New York City CONGESTION TRENDS REPORT

Transcription

1 New York City CONGESTION TRENDS REPORT AUGUST 2018

2 The analysis in this report was conducted by Transpo Group using data provided by INRIX. The only Transportation Network Company that provided data for this report was Lyft. The conclusions of this report do not necessarily reflect the official policy positions of Lyft, INRIX, Transpo Group, or the City of New York. While this report acknowledges lower travel speeds on streets in New York City, discussion regarding the applicability, effectiveness, or benefits of Vision Zero policies is beyond the scope of this report.

3 Table of Contents Executive Summary...1 Introduction...3 Methodology... 7 Travel Demand & Capacity Drivers Performance Trends Findings & Conclusions... 31

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5 List of Figures 1. Seasonally Adjusted GDP in billions of current dollars ( ) NYC Employment Rate, Seasonally Adjusted ( ) New York City Gasoline and East Coast Diesel Prices ( ) Changes in Driver Population and Vehicle Use Quarterly US E-Commerce ( ) Pedestrian Counts in Manhattan in May ( ) Pedestrian Counts at East River Bridges May ( ) New York City 12-Hour Uptown Bicycle Count at 86th St ( ) New York City 12-Hour Midtown Bicycle Count at 50th St ( ) Average Cyclist Counts at East River Bridge Locations (2017) Protected Bicycle Lane Growth in New York City ( ) Annual Transit Ridership in New York City ( ) Annual Transit Ridership in Manhattan ( ) Average Speed in Manhattan (study area) ( ) Manhattan Monthly Taxi vs TNC Pickups ( ) Manhattan Daily Speeds and Lyft Trips ( ) East River Bridges/Tunnels Average Speeds ( ) Daily Lyft Trips in New York City ( ) East River Lyft Crossings (Thursdays In October 2017) Hourly Profile of East River Crossing Speed and Lyft Activity Lyft Line Growth ( ) List of Tables 1. Congestion Trends Report Data Sources Change in East River Crossing Volumes by Vehicle Classification... 26

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7 Executive Summary The evolution of Transportation Network Companies (TNCs) in the recent past has led major cities to attempt to evaluate the impacts of TNC services on mobility, equity, and congestion. The results of various studies concerning TNC contributions to congestion have been mixed. This report provides a limited analysis of how recent and emerging trends in New York City might shed new light on the issue of TNC services and their contributions to congestion management. Understanding this issue requires acknowledgment that congestion and transportation system performance is a complex multi-variable problem. Congestion is driven by numerous factors including changes in demand, capacity, and mode split. As part of New York s Vision Zero Program, prioritization of bus, bicycle and pedestrian activity advances the goal of promoting a mode shift from single-occupant private vehicle use. While speed can be used as a measure of perceived congestion, a reduction of travel speeds is not inherently indicative of transportation system reliability. Further analysis of speed and reliability is outside the scope of this report. The key findings from this report indicate that it is not possible to conclude that Lyft is the primary contributor to the growth of congestion in New York City KEY FINDINGS This study found increased congestion cannot be solely attributed to growth in TNC market share. In fact, TNC growth is accelerating even as other trends, such as the decline in average speeds, are flattening. The population of New York City is growing and the percentage of employed New Yorkers continues to rise, increasing by 266,000 people between 2014 and Because of this, the demand for commute trips, discretionary trips, and commercial trips continues to grow, particularly as e-commerce and on-demand delivery service utilization rises. New York City Congestion Trends Report August

8 SPEED LIMIT 25 Daily average travel speeds in Manhattan CBD south of 96th Street fell by 11 percent between 2014 and Commercial and construction activity increased during the study period and frequent deliveries rose sharply. Likewise, speed limits were reduced and camera speed enforcement proliferated. Between 2014 and 2017, the aggregate average speeds for all East River crossings during the 3 PM to 7 PM period on Thursdays in October fell by just 8.4 percent mainly due to increasing congestion on the crossing approach roadways. The total number of daily vehicle trips across the East River declined by 9 percent between 2014 and 2016 while freight traffic increased by 17 percent. Passenger vehicle trips declined even as Lyft service increased. Lyft Line service (Lyft s multi-passenger highoccupancy option) continues to grow in New York City, accounting for approximately 30 percent of all Lyft trips in 2017, moving more people in fewer vehicles. Passenger vehicle trips across the East River declined even as Lyft service increased Between 2014 and 2017 average daily Lyft trips rose by 2,600 percent while all TNC vehicle registrations increased by only 116 percent. The intensive ride-matching services of TNCs optimizes the occupancy and use of the vehicles. Average daily MTA subway ridership declined by just 0.3 percent during the study period despite disruptions due to track and station improvements. 2 August 2018 New York City Congestion Trends Report

