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What a Transportation Professional Needs to Know About Counts and Studies during a Pandemic

JULY 2020

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What a Transportation Professional Needs to Know about Counts and Studies during a Pandemic

Institute of Transportation Engineers 1627 Eye Street, NW, Suite 600

Washington, DC 20006 USA Telephone: +1 202-785-0060

Fax: +1 202-785-0609 www.ite.org

Publication No. IR-148-E July 2020

© 2020 Institute of Transportation Engineers. All rights reserved. No part of this publication may be reproduced, distributed, or transmitted in any form or by any means, including storing in a retrieval system, photocopying, recording, or other electronic or mechanical methods, without the prior written permission of the publisher, except in the case of brief quotations embodied in critical reviews and certain other noncommercial uses permitted by copyright law. For permission requests, write to the publisher at the above address. Printed in the United States of America ISBN-10: 1-7345078-2-9 ISBN-13: 978-1-7345078-2-9

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Acknowledgements This White Paper was developed by a volunteer technical committee that was formed for this purpose. Contributors to the development of the material in the White Paper include the following: Randy McCourt (Committee Chair) Joey Bartus Alison Felix Ruben Gallegos Kevin Hooper Jonathan Kiser Wayne Kittelson Karyn Robles Matthew Skelly Mike Spack Ted Trepanier

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A Guide to What a Transportation Professional Needs to Know about Counts and Studies during a Pandemic

Purpose To provide ITE members and practitioners guidance on the types of questions, issues, and decisions they will have to make regarding traffic counting in the fluid and dynamic circumstances of the current pandemic (or other future unusual circumstances). We all are in awe of the speed and magnitude of changes in trip-making we have witnessed over the past few months, and fully expect continued change will be the norm for some time. To be in the midst of these changes while trying to make sense of them can be overwhelming. Ferris Bueller: "Life moves pretty fast. If you don't stop and look around once in a while, you could miss it." Ferris Bueller’s Day Off, 1986 Overview Over the past four months, typical transportation activities have changed significantly with the COVID-19 pandemic. Events that impact transportation are not that uncommon; from solar eclipses to Super Bowls. However, this event is unprecedented in its global reach, its unknown duration, and the fact that “normal” is unlikely to return after the event. We have already witnessed altered home and work environments, travel patterns, and unprecedented reductions in congestion. As the pandemic transitions from outbreak to management, some of these changes are returning to normal while others are establishing a “new” normal. The roadmap into the future involves us all. In May 2020, an ITE Task Force was formed to address various questions the transportation profession is facing regarding the management of collecting traffic data during the pandemic and into the future. These are the findings and guidance from the Task Force. Much information is hyperlinked to various sources of information that our members may find of value. The Task Force was not charged with establishing policies, recommended practices, or instructing others on how to utilize judgement in complex times as these. (The identification of one private data source over another or of one set of guidelines over another should not infer any preference on the part of the authors.) This simply represents our best thoughts on available resources, issues, and topics that ITE members may encounter and some prudent perspectives on how to proceed in utilizing good data practices within available resources. The first two sections, Counts, Studies, and Why? and Ethics present issues to ponder. The subsequent four sections, Interim Guidance and Policies, When will Normal Return? Forecasting, and Trip Generation all provide insight and guidance related to these issues. One characteristic we have all observed during these unusual times, is that conditions are changing; if not weekly, then daily. Everything presented here will change, likely before you read this. Many of the websites referenced in this guide are updating daily. We expect that by the Transportation Research Board Annual Meeting in January 2021, the Task Force will need to refresh this assessment and highlight new findings. We expect members will contribute to the discussion about these revelations in real time (such as ITE e-Community or ITE Drop-Ins) as

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we engage together in greater understanding of the pandemic and its impacts to the transportation profession.

