First Miles
Examining 18 Months of Dockless Bikeshare in Metro Boston
Executive Summary
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.
For the past 18 months, Lime has been operating a dockless bikeshare system in 16 cities and towns in the region’s Inner Core. During that time, users have taken 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, especially in terms of providing low-carbon alternatives to auto travel; 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.
Dockless bikes provide a unique way for people to travel around their communities and around the region, faster than walking and more sustainably than driving. 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. Survey data indicate that the system is serving residents for whom biking may not have been their default option: according to one survey, more than half of Lime bike riders haven’t used their own bike in more than a month, or don’t own one at all.
Approximately one-quarter of all trips terminate in a predominately residential neighborhood, providing a level of convenience unmatched by docked bikeshare, though bikes parked in these areas may go unused and have to be collected and returned to denser areas. 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.
There are big variations in system usage across the region. Malden, Everett, Arlington, and Winthrop saw the highest per-person ridership; whereas communities at the periphery of the service area saw only a small number of trips, even when controlling for total population and employment. The regional nature of the system is essential to its utility: Thirty percent of all trips ended in a different municipality than where they started. This intermunicipal exchange is most frequent in the Chelsea-Everett-Malden-Melrose corridor, which also sees very high per-capita ridership.
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. Examples include Revere Beach Parkway in Everett, Commercial Street in Malden, Washington Street in Newton, and Watertown’s Arsenal Street. In many cases, these roadways provide the only direct connection to important destinations. Retrofitting these roadways to fully serve bicyclists will be a challenging endeavor; however, 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. Had Lime followed the example of ride-hailing or short-term rental companies, very little, if any, of the information in this report would be available for analysis. 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.
About this report and MAPC
This report was prepared by the Metropolitan Area Planning Council (MAPC), the regional planning agency serving the people who live and work in the 101 cities and towns of Metropolitan Boston. Our mission is to promote smart growth and regional collaboration. This research is part of MetroCommon X 2050 , our effort to develop a new long-range regional plan for Metro Boston.
Introduction
Recent years have seen a proliferation of new forms of mobility in Metro Boston and across the country. Carsharing, ride-hailing, bikeshare, scooters, and other services provide not only new options for travelers, but also new sources of data that can help municipalities and state agencies make better transportation investments and policy choices.
For example, dockless bikes can be picked up and dropped off anywhere, and each bike contains an on-board GPS unit. As a result, they provide a rich dataset about where people are going and the routes they choose to travel, information not available from conventional dock-based systems such as Bluebikes.
This report provides a first look at the data produced by the Lime dockless bike system, which has been operating in the Boston region since Spring 2018, following a 2017 pilot program in the city of Malden. MAPC facilitated the procurement and contracting of the system on behalf of the participating municipalities, and through that process reached an agreement with Lime to have access to trip level data from the system. This data is published in a format known as the Mobility Data Specification (MDS), which provides information about the start and end points, time, and route of each trip, but not any information about the user who rented the vehicle. To understand system usage and help prioritize new bicycle accommodations, MAPC used this data and analyzed information about 300,000 trips to better understand how people are using the system to get around the region, and also to map where people are riding.
With this report, we are also publishing three data products that others can use to do their own analysis: tables with the count of trip starts and ends by day of week and calendar quarter, summarized to 250-meter grid cells; a matrix with the count of trips between each grid cell pair; and spatial data with the estimated number of trips for each segment of roadway and paths. These aggregate data products are designed to enable additional investigation while ensuring the privacy of every individual user of the system. The data is available for download on the MAPC Data Common .
This is only a preliminary analysis. Over the coming year, MAPC will continue to analyze the data, along with Lime's data about the electric scooter pilot in Brookline, in order to better inform transportation and land use policies.