9 Introduction The growth of transportation network company (TNC) services, such those provided by on-demand, shared-ride mobility platforms, has enabled new economic opportunities and travel options for people throughout cities all over the world. Access to reliable transportation at a reasonable, known, and agreed-upon cost has aided people in a wide variety of economic situations. TNCs have improved access for disadvantaged communities, people who live in areas under-served or not served by transit, and people who seek to reduce their impact on climate change by choosing to not own a car or occupy valuable space on congested urban streets by parking a car. TRANSPORTATION PERFORMANCE MODELING IS COMPLICATED The very nature of TNC operations, however, is that TNC ridership growth generally leads to more TNC vehicles operating on the roadway network. This growth must be understood in the overall context of congestion management, however, and may not be the sole contribution or even a major contribution to increased congestion. Understanding how TNC network growth affects congestion requires an independent and objective assessment of transportation system performance. Objectivity is achieved in such a study through the use of widely-available, public agency data, aggregated and anonymized location-based data that is inherently objective, and analysis of changes in TNC use against a baseline condition for TNC operations. Congestion is generally perceived as an increase in travel times over a nominal value, a lack of free-flowing vehicles or pedestrians, and difficulty of access to the facility by a variety of users. It is characterized by the extent of congestion, the duration of congestion, and the severity of the congestion. While congestion may be seen as an indicator of a thriving economy, congestion that causes stop-and-go conditions has a deleterious effect on carbon emissions and can significantly impact economic activity. Congestion impedes predictable movement, increases crash rates, and contributes to undesirable and anti-social behavior that threatens people walking and people using bicycles. Addressing congestion leads to increased economic competitiveness and an improved quality of life. New York City Congestion Trends Report August

10 It is clear from extensive research that many factors influence This study was prepared by Transpo Group, a consulting firm with expertise in transportation planning and traffic operations. The study team included transportation modelers with extensive experience in simulation modeling and performance analysis, transportation planners, a traffic operations and safety engineer, data scientists, and senior performance analysts. These team members developed and refined the study methodology, selected and vetted data sources, performed data verification and quality management activities, and conducted the analysis, reviewing the outcomes in a multidisciplinary team focused on holistic transportation system performance. the growth of congestion. Simply examining traffic volume, average speeds, and travel times can indicate the performance of a facility but such an examination cannot address complex socio-economic factors that lead to increased demand. Any effort to thoroughly understand the drivers that influence travel demand must look beyond pavement, streets, and the transportation network. Even as the scope of a study expands to capture these drivers of demand, a comprehensive examination of transportation management policies must also be undertaken to assess the impacts of speed management, vulnerable user accommodations, curb use and parking, and the management of events, closures, and traffic signal operations. NEW YORK CITY CONGESTION IS GROWING Our research found that overall road congestion in New York City is growing, particularly in areas where subway lines are highly accessible and across natural barriers such as the East River. The decline in average speeds in Midtown and Lower Manhattan flattened between 2015 and 2017, while average speeds on crossings of the East River have declined only slightly. Freight and e-commerce delivery traffic are continuing to grow, particularly in Manhattan. The capacity of the street network is being further constrained by illegal parking and street closures due to construction activities. 4 August 2018 New York City Congestion Trends Report

11 EVOLVING TNCs ARE SERVING TRIPS MORE EFFICIENTLY Trips from all TNC services using ride-hailing mobile apps increased to approximately 158 million annually for 2017 (a 4-fold increase since 2015) while annual taxi trips have declined by approximately 32 million during the period from 2015 to 2017, to 112 million annual trips. Lyft, a TNC operator in New York City increased trips from 0.5 million annual trips in 2014 to 26 million trips in Despite this increase, we observed a decline in personal vehicle travel across the East River. Lyft trip growth on East River crossings indicate that TNC operators may be absorbing both taxi trips and private automobile trips, thereby displacing singleoccupant trips, even as overall trips in New York City grow due to increasing travel demand. Lyft trips are considered private automobile trips in the segregated East River traffic counts. PREVIOUS TNC/ CONGESTION RESEARCH Many previous research efforts have attempted to quantify TNCs level of contribution to growing congestion in cities across the country. These reports have used differing methodologies; some using VMT as a method to quantify congestion, some using surveys to evaluate what mode people are leaving in favor of TNCs, and others using demographic data to understand who is using TNCs. The results of these studies are often in conflict, some determining congestion is rising because TNC VMT is increasing (Shaller, 2017), another concluded that TNCs have the potential to reduce overall traffic congestion (Li, et al, 2016), while TCRP Report 195 (2018) found no clear relationship between peak hour TNC activity and long-term changes in public transit usage. Previous research of For-Hire Transportation Study (City of New York, 2016) concluded that speed reductions in NYC are driven by increased freight movements, construction, population growth and a growth in tourism. New York City Congestion Trends Report August

12 Kent Ave LEGEND Manhattan Study Area 76th St W 79th St Amsterdam Ave 97th St Lenox Ave E 106th St East River Bridges East River Tunnels W 72nd St 79th St 3rd Ave FDR Dr S 1st Ave Palisade Ave W 34th St W 57th St 65th St Hudson 14th St Lincoln Tunnel 9th Ave 6th Ave E 34th St Park Ave Queens-Midtown FDR Dr S Tunnel 2nd Ave Queensboro FDR Dr N 21st St Queens 31st St Steinway St 7th Ave 5th Ave Long Island Expy 39th St 14th St Holland Tunnel Greenpoint Ave FDR Dr Williamsburg Metropolitan Ave Broadway Grand St West St FDR Dr N Brooklyn Manhattan Flushing Ave Myrtle Ave Brooklyn-Battery De Kalb Ave 6 August 2018 New York City Congestion Trends Report Kings Henry St ve Atlantic Ave