COUNTS, STUDIES, AND WHY? Many in the transportation profession are directly involved in counts or data and their use in studies, designs, and decision making. If counts were scheduled for mid-March, they most likely were not completed or may have been deferred until the fall of 2020. The travel impacts of COVID-19 led to immediate 40-60 percent reductions in both volume and VMT on many principal roadways. In contrast to the Great Recession, which saw VMT growth curtailed and reductions of 2-3 percent, the pandemic reductions were remarkable. Following are some of the questions ITE identified and some guidance that will help you determine the best plan of action as it relates to your study or project. It’s important to know the intended use of a count as that can help determine the appropriate actions (e.g., citizen requests, count programs, forecasting, signal retiming, etc.). Although the path to data normalization must be determined for there to be meaningful infrastructure additions/modifications, there may be substantial value in using pandemic data as a resource for future pandemic planning and coordination with other public entities. Certain count programs and citizen requests for data may be able to be deferred to later times. Studies and time-dependent capital projects may not be able to be delayed, requiring alternative base count development such as the following:

1. Past data - there are numerous sources of historical counts but there can be challenges in finding and acquiring the data

a. Silos of counts - DOT, City, County, MPO, RPC, consultants, and count firms (several count firms have extensive databases (a few examples include https://www.ndsdata.com/ https://data.qualitycounts.net/)) of historic counts; all have data, not to mention departments within organizations

b. Lack of standard formatting and available metadata 2. Doing counts - adjustments will likely be needed and consideration given to several

issues a. When will traffic return to normal?

i. There will likely be a “new normal” that will need to account for a national increase in the work-from-home model, trucking moving into peak periods that had been historically congested, national increase in remote schooling, and changes in transit use. The collective effect could be different regionally and take time to find “new equilibrium.” One of the key indicators available to determine when the new normal is in effect may be when schools have fully returned and remain back in session.

ii. Time-of-day changes - while daily counts are nearing pre-pandemic levels in some areas, the traditional peak hour counts remain quite different. Looking at ADT numbers alone will not be a good indicator of “return to normal” For example, traditional peaks remain lower and mid-day is

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higher; potentially related to increased work from home. It is very likely the new normal will be more about understanding new time of day distributions than total volume.

b. How can I get counts done? i. Resources are available to undertake various short -term and long-term

data collection projects. National and local count firms have seen a decrease in active projects. Availability and capacity are currently at their highest.

c. What are some things to consider? i. Work-from-home

1. Many companies have made temporary or permanent workflow adjustments that allow for remote working arrangements. This has had an unpredictable impact on the traditional AM and PM peak period. Conditions include the following:

a. Permanent work-from-home conditions b. Alternating in-office work weeks c. Partial day in-office work weeks d. Staggered in-office daily shifts

2. Weekday averages may need to be relied on to appropriately capture this abnormal commuting activity. Using probe data (see below) or considering an average of two-to-three days of weekday peak hours may be necessary in place of one single weekday data.

3. Volume (turn, link, mode, classification), speed, parking, travel time, and transit boarding can all be done; producing trending of pandemic impacts; however, until a vaccine becomes available, any 2020 counts should be used with caution and will likely require an “*” note.

ii. Reduced consumer driving behavior 1. Online consumerism may increase while brick-and-mortar

consumerism decreases. This may not be quantifiable in a meaningful way for quite a while, after a vaccine is available.

iii. Remote schooling 1. Several public and private schools have partially transitioned to

virtual learning environments. It’s still unclear how long this option will remain. In the short term, peak school activity may look very different during the drop-off and pick-up periods. For colleges and universities, the impact on traffic may depend on the percentage of students that live on campus vs. off campus.

iv. Studies that do not rely on vehicle, pedestrian, and bicycle volumes can be performed without concern of the COVID impact.

1. GIS/GPS Asset Inventory Studies 2. MIRE Studies 3. Ball Bank/Horizontal Curve Studies

3. Big Data

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a. Probe data is available to provide trending before-during-after COVID. Probe data can consist of both in-vehicle GPS units, which have frequent and highly- spatial accurate location pings, as well as location-based services (LBS) data which have less frequent, yet still highly-spatially accurate location pings. In-vehicle GPS data has shown to be a good resource for speed studies, while the larger sample size of LBS data has been proven effective for understanding trip routing and trip counts on roadways.

b. There are case studies of replacing count programs in the interim with big data (an Oklahoma example case study is provided from Streetlight).

c. Geospatial information about parking lot usage can serve as a measure of economic activity and traffic congestion. For example, BlackSky uses image recognition to determine how many cars are in parking lots and then uses software to compare those numbers against a baseline. “How BlackSky’s Spectra Geospatial Data Platform Uses AI to Make Sense of Satellite Images” (GeekWire, May 11, 2020)

d. Data is growing rapidly, both in density and types. As an example, INRIX trip samples increased approximately 10 fold during 2019. How you validate data is important and there are resources (such as this Streetlight White Paper) available to consider these issues.