Ridership Trends
Sixteen cities and towns have officially partnered with Lime to provide dockless bikeshare. The municipalities that participated in an MAPC-led collective procurement are Arlington, Bedford, Belmont, Chelsea, Everett, Malden, Medford, Melrose, Milton, Needham, Newton, Quincy, Revere, Waltham, Watertown, and Winthrop (see map below). Quincy pursued its own pilot with Lime at the same time. The program rolled out gradually across the participating municipalities: Malden was the first to pilot Lime bikes in 2017, and the other municipalities joined in 2018.
Notably, Lime does not operate in the four municipalities at the core of the region: Boston, Brookline, Cambridge, and Somerville. Due to conditions established by the contract with the Bluebikes operator Motivate, those municipalities are prohibited from participating in the regional dockless bikeshare contract. The only community with both Bluebikes and Lime bikes is the City of Everett, which joined the Bluebikes system in Spring of 2019 under the terms of a new contract that allows for the simultaneous operation of both bikeshare systems.
Trips by Municipality
MAPC analyzed 301,000 trips made between April 1, 2018 and September 30, 2019. This map shows the total number of trips in each municipality.
Malden has the largest number of trips by far; 74,000 Lime bike trips started in Malden over the study period, nearly one-quarter of all trip originations. Everett, which has both Bluebikes and Lime bikes, is the second busiest partner municipality, with 41,000 trip starts. Bedford and Milton saw the least activity, with approximately 970 and 110 trips, respectively.
In order to compare trip-making across communities, MAPC calculated the rate of trip making per capita, including resident population plus total employment. By that measure, Malden still remained far ahead of all other municipalities, with 450 trip starts per 1,000 persons (residents plus employees) over a one-year period from October 2018 to September 2019. Malden was followed by Everett, Arlington, and Winthrop, each of which saw between 200 and 360 trips per 1,000 persons over that same time period. The lowest rates of trip-making were in Bedford, Waltham, Needham, and Milton, municipalities that are on the edges of the Lime service territory.
In terms of overall mode share, trips on dockless bikes were a small share of trips in all municipalities. Using estimates of total annual trip production (from the Boston MPO’s regional travel demand model), MAPC estimated Lime bike mode share for each of the Lime bike municipalities. Malden continued to have the highest rank by this measure as well, with an overall dockless bike mode share of 0.08 percent of all trips originating in Malden. Arlington, Everett, and Winthrop were in the second tier, with mode shares of 0.03 percent to 0.06 percent. For comparison, MAPC had previously estimated that the ride-hailing mode share in Malden in 2018 was 1.9 percent of all originating trips. Put another way, there were approximately 30 ride-hailing trips for every dockless bike trip originating in Malden in 2018.
Trends over Time
As one would expect, there is a considerable amount of seasonal variability in usage of the system, but also year-over- year differences. This variability is shown in the chart below. In 2018, the highest ridership (more than 30,000 trips per month) was observed from July through October. September was the peak month, with nearly 45,000 trips in September 2018. Ridership slowed considerably during the winter, with an average of only 52 trips per day (approximately 1,500 trips per month) from January through March. Ridership in 2019 was substantially lower than in 2018 across the board; peak monthly ridership was in June 2019 (21,000 rides) and declined each month through September. Comparison of peak period ridership (April through September) shows a 40 percent decline in year-over-year ridership from 2018 – 2019.
The type of bicycles in the system has also changed considerably: when the system launched, it was 100 percent human-powered pedal bicycles. In late 2018, Lime introduced more electric-assist bicycles (e-bikes) into the fleet to replace conventional pedal-powered bikes. By the beginning of 2019, nearly all trips were made with electric-assist bikes. While these bikes are more convenient, they also cost more per trip than pedal-powered bikes. E-bikes are rented on a per-minute basis ($1.00 to start, $0.15 per minute) instead of a flat rate for 30 minutes. As a result, the average twelve-minute trip costs $1.00 on a pedal-powered Lime bike and $2.80 on an electric-assist bike, and the price differential increases with longer ride durations. This cost increase could have disinclined some potential riders from using the system and may have contributed to declines in ridership in 2018. Municipalities also report that there were fewer bike available in 2019, but unfortunately the number of vehicles deployed over the study period is not available to MAPC.