13 Methodology The study methodology for this work included identifying data sources, compiling results from applicable data, and assessing the relative magnitude of overall congestion trends and trends in Lyft s customer demand and use of Lyft services. This study relied largely on transportation performance data from INRIX, a global leader for transportation analytics. INRIX released its latest 2017 Traffic Scorecard report in February Each year, the Scorecard provides an analysis that compares the year-to-year state of traffic congestion in countries and major metropolitan areas worldwide. INRIX previously prepared a Congestion Trends Report for greater London, United Kingdom, and we applied the same industry-standard analysis protocols and data curation practices to this work. STUDY APPROACH For this particular study, Transpo Group compiled data from a variety of sources and examined the performance of the transportation network. For the New York City study, we chose to assess two discrete areas that experience the most intense overall congestion. The first area, Manhattan below 96th St, was assessed as an entire area and average speed changes during study period were analyzed. By selecting all streets designated in the INRIX system as Functional Road Class (FRC) 2 and 3, we were able to examine the average speed and other characteristics for all of Manhattan s major arterials, minor arterials, and the vast majority of collector streets. The other study area comprised all East River crossings below 96th St (south of the Triboro) and included the Brooklyn Battery Tunnel, the Brooklyn Bridge, the Manhattan Bridge, the Williamsburg Bridge, the Queens-Midtown Tunnel, and the Ed Koch Queensboro Bridge. For these facilities, we examined the queue length leading into the last access point, and the average speeds for each crossing segment itself, and the composition of the traffic crossing the bridges. We supplemented transportation data analysis of the Manhattan study area and East River crossings study area with data related to economic activity, population and vehicle ownership, parking, and accommodations for people-centric transportation, including walking, bicycling, and public transit. Using this information, independent of any TNC data, we were able to draw conclusions concerning the changing transportation system in New York City and probable trends related to those changes. New York City Congestion Trends Report August

14 In order to study the effects of TNCs on congestion, we requested data from Lyft, which did not operate in New York prior to 2014, the beginning of our study period. The data from Lyft was used to identify the extent of Lyft services in Manhattan and across the East River. We also obtained data on the high-occupancy Lyft Line service, noting that Lyft Line trips serve Manhattan, Brooklyn, and Queens. Transportation Data The study team obtained transportation system performance data from INRIX and various government sources associated with the City of New York, the Port Authority of New York and New Jersey (PANYNJ), the State of New York, and the New York Metropolitan Transit Authority (MTA). Several data sources were used to support the various aspects of this analysis. One of the main sources is transportation performance data from the INRIX network, which includes 300 million vehicles, smart phones, cameras, and other sensors with the ability to cover nearly 5 million miles of roads, ramps and interchanges in over 50 countries. To complement the INRIX data, we utilized information from a variety of recognized authorities within the New York City region, including the New York City Department of Transportation (NYC DOT), The Port Authority of New York and New Jersey as well as the State of New York. In addition, in an effort to understand the potential impact on congestion of the increase in private hire vehicle registrations, we obtained data from the Taxi and Livery Commission and from Lyft to specifically address this issue. All of the data obtained from public agencies was obtained through publicly-available information sources such as web sites and online searches for public information shared by those agencies. Lyft Data Lyft delivered the New York City trip data for the first two weeks of October for all the data sets. The data sets include: Pulse (trips in 10 second increments) for the first two weeks in October 2017; Ride data with information about a trip s origin and destination (o/d data), time of passenger pick-up and drop-off, and status of the ride (finished/canceled/ in progress); Granular data (second-to-second trip data) for the first two weeks in October 2017; Aggregated spatial data indicating where high-occupancy rides (Lyft Line) occur; Aggregated area overview data parsed by day of the week, hourly brackets, all Lyft rides, and Lyft Line rides. The data obtained from Lyft was aggregated and entirely anonymized. None of the data that Lyft provided to the research team was used to trace individual route choices or obtain information on specific customers. 8 August 2018 New York City Congestion Trends Report

15 Public Agency Data We ve used the information from a variety of recognized transportation authorities such as NYC DOT, NYSDOT, and MTA. We obtained socio-economic characteristics using data from the U.S. Bureau of Economic Analysis, the NYS Department of Labor, the U.S. Bureau of Labor Statistics, the U.S. Energy Information Administration, the U.S. Census Bureau and the New York State Department of Motor Vehicles (NYSDMV). The report s data sources are summarized in Table 1. Table 1. Congestion Trends Report Data Sources Description Average Road Speeds, Travel Times U.S. Gross Domestic Product Employment Population Gas Prices Traffic Conditions Source INRIX, NYC DOT Travel Demand and Capacity Drivers U.S. Bureau of Economic Analysis NYS Department of Labor, U.S. Bureau of Labor Statistics U.S. Census Bureau U.S. Energy Information Administration E-commerce Vehicle Registration Driver Licenses in Force Bicyclist Volumes Protected Bicycle Lane Growth Pedestrians Volumes TLC Licensees Average Speeds, Travel Times East River Bridges Traffic Volumes Bus and Subway Ridership U.S. Census Bureau NYSDMV NYSDMV NYC DOT NYC DOT NYC DOT NYC TLC Performance Trends INRIX, NYC DOT NYS DOT MTA Manhattan Monthly Taxi and TNC Pickups Lyft Trends NYC TLC Lyft New York City Congestion Trends Report August