e. Hybrid - Some use cases may be serviced by combining available ground counts with continuous probe data to fill in gaps or save costs of added counting.

f. Who has the data? This is an open question as new sources become available. Transportation data has been available for many years from companies such as INRIX, HERE, Streetlight, AirSage and TomTom. Newer sources include companies like Wejo and Otonomo. These data sets have strengths and weaknesses related to accuracy, depending upon the applications and context. Users should inquire about level of accuracy and consider doing pilot tests to validate appropriate applications before committing large resources to projects.

g. Call and inquire - as available data is growing rapidly, staying informed on sources and associated use cases can be a real challenge. Pricing is also changing rapidly and subject to negotiation. A classic Google search may be a good start to investigate sources specific to individual use cases but much of the information will most likely be dated. All the reputable companies have technical and sales contacts who can provide updated information and, in most cases, offer free samples for evaluation.

ETHICS Ethical issues surrounding the need, use, and creations of counts should not be ignored. Section 6 of the ITE Canon of Ethics states: The member will express an opinion on a professional subject only when it is founded on adequate knowledge and honest conviction. As transportation professionals are asked to do their job and complete projects, what is within the boundaries of adequate knowledge and honest conviction? Much of this falls within the topics presented in this guide.

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Adequate Knowledge

● How do you determine adequate knowledge? ● What is this related to context? Rural Walmart? Urban downtown? Airport parking study? ● What counts are adequate? Which land uses/areas are impacted and which are not? ● When will traffic bounce back? Can you accurately estimate mode shift changes from

transit and carpool to other modes and work-from-home? ● Have we ever been able to forecast with 100 percent accuracy? What are the ranges of

outcome or risks; have they changed? ● Should we continue our routine counting programs?

Honest Conviction

● What are the tools one can utilize? ● What is the thought and documentation process? ● Identification of where you have utilized judgement and how? Transparency? ● Objective decision making v. discretionary decisions

○ For Agency Staff: To provide adequate knowledge for our profession, it is prudent to continue Counting Programs to provide historical data for future decisions. Studies related to maintenance and safety issues should be done to fulfill our fiduciary responsibility to the public (per Sections 1, 3, 4, 8, and 12 of the ITE Canon of Ethics). Studies undertaken to solve congestion should be done only if solutions can be delivered with honest conviction, which requires judgement given the uncertainty of the pandemic’s impacts in some regions.

○ For Firm Staff: It is ethical to deliver studies as requested by clients if you have adequate knowledge and can deliver the study with honest conviction.

The decision to resume counting programs associated with Highway Performance Monitoring System annual reporting requirements is an example of where decisions are unclear. The Federal Highway Administration (FHWA) has not directed suspension of coverage/spot counts and has left decision-making to the states. The decision to utilize estimates based on 2019 data or conduct counts and when is complex. Reviewing the wealth of data sources available (many noted in this document) should be considered to inform these decisions later this summer and early fall. The findings of this paper are provided to professionals to assist in their guidance on completing studies that can be founded on adequate knowledge and delivered with honest conviction.

INTERIM GUIDANCE AND POLICIES ISSUED BETWEEN MARCH - JUNE 2020 Some DOTs, Councils of Governments, counties, municipalities, as well as the private sector have developed interim guidance and policies on conducting traffic counts and advancing studies during COVID-19. Overall, the interim guidance and policies require consultation with

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agencies prior to conducting traffic counts, specific provisions regarding the collection of traffic count data, or pausing the collection of traffic count data entirely. The following are representative interim guidance and policies from around the country developed by the public and private sectors respectively: Public Sector Connecticut - Connecticut DOT - April 2020 https://portal.ct.gov/-/media/DOT/documents/dstc/COVID-19-Traffic-Volume-Information.pdf

● Existing traffic counts for use in Department traffic impact studies and projects should not be conducted until further notice.

● The Department’s Bureau of Policy and Planning should be consulted regarding the following:

○ Available historic data and/or techniques to develop acceptable background traffic volume information.