Time of day
Ridership also varies from hour to hour. On weekdays, the system is most active in the afternoon and evening. For example, in the third quarter of 2019 (July through September), approximately 47 percent of rides started between 2:00 a.m. and 8:00 p.m. There is also a small weekday morning peak between 7:00 a.m. and 9:00 a.m., but these hours contain just 10 percent of all trips. On weekends, ridership is more spread out over the course of the day, without peaks during prime commuting hours. As noted above, ridership is lower during winter months, with a slightly earlier afternoon peak and relatively less early evening ridership.
Trip Distance and Duration
The vast majority of Lime bike trips (75 percent) are between a half mile and two miles, with a median distance of 0.92 miles and an average distance of 1.27 miles. The distribution of trip lengths is shown in the graph. Not surprisingly, people take longer trips in spring and summer than in winter and fall. Regardless of time of year, weekend trips are longer than those on weekdays. With the introduction of e-bikes, the trip distances did not change appreciably, but travel speeds increased and trip duration declined. The median trip duration in Q2 2018 was nearly 14 minutes; this figure declined to nine minutes in Q2 2019, even though the median trip length was effectively unchanged.
Where are all those bikers going?
Since each vehicle has a GPS and can be parked practically anywhere, dockless bikeshare systems such as Lime can provide a detailed picture of trip-making patterns in the region. While ride start locations may not be exactly where the rider began their trip (since a bike may not be available right outside their origin), the end of the bike trip is likely to be very close to the rider’s intended destination.
In order to summarize and anonymize the data, MAPC aggregated trips into grid cells that are 250m on a side (0.15 miles, enclosing an area of about 15 acres). For each grid cell, we calculated total numbers of total trip starts and ends for weekday and weekend trips, as well as average trip distance.
Though Lime is prohibited from operating its system in Bluebikes municipalities, users do occasionally ride into Bluebikes territory. In the past, users were able to start new trips with Lime vehicles parked in Bluebikes communities, though Lime’s efforts to strengthen its so-called ‘geofencing’ have made trip starts in Bluebikes territory far less common.
The map below displays Lime bike destinations per calendar quarter over the study period (April 2018 – September 2019). scroll through to see how system activity was focused around Malden and other early-adopter communities in early 2018, expanded across the region in late 2018, contracted over the winter, and then rebounded in Q2 2019.
Map of Lime Dockless Bike Trips Destinations by 250-meter Grids in MAPC Region
2018 Q2
1 April – 30 June, 2018
2018 Q3
1 July – 30 September, 2018
2018 Q4
1 October – 31 December, 2018
2019 Q1
1 January – 31 March, 2019
2019 Q2
1 April – 30 June, 2019
2019 Q3
1 July – 30 September, 2019
Trip origins and destinations
The maps above, suggest that trip-making activity is concentrated in city and town centers. In prior research, MAPC delineated approximate boundaries of city, town, and village centers in each municipality, based on land use mix, building ages and types, and role as a historical center of population and commerce. Once Lime bike trips had been mapped, we assessed the share of trips that terminated in city and town centers. We found that these centers comprise 12 percent of the area of the Lime bike municipalities, and contain approximately 32 percent of the population and employment. They also produced approximately 45 percent of all trips and attracted 40 percent of all trips over the 18-month period, an outsized share even when accounting for higher densities. Many of these trips are destined for outlying residential neighborhoods. We estimate that 27 percent of all trips terminated in predominately residential neighborhoods, and 24 percent originated in those neighborhoods.
This interchange of dockless bikes between commercial districts and surrounding residential neighborhoods is apparently asymmetrical; there are more trips flowing out of central areas than flowing in. Redistribution, or “rebalancing,”of bicycles is conducted by Lime on a semi-regular basis, to relocate bicycles to areas where they are in higher demand. MAPC did not directly evaluate this redistribution by Lime, but we were able to quantify the imbalances between trip starts and ends for each grid cell in the region. The map below shows the balance of trips (total trips started minus total trips ended in the grid cell) over the last 12 months.