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17 Travel Demand & Capacity Drivers Transportation is a derived demand, meaning that trips are made as a means of getting someone or something from one location to another, not for the sake of the journey. People travel to work, for other business meetings, for social activities, for educational and health reasons, as well as to purchase goods or services required for daily life. Population growth drives travel demand in addition to many other economic factors that result in growing travel activity. In this section, we examine changes in economic activity, population, vehicle registrations, commerce, and travel mode choices. Overall, our research concluded that New York s population is growing steadily, freight and associated e-commerce deliveries are growing dramatically, and employment continues to rise within New York City. Growth in freight traffic in New York City is driven partly by an increase in delivery services related to e-commerce New York City s population continues to grow, leading to increased vehicle registrations The fraction of employed New York residents has risen as the City s employment base has grown, stimulating travel within New York NYC DOT is diligently working to accommodate and protect vulnerable users as it adds more bicycle and pedestrian facilities as part of Vision Zero. The total number of taxi medallions remain unchanged while TNC registrations have increased New York City Congestion Trends Report August

18 ECONOMIC AND EMPLOYMENT INDICATORS Gross Domestic Product Increased The 16 percent growth in the Gross Domestic Product (GDP) between 2014 and 2017 is mirrored by New York City s growth as the major economic center in the United States. The growth in Figure 1 appears to be a linear increase. More New Yorkers are Employed The same trend is visible in Manhattan where employment rates increased from 92.5 percent in 2014 to 96 percent in Figure 2 displays this rising employment. Overall, 266,000 more New York City residents became employed, a significant driver of mobility demand in the City and region. This is exclusive of all jobs added in New York City, many held by residents outside of the five boroughs. The percentage of New York City residents who are employed increased by 3.7 percent, from 91.9 percent in January 2014 to 95.6 percent in December Figure 1. Seasonally Adjusted GDP in billions of current dollars ( ) Source: Bureau of Economic Analysis 20,500 22,500 US GDP ($) 20,000 17,500 15,000 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q Quarter/Year 12 August 2018 New York City Congestion Trends Report

19 Figure 2. New York City Employment Rate, Seasonally Adjusted ( ) Source: Bureau of Labor Statistics % Employment Jan Mar May Jul Sep Nov Jan Mar May Jul Sep Nov Jan Mar May Jul Sep Nov Jan Mar May Jul Sep Nov Year POPULATION AND VEHICLE USE Population is Growing Steadily The population of New York City overall increased by 1.2 percent during the study period. Similarly, Manhattan population increased by 1.1 percent during study period. The daytime population of Manhattan, however, is much larger than the population of Manhattan residents. According to the U.S. Census, Manhattan s population is based on the number of people who domiciled in the borough. Since Manhattan is a concentration point for business and cultural activity, the daytime population is double the number of people who live in Manhattan. The population swells to 4 million people during a typical workday, according to estimates from the NYU Wagner School of Public Service. Gas Prices Declined Both gasoline and diesel prices declined by more than 25 percent during the study period, as displayed in Figure 3. New York City Congestion Trends Report August

20 Figure 3. New York City Gasoline and East Coast Diesel Prices ( ) Source: U.S. Energy Information Administration Dollars Per Gallon Jan Mar May Jul Sep Nov Jan Mar May Jul Sep Nov Jan Mar May Jul Sep Nov Jan Mar May Jul Sep Nov Year Gasoline Diesel More Personal Vehicles According to 2016 New York DMV data, the mix of vehicles registered in New York City is 89 percent personal vehicles, 4 percent commercial vehicles, 3 percent taxis, 3 percent motorcycles and 1 percent other vehicle types. Driver Licensing is Rising The number of driver licenses increased by 9 percent in New York City and by 7 percent in Manhattan from 2013 to A Changing Landscape One of the most significant findings of this report is the drastically-changing landscape in for-hire car services. According to the New York City Taxi and Livery Commission (NYC TLC), the total number of taxi medallions (as shown in Figure 4) has remained unchanged since 2014, at 13,587. Between 2014 and 2017, registrations classified as Black Car vehicles (typically TNC operators complying with local regulations) increased by 116 percent to nearly 84,000. Figure 4. Changes in Driver Population and Vehicle Use Source: NYS DMV, NYC TLC 3.787M (2016) 2.162M (2016) 84,000 (2017) 13,587 (2017) Drivers Licenses Vehicle Registrations Registered TNC Vehicles NYC Taxi Medallions 9% 3.474M (2013) 7% 2.016M (2013) 116% 39,000 (2015) NO CHANGE 13,587 (2015) 14 August 2018 New York City Congestion Trends Report

21 COMMERCE & FREIGHT While e-commerce creates more delivery truck traffic, some delivery trips are likely to replace individual trips that would have otherwise been made to the grocery store, the bank, or any other brick-andmortar shop. While e-commerce data specific to New York City was not available, it is expected that the national trend (shown in Figure 5) is representative of the e-commerce activity within New York City. Figure 5. Quarterly US E-Commerce ( ) Source: US Census Bureau U.S. Online Sales (millions of dollars) 140, , ,000 80,000 60,000 40,000 20,000 0 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q Quarter/Year New York City Freight Growth is Driven by E-Commerce The NYC DOT Strategic Plan addresses freight movement in New York. According to Part 5, Recent results from DOT s 2017 Citywide Mobility Survey indicate that 41 percent of New Yorkers receive a delivery of some kind at their home at least a few times a week. This growth is responsible for 400 million tons of cargo entering, leaving, or passing through the City of New York each year and 90 percent of that freight is moved using trucks. The report concludes that As the City s population and job base continue to grow, so will the demand for goods and services. The 2016 New York City Mobility Report identified an average annual growth rate of 1.8 percent between 2010 and 2013, before the recent exponential growth in e-retailing began for both residential consumers and, increasingly, business consumers in office buildings. New York City Congestion Trends Report August