○ Any existing traffic counts that may have been conducted since March 1, 2020 for the intended use in traffic impact studies and projects; Department to determine if the counts are relevant.

Louisiana - Louisiana Department of Transportation and Development - May 12, 2020 website posting http://wwwsp.dotd.la.gov/Inside_LaDOTD/Divisions/Engineering/Traffic_Engineering/Pages/default.aspx The Louisiana Department of Transportation and Development is investigating ways to collect traffic data. The Department will provide their procedure when complete, which will be no later than mid-August, 2020. Maryland - Montgomery County Planning Department Briefing on Temporary Policy for Traffic Counts Collection and Transportation Impact Study Submission During COVID-19 Pandemic - May 7, 2020 https://montgomeryplanningboard.org/wp-content/uploads/2020/04/COVID-19-Traffic-Count_TIS-Policy-Briefing_050720_final.pdf

● The Planning Department established a policy to suspend traffic count data collection in the County until further notice. At the same time, the Department does not want to inhibit development applications and master plan evaluations from proceeding.

● Recommend a combination of a Growth Factor Approach and a Traditional Counts After

Specified Time Approach be used. Under this recommendation, no new counts for development applications or master plan evaluation shall be collected until fall 2020.

● Until new traffic counts can be collected, a Transportation Impact Study (TIS) in support

of a Preliminary Plan or Site Plan application may proceed if existing counts for all critical intersections of the proposed development have been collected within three years of the application submittal.

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● For new subdivision applications where no traffic counts have occurred, an application

may be submitted without the required TIS. However, a TIS will need to be submitted and reviewed before a public hearing is scheduled.

● This policy mirrors the policy adopted by the Prince George’s County Planning Board on April 9, 2020.

● The Planning Department will continue to investigate opportunities to utilize innovative approaches such as “Big Data” to estimate traffic counts.

Massachusetts - MassDOT Traffic Count Data Collaborative - April 13, 2020 https://www.acecma.org/about/news/massdot-traffic-count-data-collaborative-3009

● MassDOT is collaborating with municipalities, regional planning agencies, and private industry to make historical traffic count data more easily accessible to those who need it.

● In the short-term, MassDOT will set up a traffic count repository where consultants are

encouraged to upload historical count data so designers and public agencies may all view, share, and utilize for their own projects. This count library will assist with the development of design projects that may otherwise slow down or stop entirely due to the lack of reliable existing traffic data.

● The long-term goal is to cooperate with traffic data collection companies to leverage

MassDOT’s existing Transportation Data Management System to incorporate raw count data that meets the Department’s QA policies, so that it may be processed, geolocated, and made publicly available.

Massachusetts - MassDOT Engineering Directive - May 11, 2020. https://www.acecma.org/about/news/massdot-issues-new-traffic-data-guidance-as-of-5-11-20-3028

● The purpose of the Engineering Directive is to provide guidance on how to estimate existing and future traffic counts in lieu of taking new traffic counts after March 13, 2020.

● Due to reductions in traffic volumes caused by the COVID-19 pandemic, taking new traffic counts in 2020 may undercount the baseline for which future years are based.

● This Directive introduces and makes effective the MassDOT Guidance on Traffic Count Data dated April 2020.

● Historical traffic data may be used on any project to supplement and/or replace existing traffic counts, as long as it conforms to the latest version of the MassDOT Guidance on Traffic Count Data.

● The Directive includes all projects submitted to MassDOT.

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New Mexico - Mid-Region Council of Governments (MRCOG) - website posting https://www.mrcog-nm.gov/285/Traffic-Counts The regional traffic managers within the Albuquerque Metropolitan Planning Area have determined that current data-counting efforts in support of new project proposals would not be representative of actual traffic conditions. All analysis must be coordinated with local agency guidance and consultation, studies will be handled on a case-by-case basis, and should include additional data sources for project analysis and impact mitigation efforts. Oregon - Portland Bureau of Transportation Guidance – Traffic Count & Speed Data, Collection and Analysis During Pandemic - June 26, 2020 https://www.portlandoregon.gov/transportation/77397 Guidance for Collection of Traffic Volume Data

● Use historical peak hour count data within 18 months prior to emergency declaration (March 2020).

● Inquire with City staff to determine if there is an adjustment factor that can be applied from nearby active traffic count locations.

