Week 11: Solving Boston’s Traffic Crisis

Friday, July 10, 3:30 pm

 

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An app for safer driving: Driving behavior change through self-reflection
Presenter: Yifan Lu, City of Boston Mayor’s Office of New Urban Mechanics

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Co-authors:

Kristopher Carter, City of Boston

 

In the spring of 2015, Mayor Walsh announced a commitment to eliminate traffic fatalities and serious injuries from our roadways through a Vision Zero initiative. Over the past three years, a Vision Zero Task Force and rapid response teams were formed, data sharing agreements among agencies were executed, nation-leading truck side guard legislation was passed, data analysis with community input was initiated, a comprehensive mobility plan called GoBoston 2030 was launched, and large-scale capital projects have broken ground. However, much of the initiative’s success rests on the ability of Bostonians to change the way they behave when they are behind the wheel of a car. Traffic safety is personal and we need to hold ourselves accountable for results.

CapitaLiz Hessing on the competitive nature of our City, we piloted the first edition of the Boston’s Safest Driver competition in the fall of 2016. The program utiLiz Hessed a smartphone app developed by a local start-up Cambridge Mobile Telematics to provide a score out of 100 to drivers at the end of each of their trips, the first of its kind in the country. Our goal was that, through self-reflection and friendly competition, we could shift behaviors behind the wheel, and if we did it in the right way, make it habit forming. Among the top 25 percent of drivers using the app in the 2016 competition, we saw phone use drop by 47 percent and their speeding decrease by almost 35 percent.

After a very successful pilot that showed reductions in phone distraction, speeding, and hard braking among users, we reshaped and scaled the program in 2019 for broader adoption based upon our learnings. We saw positive results overall. Similar to the 2016 competition, there were significant reductions in unsafe behaviors in each of the categories. We saw a 33 percent decrease in overall risky behaviors, 48 percent decrease in distraction behaviors, 57 percent decrease in harsh braking, and 38 percent in speeding. In total, 2,920,080 miles were recorded, of which 19,650 were biking trips. In addition, the anonymized data aggregated over the duration of the competition helped identity hotspots where certain infrastructure features could be improved.

The talk will focus on our findings from the 2019 competition and the lessons learned.

 


Measuring the benefits of bus transit priority for riders
Presenter: Philip Groth, MBTA

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Co-authors:

Alissa Zimmer, MBTA/MassDOT

 

As traffic congestion increases, MBTA buses are subject to longer travel times and declining reliability. From 2006 to 2019, median trip running times across all MBTA bus routes increased by 13% overall, including more than 20% at peaks. As a result, bus trips are longer and less reliable, and the MBTA can run fewer trips with the available fleet.

In order to improve bus travel times and reliability, the MBTA has been partnering with cities and towns to create bus lanes and other transit priority measures to help give buses a clear path past traffic. As a result, riders experience faster service with fewer delays, and the MBTA is able to offer more service with the same resources. The MBTA has identified 14 corridor miles for focused investment in bus priority infrastructure that will have the highest and most immediate benefits for riders, and approximately 10 miles are currently in operation.

The corridors targeted for investment are often areas that have a high level of congestion-related delays and high ridership. After bus lanes are implemented, bus routes using the lanes should immediately experience faster run times and reduced variability in run times, with better on-time performance (OTP) and increased ridership emerging over time. In order to evaluate bus lane performance, the MBTA uses data from our Automated Vehicle Location (AVL) and Automated Passenger Counter (APC) system to estimate delays and ridership both before and after the implementation of the bus lane. It’s also important to develop rider-focused metrics that attempt to capture the improved experience of bus riders who are affected by bus lanes.

Evaluating bus lane performance and quantifying the benefits is important for several reasons. First, it helps provide feedback on project design and operations. Many bus lanes are implemented as pilots, and require some alterations to improve performance. Second, it helps inform Service Planning and Scheduling, allowing the MBTA to “reinvest” the travel time savings into better service. Finally, it helps the MBTA and our municipal partners make the case for these investments. In most cases, creating a bus lane requires repurposing part of the roadway that currently is used for parking or general traffic. This is often unpopular with some stakeholders, so being able to clearly describe the benefits helps make the case for continuing these investments.