22 NETWORK DISRUPTIONS & CLOSURES The roadway network in Manhattan is subject to a variety of recurring disruptions and temporary, short-term, and long-term closures. While unplanned disruptions such as emergency utility work and planned disruptions such as security-related road closures for significant events do occur, those are not ongoing and repetitive events that impact traffic operations on a regular basis. Parking Parking in congested areas like Manhattan can cause significant capacity constraints on the network. The circulation of vehicles looking for parking has been demonstrated to waste millions of dollars annually and needlessly contributes to carbon emissions. Double parking, freight delivery parking on narrow streets, and illegal parking in peak-period-only travel lanes blocks the use of roadways and is particularly problematic for people on bicycles. Increasing TNC use is offsetting singleoccupant vehicle trips that require parking in Manhattan, aiding efforts to optimize the use of street space for moving people rather than long-term storage of cars. Construction Construction closures related to building construction and public works activities also have an impact on street network performance. The closure of all or a portion of a street causes diversion to other streets that are already saturated and backups caused by flagging operations can cause queue spillback into intersections, creating attendant gridlock. Manhattan Streetscape Changes The streets of Manhattan serve a stunning array of needs. Balancing competing commercial, residential, and industrial uses of the curb, as well as the challenges of transporting a growing population and moving increasing volumes of consumer goods safely and efficiently, means that minor disruptions can often have major impacts on mobility. The NYC DOT has made changes to traffic signal operations in recent years. Some of these changes include systemic and systematic improvements related to safety. Two such changes include leading pedestrian intervals and a change in left turn signal operations. Leading pedestrian intervals, where the pedestrian WALK indication for a crossing is illuminated prior to the green indication on the parallel roadway approach, reduce the amount of time in each cycle that can be dedicated to vehicle movements. This increases delay for motor vehicles at the intersection and can result in longer queues, impacting the overall performance of at network or corridor. However, this is offset by a crash frequency reduction in pedestrian-involved left turn crashes. Left Turn Pedestrian and Bicyclist Crash Study by NYC DOT indicated that Leading Pedestrian Intervals treatment reduced overall pedestrian and bicycle injuries by 14%. Fatal or serious injuries declined by 56% for left turn-related collisions. 16 August 2018 New York City Congestion Trends Report

23 Pedestrians NYC DOT regularly collects pedestrian volumes in different parts of New York City. Pedestrian volumes have increased both in Manhattan and on the East River bridges, as displayed in Figures 6 and 7. The pedestrian counts during AM, midday, and PM peak hours in May were used for the analysis. Pedestrian volumes in Manhattan increased by 37 percent between 2012 and Pedestrian volumes across the East River increased by 200 percent between 2012 and Figure 6. Pedestrian Counts in Manhattan in May ( ) Source: NYC DOT 900, , ,000 Pedestrians 600, , , , , , Year Figure 7. Pedestrian Counts at East River Bridges May ( ) Source: NYC DOT Pedestrians 20,000 18,000 16,000 14,000 12,000 10,000 8,000 6,000 4,000 2, Year New York City Congestion Trends Report August

24 Bicycle Operations NYC DOT conducts regular bike counts using automated counters on the East River bridges, in Midtown (at 50th Street along the avenues) and Uptown (at 86th Street along the avenues), as displayed in Figures 8, 9 and 10. Over the study period, the number of cyclists has grown at all count locations in New York City. East River bicycle traffic has increased by 4 percent from 2014 to In Midtown, the number of cyclists increased by 22 percent from 2014 to The biggest growth occurred Uptown bicycle counts rose 33 percent between 2015 and Bicyclists Figure 8. New York City 12-Hour Uptown Bicycle Count at 86th St ( ) Source: NYC DOT 3,500 3, ,000 1,500 1, Year Bicyclists Figure 9. New York City 12-Hour Midtown Bicycle Count at 50th St ( ) Source: NYC DOT 3,500 3, ,000 1,500 1, Year +500 Figure 10. Average Cyclist Counts at East River Bridge Locations (2017) Source: NYC DOT 25,000 20,000 Bicyclists 15,000 10,000 5,000 0 Brooklyn Manhattan Williamsburg Ed Koch Queensboro Total Bridge 18 August 2018 New York City Congestion Trends Report

25 Protected Bike Lanes Figure 11 displays the substantial growth of bike lanes in New York City during the study period. Since 2007, the NYC DOT has installed more than 95 miles of protected bicycle lanes throughout the city. NYC DOT analysis of protected bike lanes on Manhattan arterials has found they have substantially increased safety for all road users. It is outside the scope of this document to evaluate motor vehicle travel pattern changes caused by the removal of travel lanes or the removal of parking lanes. However, bicycle network expansion can affect overall capacity and travel demand balancing within the street network, even if users of individual segments may experience improvements in travel times or average speeds. Ride-Hail Circulation Many studies have examined the effects of taxi circulation in congested cities and have determined that it is a cause of congestion. The circulation of TNC vehicles, however, is typically purposeful and part of the driver s activities in moving to the next pickup location. TNC operators have an interest in reducing vehicle downtime and thereby limit circulation to the extent practicable. Figure 11. Protected Bicycle Lane Growth in New York City ( ) Source: NYC DOT Annual Additional Miles Year New York City Congestion Trends Report August