● If recent count data is not available, the traffic engineer may collect current traffic count data and apply an adjustment factor determined using data over the most recent two-year period prior to emergency declaration from: Oregon Department of Transportation (ODOT) automatic traffic recorder stations, ODOT annual corridor volume counts, or City-maintained permanent count station or signalized intersection with real-time detector data collection.

● All traffic studies shall use the current 1.5 percent/year background growth rate from data collection year to buildout year.

Guidance for Collection of Traffic Speed Data

● Portland Bureau of Transportation (PBOT) will consider new speed counts as usable data for traffic impact studies, speed zone investigations, and other studies.

Analysis Requirements for Traffic Data

● PBOT Traffic Scoping forms must be completed and approved for land use actions. ● Include statement regarding reduced traffic volumes due to emergency declaration. ● Cite all data collection sources and methods and include calculations of all adjustment

factors in the report’s appendix. Texas - City of Dallas DOT - website posting https://dallascityhall.com/departments/transportation/Pages/default.aspx Temporarily suspended all services that will require data collection involving traffic studies, traffic warrant analysis, and pedestrian counts.

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Virginia - Fairfax County DOT COVID-19 Traffic Count Guidance - May 1, 2020 https://www.wellsandassociates.com/wp-content/uploads/2020/05/2020-5-1-FCDOT-COVID-19-Traffic-Count-Guidance.pdf

● Fairfax County DOT has determined to utilize historical traffic data as the foundation for traffic impact studies conducted during the COVID-19 crisis.

● Collected traffic count data during COVID-19 is not acceptable for development analysis. ● Turning movement counts collected within the last two years are generally acceptable. If

beyond the two-year threshold, site specific adjustment factors and changes in land use should be investigated.

● Every project will need to be evaluated on a case-by-case basis. ● Coordination and approval from Fairfax County DOT and Virginia DOT is necessary. ● Fairfax County DOT and Virginia DOT will determine acceptable methodologies in

coordination with applicants prior to study submission. Washington - Clark County Public Works Guidance – Required Traffic Count Data, Collection and Processing - March 20, 2020 https://www.kittelson.com/wp-content/uploads/2020/03/3-18-20-CCC-40.350.020-D4-Traffic-Count-Data-Collection-Emergency-Event-Policy-Managment-Decision-Final.pdf

● Peak hour count data within 12 months of being deemed fully complete may be used. ● If peak hour count data is not available within 12 months of being deemed fully

complete, current traffic count data may be collected with specific provisions that include the following:

o South Washington Regional Transportation Council volume counts are available and sufficient to evaluate traffic growth over the most recent two year period.

o Applying an adjustment factor to the collected data. ● Required to use the 2 percent/year background growth rate from current year to buildout

year. Private Sector Alliant COVID-19 and Traffic Counts: Making Good Decisions with Less Data. (April 14, 2020) http://www.alliant-inc.com/covid-19-and-traffic-counts-making-good-decisions-with-less-data/

● Look for historical counts. ● Look for nearby counts. ● Review historical growth rates and agency transportation plans. ● Collaborate with consultants and agencies who may have historical counts, including

video archives. ● Big Data – Couple big data sources (e.g., Streetlight, INRIX, ClearGuide) with other

known traffic volume sources.

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Kimley Horn Traffic Studies During COVID-19: Keep Projects Moving Using Big Data (May 28, 2020) White Paper – Proposed Methodology for Developing Intersection Turning Movement Volumes Using Historical Counts and Big Data (May 2020) https://www.kimley-horn.com/traffic-studies-covid-19/

● Methodology prioritizes getting the most out of any available count data. ● Paper identifies where and when big data may be a good supplement to this traditional

resource. ● Data may be sourced from a variety of providers including Azure/Tom-Tom, Waze,

Google, and we are currently exploring a powerful integration with INRIX. ● Contains a decision tree which summarizes the basic process outlined in the paper for

determining the best mix of count data and big data at any given project intersection. The decision tree below helps identify the most appropriate method for developing existing conditions turning movement volumes.

