the return to fare collection provided a natural experiment for learning more about how the system is being used and how passengers respond to fares.

A summer 2020 update on ridership overall, with a particular focus on the work we are doing on the data and technology side to better capture bus ridership.

Due to the current COVID-19 pandemic, many of our usual frequent riders have stopped taking the MBTA. As a result, until service and ridership have begun to return to normal, we will be reporting customer satisfaction differently.

Early April 2020 update on the effect of the COVID-19 pandemic on MBTA ridership.

This post looks back at the week of 3/16/2020, when major changes in ridership due to the COVID-19 pandemic began to occur.

An early look at changed to ridership due to the COVID-19 pandemic, as of March 19, 2020.

This year, MassDOT released new Statewide Bicycle and Pedestrian Plans with the goal of increasing the comfort, safety, and convenience of biking and walking for all people. One key piece of both plans is making it easier for people to access transit.

After the unfortunate derailment on the Red Line in June 2019 that drastically affected service throughout the summer, we visualized how ridership on the line had been impacted.

Substitution, as it relates to walkability, is defined here as the propensity at which passengers exclusively choose a particular route over other nearby alternative routes. Substitution explains differences in how passengers choose to access MBTA services.

Studies of walking distances of different subway networks have found that walk distances vary considerably from station to station. In this blog post, we explore how walk distances may vary from station to station in our MBTA network

Public transit is one of many solutions that can help us reduce our collective transportation emissions. One of the ways that the T works to get people out of single occupancy vehicles and onto trains and buses is through our Perq program, formerly known as the Corporate Pass Program.

When you separate buses from mixed traffic, you can both improve the speed of bus travel along the corridor and decrease the variability of run times, both of which make taking the bus a more competitive option with driving, and over time, you can not only improve the experience for passengers but also attract more passengers to the bus. We take a look at how well these interventions have met these goals.

This post will discuss the methods we use to count riders and trips, and to estimate those we can't directly count. We will also discuss some of our future plans for improving these estimates and our reporting.

This article analyzes the changes in ridership from fiscal year 14-15.

In the last five years, the MBTA and other large transit agencies across the country have seen drops in their ridership, especially on buses and during off-peak times. This is counter to historical trends; given increased population and economic growth in Boston, we would typically expect ridership to increase.

Estimating passenger walk time impacts, transfer time impacts, stranded passengers, and impacts across the day.

An explanation of the methodology the MBTA's Service Planning Department used to estimate the impacts on riders of the 47 Better Bus Project proposals affecting 63 bus routes.

Estimating ridership impacts and calculating net impacts.

How one-time events like parades and the calendar influences ridership numbers.

So, you have some stop-level data...

Detailed data about declining MBTA bus speeds and next steps being taken to reverse this trend.

How will the upcoming fare collection system, AFC 2.0, affect the cash/ticket surcharge?

In the spring of 2018, the MBTA temporarily closed Wollaston Station for construction. Where did all the old Wollaston riders go?

This post explains changes to the real-time data feed for heavy and light rail vehicles made on September 12, 2018 impact our reliability performance measure.

Long cross-town routes with multiple transfer/connection options tend to be likely to have different riders along the routes, with relatively few people riding the entire length of the route. We evaluate whether it makes sense to treat these routes as a single service, or at the segment level.

Because service disruptions can be complex and tend to unfold over time, there is a constant trade-off between the timeliness of sending the alert and the accuracy of the estimated length of impact to service. We discovered through customer feedback, including in our monthly satisfaction survey, that our passengers were relatively dissatisfied with our approach.

In collaboration with the Boston Area Research Initiative, the MBTA is holding a data challenge to see how students and researchers can creatively use the survey data to answer research questions. The winners of the data challenge will be invited to present their work at the BARI Spring 2018 conference on April 27th, 2018.

The MBTA, working with the Central Transportation Planning Staff, has just completed a systemwide passenger survey to collect necessary passenger demographic data for bus routes and rail stations. This project updates the 2008-2009 dataset and will be used for service planning, ridership analysis, and Title VI equity analyses.

How to measure equity on high ridership bus routes.

This post explains a change we just made to Green Line data that impacts our performance measures.

Investigation into bus ridership changes using regression analysis.

Explaining how a "perfect" chart came together.

Answers to the MBTA Station Prints Quiz!

An analysis of bus crowding by street as opposed to bus route.

Can you identify an MBTA station by its boarding print?

This post describes the technical details of tracking Green Line vehicles. The final output is included in the larger MBTA passenger data which feeds the new MBTA.com as well as apps like the Transit app. Read more about the format of the data at the MBTA Realtime portal.

The MBTA and BostonBRT piloted all-door boarding on the Silver Line 4 and 5. Here are the results!

Investigating the changes in short fares paid on-board buses after the cash fare was reduced from $2.10 to an even $2.00.

The MBTA is developing a new Service Plan focused on improving our bus routes to better meet our customers' needs. For the first time we now have much better data about how passengers are using the bus and rapid transit network from our Origin Destination Inference model (ODX).

This article is a comparison of month to month usage of ridership across multiple modes.

How the net cost of a bus route is calculated.

The MBTA sees thousands of visitors during major events, like the Patriots Victory Parade, St. Patrick's Day Parade, and Boston Marathon. We know during these events we will have higher than normal ridership. Fortunately, most of these events have happened before, so we have data to work with.

An analysis of frequency and convenience of transit for overnight service.

An analysis of frequency and convenience of transit for overnight service.

This article is an analysis of the green line reliability slump in February of 2017.

An investigation into fare payment transaction times and their effect on reliability and service times.

A survey of overnight bus service using customer behavior and preferences.

Using data to make decision on whether a dedicated bus lane should be proposed in various areas across the greater Boston area.

How the measure for bus crowding was decided and how it is calculated

Insight into providing 7 day charliecards which would reduce maintenance costs overall.

Analysis of how close a tranist station is in regards to walkability.

Analysis of how much fare is lost on the green line during peaks hours when the rear doors allow passengers to board without first paying.

Analysis of why the commuter rail has the lowest satisfaction rates compared to buses and light rail.

Analysis of Youth Pass Pilot which increased ridership by a large amount.

Conclusion that ridership behaviors may have changed regarding gov't centers closing, but will eventually return.

10% improvement on reliability for non-peak hours.

Analysis of how customers use tools to decide their route to destination through different modes.

Chart from fiscal and control board that shows the usual load at each station on orange line.

Panel used to determine at what point people will stop boarding a vehicle due to crowding.

An explanation of how the MBTA tracks vehicles using GPS and other various tools.

A look into the types of fares purchased at various stations and what that data may suggest.

In this article we investigate the drop in riders from FY 2008 to FY 2015.

In this article we address the problem of knowing, with precision, the final destination of riders

A detailed look into the analysis behind the customer surveys produced by the MBTA.

A detailed look into the analysis behind producing charts to accurately portray complex data.

How is ridership data collected?

How do we know what customers think? How does the MBTA Panel Survey work?