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27 Performance Trends This report provides an analysis of performance trends in Manhattan below 96th St and for the East River crossings south of the Triboro. In order to obtain a comprehensive picture of congestion, we examined various metrics related to congestion, including travel time, average speed, and mode shifts to more efficient services. Travel speeds were calculated using INRIX s historical archive, derived from floating-car data, which allows attribution of speed data to specific roadway segments. The Manhattan study area exhibited an 11 percent reduction in vehicle speeds throughout the network. While the specific cause of the speed reduction cannot be isolated, many factors, including changes in vehicle volumes, street geometric changes, and shifting models of commerce, have an impact on mobility for motor vehicles. The City of New York, through its Vision Zero program, has implemented a variety of policies and street design changes both within the study area and citywide. These changes have succeeded in reducing fatal and injury crashes affecting vulnerable users. According to the City of New York Vision Zero Year Four Report, pedestrian fatalities citywide decreased by 32 percent between 2016 and Subway and high-occupancy Lyft Line trips improve efficiency of the transportation system Personal vehicle crossings of the East River are declining Taxi trips are declining as TNCs increase market share East River freight traffic continues to increase Lyft Line trips are increasing every year New York City Congestion Trends Report August

28 Some of the heaviest activity in multi-passenger Lyft Line service occurs in Manhattan. Our examination of the East River crossings revealed a more complicated story. East River crossing times have increased, and travel speeds have fallen slightly as the composition of East River crossing traffic continues to change. Personal vehicle and taxi trips are declining while freight trips continue to increase. The reduction in travel speed occurs during the afternoon peak commute period and is not coincident with the greatest growth in Lyft trips across the East River. Weekend trips comprise 35 percent of all weekly Lyft trips and 32 percent of daily Lyft trips occur between 6 PM and midnight. In fact, the growth in Lyft trips in the evenings may be comprised partly of transit customers who face maintenance delays and sparse or extremelycrowded late-night service on MTA trains and are choosing an alternative that suits their needs. PUBLIC TRANSIT TRENDS Annual subway ridership increased from 2014 to Subway ridership peaked at billion annual passenger trips in Between 2015 and 2017, subway ridership decreased by approximately 17,000 trips on an average weekday a 0.3 percent decrease. As displayed in Figures 12 and 13, the annual subway ridership fell by 1 percent in both Manhattan and overall in New York City between 2014 and Annual bus ridership decreased by 10 percent in New York City and by 15 percent in Manhattan. Figure 12. Annual Transit Ridership in New York City ( ) (Source: Metropolitan Transportation Authority) 3,000 Figure 13. Annual Transit Ridership in Manhattan ( ) (Source: Metropolitan Transportation Authority) 3,000 2,500 2,500 Passengers (Millions) 2,000 1,500 1,000 Passengers (Millions) 2,000 1,500 1, Year Year Subway Bus Subway Bus 22 August 2018 New York City Congestion Trends Report

29 MANHATTAN TRENDS We analyzed average speeds in the Manhattan study area using INRIX speed data and NYC DOT taxi speed data. The data in Figure 14 is INRIX-supplied Thursday average speeds south of 96th Street by time of day from 2014 to 2017, representing the typical congested weekday and typical for all vehicles. The taxi data presented alongside the INRIX data in Figure 16 is NYC DOT average daily taxi speeds south of 60th Street for the period from 2010 through The INRIX data, summarized in Figure 14, revealed that average vehicle speeds in Manhattan have decreased since Annual average speeds declined between 2014 and 2015 by 4 percent (0.5 mph), followed by 6 percent (0.6 mph) speed decrease between 2015 and 2016, and 2 percent speed (0.2 mph) decrease between 2016 and Roadways in Manhattan are typically most congested between 8 AM and 7 PM with the lowest speeds occurring between 3 PM and 6 PM. Figure 15 displays the monthly total number of taxi, TNC, and Lyft-specific pickups in Manhattan from 2015 to Since their introduction in late 2013, TNCs have increased their total market share of on-demand transportation to overtake taxis as the primary providers within Manhattan. The average number of on-demand TNC and taxi pickups exceeded 23 million per month in The comparison of Manhattan taxi speed data south of 60th Street, INRIX-based Manhattan speed data south of 96th St, and growth in Lyft trips is compiled in Figure 16. Historic speed trends from the recent NYC DOT mobility report indicate that the decline in taxi travel speeds, used as an indicator of overall street performance, began several years prior to the growth of TNC services and this speed decline has been relatively linear. The largest speed reduction in the Manhattan study area occurred between 2012 to 2015, before the rapid growth in TNC trips. Manhattan average daily speeds decreased between 2014 and Figure 14. Average Speed in Manhattan (study area) ( ) Source: INRIX 16 Average Speed in Manhattan (mph) (all roads south of 96th St) am 7am 8am 9am 10am 11am 12pm 1pm 2pm 3pm 4pm 5pm 6pm 7pm 8pm 9pm Time New York City Congestion Trends Report August