Kittelson & Associates, Inc. White Paper - Estimating Traffic Volumes Under COVID-19 Pandemic Conditions (April 2, 2020) https://www.kittelson.com/wp-content/uploads/2020/04/Traffic_Volume_Estimates_Kittelson_April_2020.pdf

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Article - Collecting Traffic Counts When There’s No Traffic https://www.kittelson.com/ideas/collecting-traffic-counts-when-theres-no-traffic/ The article and white paper outline the following four steps to develop proxy volume estimates:

Step 1: Establish project context and data needs. Step 2: Coordinate with appropriate agencies. Step 3: Identify available data resources.

Resources can include the following: ● Traffic data collection companies. ● Public agencies that conduct their own independent traffic count programs. ● Published transportation studies (e.g., Long-Range Transportation Plans,

Transportation System Plans, Corridor Plans, and Transportation Impact Studies).

● Applying User-Generated Data from emerging technologies such as Connected Vehicles and Bluetooth readers. Traffic data aggregators (such as StreetLight, Moonshadow, Wejo and INRIX) collect these types of data.

● Data using video surveillance cameras, road tubes, manual counters, and drones.

Step 4 Develop proxy volume estimates Wells + Associates: Yes DMV, You Can Forecast Traffic Counts for Traffic Impacts Studies During COVID-19 (May 4, 2020) https://www.wellsandassociates.com/blog/dmv-traffic-counts-during-covid-19/ This article outlines ways to develop accurate baseline traffic counts to keep projects moving forward. This includes using historical traffic data and working with the public sector to develop traffic count adjustment factors. Sin Associates: Big Data as an Alternative for Traffic Counts during COVID-19 (June 2, 2020) http://www.sain.com/blog/big-data-as-an-alternative-for-traffic-counts-during-covid-19/

● Why use Big Data for transportation studies in the future? ● What are some of the disadvantages of using Big Data for transportation studies?

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WHEN WILL NORMAL RETURN? Many people have questions about whether traffic volumes and congestion will return to normal. Unlike an eclipse, 9/11, a Super Bowl, construction, hurricanes, or other major events that have disrupted travel, several long-term forces are at play that make a full return to normal like these other events very unlikely. For example, the work-from-home (WFH) genie is out of the bottle. As technologies are advancing rapidly to facilitate WFH, there is little likelihood that the historic ACS 4-5 mode share for WFH will return. Many employers are staggering work shifts, such that even though they are open and working a variety of flexible work hours scenarios (MWF + Tu/Th and Tu/Th + MWF, work in office one week/out of office 2 weeks), the employee density is below typicals prior to COVID-19. Even with the various surveys of worker acceptance of WFH (https://zapier.com/blog/wfh-report/), there is economic motivation for both employees and employers. It has been estimated that an employee can save $10-15,000 annually by working from home. Employers can benefit from both gains in employer productivity and overhead savings ($2,000 to $4,000 per employee annually in overhead alone). https://globalworkplaceanalytics.com/telecommuting-statistics) It is anticipated that the next American Community Survey could indicate WFH to be between 10-12 percent (or higher), a significant increase from the last 2018 ACT report which conveyed the historic rate of 5 percent. (https://www.enotrans.org/article/2018-acs-survey-while-most-americans-commuting-trends-are-unchanged-teleworking-continues-to-grow-and-driving-alone-dips-in-some-major-cities/). And rates of WFH will not be uniform for employers as some work sectors (high tech and government services) may be more suited to long-term growth in this mode of operation. There are several resources available to monitor traffic volumes such as the following:

● The USDOT/FHWA issues a monthly report of nationwide Traffic Volume Trends. The Traffic Volume Trends are based on hourly traffic count data collected at approximately 5,000 continuous traffic counting locations nationwide and are used to estimate the percent change in traffic for the current month compared with the same month in the previous year. Estimates are re-adjusted annually to match the vehicle miles of travel from the Highway Performance Monitoring System and are continually updated with additional data. In May 2020 the following data was reported:

● Travel on all roads and streets changed by -25.5 percent (-72.9 billion vehicle miles) for

May 2020 as compared with May 2019. Travel for the month is estimated to be 213.2 billion vehicle miles.

● The seasonally adjusted vehicle miles traveled for May 2020 is 199.8 billion miles, a -26.1 percent (-70.6 billion vehicle miles) decline from May 2019. It also represents a 24.1percent increase (38.8 billion vehicle miles) compared with April 2020.