The bright yellow areas indicate locations where trip starts significantly exceeded trip destinations, and are largely centered on main streets, town centers, and commercial districts. The dark blue areas show the neighborhoods where trip destinations exceeded trip starts; and the light gray areas cells are those where ride starts and ends were roughly equal.
While these patterns suggest that many Lime bike riders are using the bikes to ride from main streets and commercial areas into residential areas, the data does not account for the non-ride redistribution of bicycles performed by Lime staff. What this data does indicate, is that many Lime bike trips are taken to connect nearby residential neighborhoods to local activity centers within the town or in neighboring towns.
Trip Length
MAPC also evaluated the distribution of trip distances across the region to identify locations that tended to generate or attract longer than average trips. Scroll through the two maps below to see the average trip distance for trips that start in each grid cell, and the mean trip distance for trips that end in each grid cell, respectively.
As discussed above, most of the Lime bike trips are relatively short distance (0.5 to 2.0 miles), but several areas stand out as generating and receiving significantly longer trips. Long trips are a feature of the Minuteman Bikeway in Bedford and Lexington, with many trips that exceed two miles both starting and ending in those areas.
Overall, we find that the majority of long-distance Lime bike trips end in Bluebikes territory, particularly in the neighborhoods around Lower Allston, Harvard Square, Boston University, and Back Bay. As Lime bike riders cannot start trips in these towns due to geofencing, these bikes must then be relocated by Lime back into participating communities.
The overall balance of trips exchanged between different municipalities is shown in the table below, which presents data for a one-year period from October 2018 through September 2019. On average, about 70 percent of trips stay within the city or town where the trip began. However, certain pairs exchange a considerable number of trips, and these exchanges are often not balanced between the municipalities: More than one-fifth of trips that start in Arlington and Belmont end in Cambridge; about half end at Alewife T station, and the rest elsewhere in Cambridge. The number of return trips from Cambridge to these towns is roughly the same size. However, almost two-thirds of trips starting in Milton end in Quincy, but 97 percent of trips that start in Quincy stay within the city. The most intermunicipal trip exchange occurs among Malden, Medford, Melrose, and Everett, where 15 – 27 percent of trips start or end in a neighboring municipality.
Transit Connections
The communities with Lime bikes differ considerably in the availability of public transit options, specifically light rail and commuter rail. To evaluate how often Lime bike riders were using the bicycles to make connections to or from transit stations, we identified all trips that either started or ended within 100 meters of a commuter rail or rapid transit station (including Silver Line stops). Across the region, we found that roughly 15 percent of Lime bike trips started or ended at a transit station. In several towns, such as Arlington, Bedford, Melrose, and Needham, a significant share of trips (9 – 14 percent) left the town to end at a transit station in a neighboring municipality. This shows a clear use of the Lime bike services to fill the “last-mile” trip mode connecting riders to the transit system. However, this particular trip purpose remains a relatively minor share of all trips; the remaining 85% are not associated with rapid transit, and could in fact be substituting for local bus routes.
Travel Routes and Road Stress
Because Lime bike record GPS locations while the bike is in operation, the actual routes chosen by riders can be mapped. These routes reveal in precise detail not just where Lime bike riders are going, but the roads they are choosing to use. This information has broad applicability to cities and towns seeking to improve biking conditions in their community.
Lime bike users are generally not frequent cyclists; according to recent user survey, 53 percent have not used their own bicycle in more than a month, or don't even own one. If certain facilities are highly utilized by Lime bike riders, it is likely these same facilities will be very important to cyclists and would-be cyclists throughout the community. Moreover, their experience on the roadway while using a Lime bike may influence whether these interested but infrequent cyclists cycle more often; or if they are deterred by dangerous or unpleasant conditions. Therefore, the routes heavily used by Lime bike riders should be important priorities for local bike facility improvements.