30 2016 and exhibited the smallest annual decrease between 2016 and There is an apparent difference between the INRIX-based vehicle speeds and taxi speeds that is likely caused by the geographic difference in study areas and by taxi-specific characteristics due to operations in Manhattan. Despite the difference in speeds, we observed that the trend between two data sets appears to be congruent. Figure 15. Manhattan Monthly Taxi vs TNC Pickups ( ) Source: NYC TLC 35 Number of Pickups (Millions) J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D Month/Year Taxi ALL TNCs Lyft Even as the number of Lyft trips has grown the most between 2016 and 2017, the average daily roadway speeds in Manhattan fell by approximately 0.2 mph during the same period. This slight decrease in average speeds, considered an indicator of congestion to many travelers, is nearly imperceptible to users of broad portions of the street network and is not concomitant with the rapid growth of TNC trips in New York City. Figure 16. Manhattan Daily Speeds and Lyft Trips ( ) Source: NYC DOT, INRIX, Lyft Avg Daily Roadway Speeds Year 80,000 70,000 60,000 50,000 40,000 30,000 20,000 10,000 0 Avg Daily Lyft Trips Average Daily Taxi Speeds INRIXAverage Daily Speeds Lyft Trips 24 August 2018 New York City Congestion Trends Report

31 EAST RIVER TRENDS In addition to using Manhattan as a key indicator of New York City roadway performance, we also assessed the six East River crossings. Four bridges and two tunnels provide for vehicular travel to and from Manhattan. These critical links have physical capacity restrictions, so the East River crossings were analyzed to understand changes in congestion for travel between Manhattan and the Long Island boroughs. Figure 17 summarizes the average speed for the six East River crossings for each hour throughout the day for average Thursdays in 2014, 2015, 2016 and Figure 17. East River Bridges/Tunnels Average Speeds ( ) Source: INRIX Speed (mph) am 1am 2am 3am 4am 5am 6am 7am 8am 9am 10am 11am 12pm 1pm 2pm 3pm 4pm 5pm 6pm 7pm 8pm 9pm 10pm 11pm Time Average vehicle speeds remained relatively consistent from 2014 to 2017 during the day (5 AM to 3 PM). However, average vehicle speeds during the afternoon and evening have decreased. During the PM peak period (3-7 PM) when speeds are lowest, observed speed reductions exceeded 8 percent between 2014 and The most significant change was apparent during the evening period (7 PM to midnight), when speeds decreased approximately 19 percent and congestion routinely persisted until after midnight. New York City Congestion Trends Report August

32 The vehicle type mix has also changed on the East River crossings. Travel by automobile, including taxis, decreased between 2014 and Table 2 displays an observed increase in freight vehicle traffic. An increase in truck traffic typically constrains roadway capacity and speeds due to the performance characteristics of these vehicles. Table 2. Change in East River Crossing Volumes by Vehicle Classification Source: NYC DOT PM Peak (4-7 PM) Personal Vehicle* Vehicle Classification Buses Single-Unit Truck Tractor- Trailer Total ,700 3,280 3, , ,700 2,810 2, ,600 Change -7, ,800 Change in % -5% -14% -12% 17% -6% * The Personal Vehicle classification in the table above includes both taxi vehicles and TNC vehicles. 26 August 2018 New York City Congestion Trends Report

33 CHANGING RIDESHARE LANDSCAPE Since its launch in New York City in July 2014, Lyft service has grown each year. Figure 18 summarizes the average number of Lyft trips by day of week. In 2017, Lyft provided an average of 73,000 trips per day within New York City. Lyft activity is highest on the weekends. In addition to the daily number of rides, we also examined the number of Lyft crossings of the East River in To determine the fraction of Lyft traffic overall, we compared data at the hourly level to examine the proportion of daily Lyft trips crossing the East River and peak congestion periods on those crossings. As Figure 19 shows, peak Lyft usage occurs during the evening (7 PM midnight), not during peak periods of congestion (4-6 PM) along the East River. Figure 18. Daily Lyft Trips in New York City ( ) Source: Lyft Trips 100,000 80,000 60,000 40,000 20,000 0 Sun Mon Tues Wed Thurs Fri Sat Day Figure 19. East River Lyft Crossings (Thursdays in October 2017) Source: Lyft Crossings 5,000 4,500 4,000 3,500 3,000 2,500 2,000 1,500 1, am 1am 2am 3am 4am 5am 6am 7am 8am 9am 10am 11am 12pm 1pm 2pm 3pm 4pm 5pm 6pm 7pm 8pm 9pm 10pm 11pm Time New York City Congestion Trends Report August

34 The peak period of Lyft use does not coincide with the lowest travel speeds recorded for the East River crossings, as indicated in Figure 20. While peak Lyft activity occurs during times when speeds decreased most significantly (between 7 PM and midnight), Lyft only accounts for a small portion of the vehicle mix at this time. In fact, the vehicle mix has changed on East River Crossings and 2017 data indicates that more freight vehicles use the crossings. As freight vehicles tend to have a greater impact on segment speeds due to their characteristics, it is plausible that Lyft activity is not the primary contributor to the observed late evening decline in crossing speeds. Speed (mph) Figure 20. Hourly Profile of East River Crossing Speed and Lyft Activity Source: Lyft, INRIX am 1am 2am 3am 4am 5am 6am 7am 8am 9am 10am 11am 12pm 1pm 2pm 3pm 4pm 5pm 6pm 7pm 8pm 9pm 10pm 11pm % of Daily Lyft Trips Time Travel Speed Lyft Trips 28 August 2018 New York City Congestion Trends Report