● Cumulative Travel for 2020 changed by -17.3 percent (-227.2 billion vehicle miles). The cumulative estimate for the year is 1,087.0 billion vehicle miles of travel.

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Region Total Travel in May 2020 (in billion vehicle miles)

Percent Change in VMT (May 2019 to May 2020)

North-East 26.8 -33.4%

South-Atlantic 47.9 -26.1%

North-Central 46.2 -26.3%

South-Gulf 46.0 -19.8%

West 46.3 -24.3%

Total 213.2 -25.5%

● The Bureau of Transportation Statistics has an Explore U.S. Mobility During the COVID-19 Pandemic website from which users can learn about U.S. mobility at the National, State, and County levels by using interactive maps, charts, and graphs in the following three categories:

➔ Map of Activity by State or County ➔ Mobility Over Time: National, State, and County level ➔ Distribution of Trips by Distance: National, State, and County level

The underlying data are also available for download and further analysis. The BTS also offers an inventory platform from which users can create their own visualizations.

● Another resource is the COVID-19 Community Mobility Report which is updated daily by

Google. This report tracks mobility changes in retail/recreation, grocery/pharmacy, parks, transit stations, workplaces, and residential areas across the globe which users can even view down to the County level. Users can also view congestion on Google Traffic in every metro area and compare “today” to typical conditions anytime you want. Monitoring Google Traffic over the pandemic leads to a few of the following observations when trying to assess “are we there yet” in terms of normal:

➔ Certain employment sectors may be more prone to larger shares of work from home. This may continue into the future differently than other uses. Two such uses are the public employment and the technology sector. Monitoring Sacramento’s (a major public employment center), return to congestion has not followed other West Coast metro areas. This also seems to be the case for hi-tech. None of the corridors in Silicon Valley (SF Bay Area), Redmond (Seattle area), Silicon Forest (Portland area) and Irvine (LA area) have experienced the return to congestion consistent with the remainder of their regions.

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➔ Transit-dependent areas are likely to experience greater WFH than others, as the transportation network rebalances and transit ridership recovery takes hold following a vaccine.

➔ Corridors exiting metro regions may be more congested as recreational trips shift from air to ground travel, particularly through the summer months, approaching weekends, and holidays. At the same time, congestion near airports will likely be depressed until after the vaccine is in place.

The micromobility disruptions of the last decade are likely to take new flight post-pandemic for short trips. But concerns about cleanliness present a barrier to growth. This is a significant impact to transit as we knew it prior to COVID. Surveys of commuters show deep concerns about returning to close spaces and poorly-maintained (cleanliness) travel modes. And while initial surveys show similar likely use between micromobility and transit, will the decision to use a more controlled environment (ride hailing) be perceived more openly than a mass transit environment?

https://www.wbur.org/bostonomix/2020/05/27/massinc-polling-coronavirus-reopening-transportation-mbta-driving While travel trends in the USA indicate in many locations that July 2020 will produce regional VMT and volume data similar to pre-COVID conditions, there is much to be wary about in localized travel. CBDs, areas near airports, schools, shopping centers, and other major trip generators continue to have significantly lower vehicle travel. Their recovery will be longer before they see travel levels closer to pre-COVID conditions (if at all). There are plenty of resources that are tracking VMT; these from INRIX (below) and Streetlight are shown as examples.

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https://inrix.com/blog/2020/06/covid19-us-traffic-volume-synopsis-15/ Circumstances continue to evolve and it is not clear that in all cases the return to normal will be exactly normal. For example, there could be plateaus along the way as the time between outbreak and vaccine continues. Some areas may see greater traffic levels and/or the impact of WFH could be significant enough to result in lower volumes. In the Seattle area, tracking of VMT through the pandemic has revealed a “July plateau” that may be emerging.

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Seattle Region Daily Change in VMT

http://tps.uwstarlab.org/ While the reopening of schools (and remaining open) is an obvious benchmark for “normal,” there are several other indicators that can be helpful in tracking the return to “normal.” A few such as commercial vehicle activity, trade, and fuel fill-ups are monitored continuously and provide a quick assessment of trends. These indicators also point to July 2020 as where regional trends approach normal for vehicle-related travel (assuming that a mandated return to “shelter in place” is not necessary in months to come). https://www.geotab.com/covid-19-recovery/

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Bicycle travel has also been affected by the pandemic. City of Phoenix data shows that weekday bicycle travel on most streets has stayed similar to trends from 2018 to 2019 to 2020, yet weekend bicycle travel in recreational areas (streets and trails) are up substantially for both weekday and weekend counts. This demonstrates the need to look at context carefully as some trends are substantially different with the pandemic. In this case, recreational trips compared to work type trips.