 


Creating a Road Map of ‘Busable Streets’
Presenter: Julianna Horiuchi, Spatial Analysis Assistant, MBTA

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Co-authors:

Alissa Zimmer, Massachusetts Bay Transportation Authority

Anna Gartsman, Massachusetts Bay Transportation Authority

Ian Thistle, Massachusetts Bay Transportation Authority

 

Transportation can be a key determinant of equity in the urban environment, and buses—cheaper for riders and more flexible for transit agencies—play a large role. But with Boston’s challenging street geometries and physical geography, knowledge of what roads can actually get people to where they’re going becomes increasingly important. Attempting to fill the data gaps that only bus service planners know exist, we set out to create a road network map of the MBTA service area in which streets are assessed by their abilities to accommodate a 40-foot bus—a map of “busable streets.” This single GIS-based map layer—built almost entirely on public spatial data—pulls together elements such as road surface, street width, bridge clearances, and percent grade into a manageable, four-level ranking. The surprisingly simple dataset has the potential to support bus and rapid transit diversion efforts, inform conversations with communities on changes to their bus routes, and ultimately assist service planners in making data-driven decisions.


First Miles: Examining 18 Months of Dockless Bikeshare in Metro Boston
Presenter: Timothy Reardon, MAPC

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Co-authors:

Armin Akhavan, Northeastern University

Bita Sadeghinasr, Northeastern University

Conor Gately, MAPC

Steven Gehrke, Northern Arizona University

 

Metro Boston has a wealth of transportation options practically unheard of ten years ago, from ride-hailing and carsharing to bikeshare and scooters. Each of these new types of mobility provides not only new options for travelers, but also new sources of data that can help public agencies make better transportation investments and policy choices. The Metropolitan Area Planning Council analyzed detailed trip-level data from the Lime dockless bikeshare system operating for in 16 cities and towns in the region’s Inner Core. Over a period of 18 months, users took over 300,000 trips, logging an estimated 380,000 miles. While this is a small share of overall travel, the data that the system produces about travel patterns can shed light on two important areas of interest: a) the role that dockless bikeshare and other forms of so-called “micromobility” might play at the periphery of Boston’s Inner Core; and b) where transportation investments and infrastructure improvements are most needed to create safe conditions for bikers, whether they are using Lime bike, Bluebikes, or their own bicycle.

We found that the average trip is about 1.3 miles and takes about 16 minutes on one of the electric-assist bikes that comprise most of the Lime bike fleet. Two-fifths all trips start in town centers and commercial districts, and many of those fan out into outlying neighborhoods beyond an easy walking distance or inaccessible by transit. Connections to transit are an important, but relatively small, share of all Lime bike trips. We estimate that 15 percent of all trips begin or end at a subway, trolley, Silver Line, or Commuter Rail station.

Lime bike riders face some tough conditions when riding around the region. Eighteen percent of miles travelled were on roadways we classify as “very-high-stress” roadways, with high traffic volumes, multiple lanes in each direction, and no protected bicycle facility. In many cases, these roadways provide the only direct connection to important destinations. The travel patterns observed here demonstrate how important it is to build facilities that will keep bicyclists safe, and to do it soon. The facilities are needed not just to encourage more people to bicycle, but to protect the people who already are biking in unpleasant if not dangerous conditions.
By providing new insight on micromobility and key bike connections, this report also demonstrates the importance of guaranteeing that public agencies have access to data from new mobility and sharing economy systems. Fortunately, Lime agreed to provide access to trip data using a nationally-recognized data standard that protects rider identity, enabling a substantial amount of research and creating value for the region. This level of data access should be standard procedure for all new forms of mobility, whether scooters, drones, autonomous vehicles, or anything else. With this information, public agencies can ensure that new technologies and modes contribute to a more sustainable, equitable, and convenient transportation system.


Moderator: Adam Vaccaro, Reporter on Transportation and Infrastructure, Boston Globe