In order to understand the map chosen by Lime bike riders, MAPC used millions of 'waypoints' produced by the bikes' GPS units and joined these together into paths following the street network. The accuracy of the assigned routes and the count for each segment is subject to limitations, including GPS accuracy and completeness, errors or omissions in the mapped street network, nonstandard/illegal routes, and assumptions made during the trip assignment process. Not all trips could be mapped completely, so some of the trip count for each segment is imputed. The technical documentation includes details on how the trips were mapped from GPS data and assigned to specific roadway segments.
This map shows the routes taken by Lime bike riders. Thicker lines indicate segments used by more riders. Click on any segment to get information about the estimated number of trips that used the roadway, and scroll through to zoom in on a few notable spots in the region.
Malden sees the highest concentration of Lime bike activity across the region, with hundreds of trips going to or through Malden Center on Main Street, Salem Street, Pleasant Street, and Ferry Street, and on the Northern Strand Community Trail. The sections of Main Street and Ferry Street spanning Malden and Everett rank among the busiest roadways, demonstrating the value of Everett's Bluebikes agreement that permitted concurrent operation of Lime .
The Minuteman Bikeway is very popular with Lime bike riders, especially between Arlington Center and Alewife T station, which is the destination for approximately 10 percent of all trips that start in Arlington. This map also shows the popularity of parallel routes (Massachusetts Avenue) and connecting cross streets that link the bikeway to nearby neighborhoods.
In Quincy, Hancock Street is the central corridor for Lime bike ridership, but the map also shows how riders are using the system to connect from outlying neighborhoods to the business districts at Quincy Center, Wollaston, and North Quincy. Notably, the use of Lime bikes as a connection to transit is relatively low in Quincy—only 7 percent of trips that start in Quincy end at a subway station.
In Watertown, the most popular link is the Charles River bike path, especially west of Watertown Square. However, the presence of high-quality off-road facilities doesn’t diminish the use of other nearby arterial roads. Many Lime bike riders looking for a more direct route to or from Cambridge or Brighton use Arsenal Street; and those coming from west of the Square use Main Street. This demonstrates the importance of creating safe connections on major roadways, even when they run parallel to off-road facilities.
Is it Safe? Is it Stressful?
Once the bike routes have been mapped, information about cycling conditions can be overlaid to identify what roadways have the greatest disparity between demand and cycling safety. These roadway connections can be prioritized for improved bicycle accommodations.
Researchers and practitioners have begun characterizing the “stress level” for bicyclists on a given roadway using a variety of measures related to safety, security, and experience of bicycling. “Low-stress” roadways are those that provide safe, convenient, and pleasant experiences for cyclists of all ages, keeping bikers out of harm’s way and fostering an affinity towards cycling as a useful mode of transport. Meanwhile, higher-stress roadways are those that require lots of interactions with auto traffic, making cyclists feel unsafe and disinclined toward bicycling.
Robust analysis of biking stress entails analyzing many aspects of roadway design, ranging from lane widths and vehicle speeds to bike facility configuration and auto parking. While some researchers have begun preparing detailed maps of biking stress levels in Boston and surrounding communities, there is no comprehensive assessment of stress level across the LimeBike service territory. Therefore, MAPC used available data and roadway/bike facility information (from Open Street Map and MAPC’s Trailmap ) to prepare a preliminary assessment of traffic stress levels, as a next step toward identifying important bicycle connections that merit better facilities. We categorized the transportation network into four categories:
Low-Stress Facilities: Off-road bike paths and cycle tracks physically separated from auto traffic, as well as low-volume residential roadways. These facilities provide a strong separation from all except low speed, low volume traffic. Suitable for riders of all ages and abilities, including children.
Moderate- and High-Stress Facilities: Roads and streets that lack separated bike facilities, but that may have painted bicycle lanes or sharrows. These streets often have multiple lanes in each direction for auto traffic. They are appropriate for cyclists confident riding alongside vehicle traffic and parked cars.
