For Boston’s long over-due comprehensive bus network redesign, Arup used a parametric modelling process, unprecedented in transit planning. This data-driven approach supported an exhaustive redesign that brings bus service to hundreds of thousands of new, underserved residents.
Cities across the US are re-evaluating their bus networks, often discovering their long-standing routes haven’t kept pace with changes in demographics and area growth. The Massachusetts Bay Transportation Authority (MBTA), which serves the Greater Boston Region, recognized discrepancies between their bus service and changed ridership needs as the area transformed over the years. The agency realized that a comprehensive overhaul of the system could improve bus service efficiency and frequency while also drive social and economic change across the region.
In 2018, the MBTA engaged Arup, Cambridge Systematics and Regina Villa Associates for a planning study and a network redesign that would better align the bus system with the region’s contemporary and future needs, and would focus on providing more equitable transit access. The agency specifically wanted a data-driven process that would enable a blank-slate redesign founded on unbiased, information-rich decision making. The project addresses the population’s local and regional bus needs for a system that serves more than 50 cities and towns, and represents more than a third of all MBTA trips with 400,000 riders each day.
The magnitude of the enterprise and the MBTA’s data-driven expectations led Arup to re-evaluate conventional transit planning processes and follow an unprecedented approach using a parametric model. The first such application for a major transportation planning project, this process enabled the team to comprehensively assess transit needs by evaluating millions of trips across all transit modes in the region. The model then successively created improved data sets according to MBTA goals, evolving to produce the best possible combination of routes for its bus network. The scale of statistical ground covered by the parametric model would have been impossible to approximate using a conventional planning approach.
The resulting proposed Bus Network Design is an exhaustive reimagining of the MBTA bus network. It increases bus service by 25%, bringing high-frequency service to hundreds of thousands of people, including new access for 115,000 residents of color and 40,000 low-income households. Following adjustments from public input through summer 2022, the new network will be implemented in several phases beginning in spring 2023 through 2028.
25% increased bus service across the network
225,000 more residents to access high-frequency service
40,000 low-income households with new bus access
Although US cities have changed significantly from the early 20th century, to this day many metropolitan bus networks across the nation largely follow routes established decades earlier by the first trolley lines. Since a number of municipalities typically make up a region, transit funding and decision making is often similarly segmented, with piecemeal improvements creating a patchwork of transit conditions that complicate effective region-wide travel.
Buses are a critical mode of transit for Greater Boston. During COVID-19, the region’s bus ridership proved to be more durable than any other mode, a common trend in many major US cities. Nevertheless, since its bus network looks strikingly similar to a regional streetcar map circa 1920, the MBTA saw the need to completely re-envision the system for how residents live, work and travel today. Ranked the eighth bus system in the US by ridership, the MBTA is one of the largest network to commit itself to a comprehensive transformation.
Redesign for regional impact expanding transit access and reducing emissions
The agency prioritized equitable access for the people who rely on buses most: lower-income residents, people of color, seniors, and people who live in households with few or no vehicles. Bus-only neighborhoods experience much longer and more difficult commutes than communities with easy access to rapid transit service. An improved bus network, with high-frequency routes more directly linked to centers of commerce, could ensure the residents of these transit-critical communities have better access to jobs, education, and essential services. From a post-COVID perspective, a good bus network is essential to economic recovery.
The MBTA also saw how a redesign could enable the network to better compete with drivers, and thereby reduce energy consumption and emissions region-wide. It could help address traffic congestion, and respond to changing in-office work patterns, where peak bus service is less relevant while all-day service is in demand.
Technology-empowered analytical approach to aid transportation planning
Arup’s unprecedented application of parametric modelling to the planning process meant the team also had to pioneer relevant standards and definitions to guide the data inputs, such as: What constitutes an acceptable commute? How close do routes need to be to key attractions and commerce centers? In other words, how might a “busable” route for Boston best be defined? Here the team’s work spanned from examining the grades of particular streets to make sure buses could ascend them, to detailed statistical research on how many combinations of networks the team needed to analyze to find the best possible solution, before diminishing returns set in.
In-depth, inclusive data sets
To best inform an evaluation of the region’s travel conditions and needs, Arup gathered significant amounts and kinds of data inputs, including of trips taken across all modes of travel in the region—not only via bus. Data from location-based services reflected people’s movement during all days of the week. This provided new insights, including the travel patterns for minority and low-income populations, groups that have traditionally been under-represented in decision making.
The team focused on gathering origin-to-destination data to better capture the realities of travelers, including having to combine transit modes or needing to transfer multiple times to reach destinations. Altogether, Arup collected data on 90 million trips across the region for the model to process.
The MBTA’s focus on a cogent, data-driven process led us to the unprecedented application of parametric modelling in a transit planning project, which improves the process in a way that brings confidence to both the clients and the public. The operational scale and data-driven approach of parametric modelling is revolutionary to the planning process and outcomes. It’s a critical planning tool for projects of all sizes. ” Matthew Ciborowski Associate, Americas East Cities Planning and Design Services Co-Leader
Since parametric modelling uses computer decision-making, human influence, such as historical patterns and ingrained industry conventions, is removed from the analysis. It enables a data-driven design approach that guides a more objective yet goal-focused process and solution.
Once the team input the data into the parametric model, the model utilized a series of rules, or parameters, that identified the best local connections for bus routes and iteratively evaluated and refined the results for increasingly suitable options to form a network. This process was informed by weights reflecting the MBTA’s key objectives, which enabled the model to filter and rank bus networks—all within the framework of resource constraints. These filters refined potential routes according myriad factors, such as trip distances and duration, connections to rapid transit, and the ability to connect residential and commercial areas. The agency’s goals of equity and access were prioritized throughout the analysis.
Ultimately, the model generated and then evaluated close to 14 million possible connections, filtering those to 92,000 possible routes and creating over 100,000 network combinations which the team scored and refined over the course of 12 weeks—an impossible timeframe and task by any other means.
A holistic, evolving network
As a holistic redesign, the proposed new bus map for Greater Boston will behave more coherently as a system. This enables the MBTA to do much more using a defined set of resources. The new plan provides improved clarity around trade-offs, allowing the agency to make more informed decisions. Significantly, it gives the MBTA the opportunity to more effectively use transit as a mechanism for foundational regional change and generate equitable economic development.
The MBTA also requested a replicable and adaptable process that they can continue to use in the future as conditions inevitably change over time. Arup will be handing off the process itself. This enables the MBTA to plug in new travel data or include new parameters to refine the network as a system in the near future, as opposed to making disconnected local fixes or waiting decades for another comprehensive redesign. The MBTA’s desire for a more regular understanding of conditions signals a significant shift in the planning process that parametric modelling enables. As a data-driven process, the approach allows an openness to and humility towards the unknowable future, and opens a pathway for planning to be more flexible and responsive to social, demographic and economic needs.