35 HIGH-OCCUPANCY RIDESHARE TRENDS Lyft introduced Lyft Line service in New York in the last quarter of This service allows riders to join trips in progress, creating a high-occupancy service that is not provided by taxis. As displayed in Figure 21, Lyft Line trips continue to grow and presently comprise approximately 30 percent of all Lyft trips in New York City. Figure 21. Lyft Line Growth ( ) Source: Lyft 4 Rides (Millions) / / / / / / / /2018 Month/Year All Rides Lyft Line Rides According to Lyft s data, some of the heaviest activity in multi-passenger Lyft Line service occurs in Manhattan. Lyft s increasing multi-passenger trips are aiding travel across the East River and throughout New York by increasing the fraction of vehicles that are high-occupancy and eliminating the need to store cars in Manhattan in particular. As more people abandon single-occupant taxis and personal vehicles in favor of convenient Lyft Line service, Lyft s ability to change the ratio of high-occupancy to single-occupancy vehicles is likely to make an even bigger impact on carbon emissions and reduced personal vehicle trips. New York City Congestion Trends Report August

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37 Findings & Conclusions This study explored the drivers of congestion and evaluated various aspects of transportation system performance in New York City. Transpo Group identified various publicly-available data sources related to economic growth, population and demographic trends, and transportation system management. After evaluating the drivers of demand, we obtained Lyft data in order to understand how Lyft serves New York City trips. Travel demand is growing in New York City Our evaluation of the drivers revealed that trip growth is being driven by economic activity, justified by the following findings: Population and jobs are growing Freight and delivery traffic is growing in New York City The decline in MTA subway ridership is just 0.3 percent, or 17,000 daily trips, between 2014 and 2017 More people are riding bicycles and walking Average speeds in the Manhattan study area between 2016 and 2017 exhibited a very small decrease compared to previous years; Lyft trip growth was greatest between 2016 and 2017 VMT and personal vehicle trips across the East River have fallen even as Lyft and TNC crossings rise Lyft is serving more high-occupancy trips than ever before and may be a factor in the reduction in motor vehicle crossings of the East River New York City Congestion Trends Report August

38 Manhattan travel speed reduction, one indicator of congestion, is not concomitant with growth in Lyft trips Lyft is serving more high-occupancy trips than ever before and may be a factor in the reduction in motor vehicle crossings of the East River. Additionally, Lyft and TNC registrations have grown by 116 percent while Lyft trips have increased by 2600 percent. This points to the ability of the TNC ride-hailing model and complex management systems to efficiently absorb and route numerous trips. Manhattan travel speed reduction, an indicator of congestion, is not concomitant with growth in Lyft trips. Based on this key finding, summarized on page 24, we can observe that the dramatic increase in Lyft service since 2015 is not accompanied by a corresponding large reduction in average speeds. The key findings from this report indicate that it is not possible to conclude that Lyft is the primary contributor to the growth of congestion in New York City. A complex array of factors influences It is not possible to conclude that Lyft is the primary contributor to the growth of congestion in New York City the growth and severity of congestion. Cities around the world have sought to mitigate congestion with a variety of approaches beyond civil infrastructure projects, which can also be very successful at removing large volumes of long-distance traffic from a City s dense urban areas. These strategies include the following approaches: Signal Optimization and Coordination Transit Signal Priority and Adaptive Traffic Signal Control Curb Management and Responsive Freight Management Policies Dynamic Parking Pricing, Monitoring, and Information Systems Camera Enforcement of Loading Zones and Double Parking Hot Spots Congestion Pricing for both Segments, and Cordons 32 August 2018 New York City Congestion Trends Report

39 SUPPORTING DOCUMENTS City of New York, Vision Zero Action Plan. City of New York, For-Hire Vehicle Transportation Study. Office of the Mayor City of New York, Vision Zero Year Four Report. New York City Mayor s Office of Operations Clewlow, R.R. and Mishra, G.S., Disruptive transportation: The adoption, utilization, and impacts of ride-hailing in the United States. University of California, Davis, Institute of Transportation Studies, Davis, CA, Research Report UCD-ITS-RR Schaller, B., Unsustainable? The growth of app-based ride services and traffic, travel and the future of New York City. Report by Schaller Consulting, Brooklyn NY. Circella, G., Alemi, F., Tiedeman, K., Handy, S. and Mokhtarian, P., The Adoption of Shared Mobility in California and Its Relationship with Other Components of Travel Behavior (No. NCST-RR ). Li, Z., Hong, Y. and Zhang, Z., An empirical analysis of on-demand ride sharing and traffic congestion. Thirty Seventh International Conference on Information Systems, Dublin. MAPC, Fare choices a survey of ride-hailing passengers in metro Boston. A Metropolitan Area Planning Council Research Brief Moss, M.L. and Qiup, C., The Dynamic Population of Manhattan, New York. National Academies of Sciences, Engineering, and Medicine Broadening Understanding of the Interplay Between Public Transit, Shared Mobility, and Personal Automobiles. Washington, DC: The National Academies Press. New York City DOT, 2016, Left Turn Pedestrian and Bicyclists Crash Study, New York City DOT, 2018, New York City Mobility Report.