Very-High-Stress Facilities: Connector or arterial roadways with multiple lanes in each direction, high auto volumes and speeds, and no physically separated bicycle facilities. These facilities present the highest risk and largest potential consequences of bike-car collisions.
Other: Non-standard facilities hard to classify based on the available data. The category includes paved and unpaved pathways and roads in parks and on other public land; parking lot access roads; alleyways; and other unclassified roads on commercial, institutional, or industrial campuses. While some of these facilities may be suitable for bicycling, incomplete information prevents us from characterizing the specific facilities in this study.
Multiple criteria are used for our preliminary classification: functional classification of the roadway, number of lanes per direction, and type of bike facility. While these criteria don’t include all facility characteristics that contribute to level of traffic stress, they were available for all communities in the region and can serve as the basis for a preliminary classification system. We also had to rely on information available in the datasets used for the analysis, and recent infrastructure investments or facility improvements may mean that our classification doesn’t reflect current conditions on the ground. MAPC will continue development of a comprehensive database of biking facilities and will continue to refine and improve the level of traffic stress classification over time.
Low-Stress Route Segments
This map shows the volume of trips ridden on low-stress facilities throughout the region over the 18-month period. The region’s major off-road bikeways stand out as important “highways” for bicyclists: Northern Strand Community Trail, Minuteman Bikeway, and the Dr. Paul Dudley White Bike Path on both sides of the Charles River. MAPC estimates that approximately 44 percent of all miles traveled by Lime bike riders were on these low-stress road segments.
Very High-Stress Roads
This map shows trips ridden on very-high-stress facilities throughout the region. Large numbers of Lime bike routes traverse high-volume arterial roadways and parkways that don’t have safe or pleasant bicycle infrastructure. Centre Street and Florence Street in downtown Malden; Commercial Street, connecting Malden with the Mystic Landing development and Wellington T station; Revere Beach Parkway; Washington Street in Newton; Arsenal Street in Watertown; and even sections of Massachusetts Avenue in Arlington all qualify as very-high-stress facilities that lack adequate bike infrastructure, if any. It’s possible that some or most bicyclists navigate the most treacherous stretches on the sidewalk, but that remains a suboptimal solution.
A View of High and Low Stress Segments
This map shows all roadways and paths used by Lime bike riders over the study period, including Low-Stress (green), Moderate- and High-Stress (brown), and Very High Stress (red).
Zoom in and click on a segment to see the name of the street, the estimated count of trips, and the estimated distance traveled on that segment by all riders.
Conclusion
Dockless bikes are an entirely new form of travel in the region, providing rapid mobility for local trips generally less than two miles. Two fifths of trips start and end in city and town centers, and more than a quarter end up in surrounding residential neighborhoods. Connections to transit were a less significant component of the system's use. These findings suggest that dockless mobility can serve an important 'circulator' role in communities and provide last-mile connections into moderate density residential neighborhoods, where conventional docked bikeshare would be difficult to support. While the balance of trips showed a net flow out of city and town centers, this could be due to redistribution of vehicles back into densely developed areas.
By mapping the routes taken by Lime bike riders, we can also identify important bicycle connections that should be prioritized for safety improvements. Nearly one in five miles traveled by a Lime bike rider was on a "very high-stress" roadway lacking safe and comfortable bike facilities. Many high-volume roadways with no bicycle accommodations may not be prioritized for improvements because there is a perception that they are not used by bicyclists. These data show that many such roadways are in fact used heavily. Improvements are needed not just to attract new bikers but to protect the ones that are already riding there.
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. Had Lime followed the example of ride-hailing or short-term rental companies, very little, if any, of the information in this report would be available. 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.
Credits
Contributors : Armin Akhavan,* Conor Gately, Steve Gehrke,** Guy Hydrick, Jessie Partridge Guerrero, Tim Reardon, Bita Sadeghinasr,* Annabelle Taylor
* Northeastern University
**Northern Arizona University
November 6, 2019
See the Technical Appendix with a summary of data processing and analytical methods.