Transit and air travel were severely impacted by COVID and have been much slower to recover even as automobile travel has approached normal. USDOT Bureau of Transportation Statistics does weekly assessments of trips, rail, air, and transit travel. New York provides daily comparisons of transit ridership. Illinois also provided transit trends. These all show transit ridership is still off 80 percent from historic norms in July 2020 and air travel is down 75 percent. Short vehicle trips (1 mile) and long trips (over 25 miles) are near prior trends but common trips (1-25 miles, particularly common for urban areas) remain 10-15 percent below baseline nationally in the USA. https://new.mta.info/coronavirus/ridership https://www.bts.gov/newsroom/week-transportation https://www.cmap.illinois.gov/updates/all/-/asset_publisher/UIMfSLnFfMB6/content/covid-19-federal-legislation-analysis-and-transportation-system-impacts While there are lots of mobility trends available through big data sources (Apple’s Mobility Reports are an example), when assessing “normal,” analysts should be wary of pre-COVID being defined as February. Conditions in February for many land uses are some of the lowest

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months of the year for activity. Using a comparable pre-COVID month is advisable so that any seasonal trends can be captured.

https://www.fhwa.dot.gov/policyinformation/pubs/pl18027_traffic_data_pocket_guide.pdf The following sections provide an outline for considering “what is normal”. Traffic volumes are very fluid and dynamic, changing weekly. The long-term impacts of the COVID-19 pandemic will not be realized for a while, however, there continues to be a need to collect and analyze traffic data. Recognizing this need for data collection, it will be critically important to understand the context of the data that was collected, how the data will be used, what risks may be assumed by using the data, and to document and disclose the specific circumstances that may have influenced the traffic patterns at the time of data collection. Context of Data When an agency determines that traffic data collection is necessary, the context of the count will need to be clearly defined. It is recommended that the agency identify the type of data to be collected, the method of collection and the intended use of the data. As compared to pre-COVID data collection, detailed information should be collected, so as time passes and as the specific impacts of the pandemic on traffic patterns fade from memory, there are clear records indicating how the COVID-19 data may differ and potentially influence any traffic data analysis. At the time of data collection, there may be a strong desire to try to establish whether or not the current traffic patterns are establishing a “new normal.” This is a larger philosophical question that cannot be answered when tasked with an individual data collection need. The agency/firm must take all reasonable steps to determine if the data collection represents its need. ‘Reasonable steps’ is something that the agency/firm should determine from its internal work processes and business practices. Data collection needs to continue, so agencies should continue to collect data, document the context and circumstances of the data collection, and then use best practices established by the agency to determine how and when it is appropriate to use the data. Risks Associated with COVID-19 Data Once the context of the data is understood, an agency should then consider the risk associated with data collected during the COVID-19 pandemic. Agencies should ask if the data collection

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accurately portrays the need it is serving and how the pandemic may be impacting traffic and the resulting analysis. Because of the uncertainty surrounding post-pandemic traffic patterns, it will be critical that agencies disclose and document all aspects of the data collection so that those same risks are understood and evaluated should the COVID data be used in the future. Based on the context of the data collection, an agency or firm can develop a simple risk matrix, such as this example to determine if their data collection need falls in a low, medium or high impact area. This matrix should be user- defined since the levels of risk and impact are variable for each user. Once this matrix is developed, the agency can then determine if it is in their best interest to pursue the data collection. (https://www.researchgate.net/figure/Qualitative-Risk-Matrix-Probability-x-Impact_fig3_275155519) If the level of risk with using COVID data is too high, agencies can look to alternatives such as using comparable data from the same timeframe in a prior year to complete their analysis. Another alternative would be to develop ranges for data, and if no ranges are available to utilize a min/max scenario. Finally, rather than using COVID data in its raw form, use the data to run scenarios through a simulation program so that an agency can better understand how any variation in traffic patterns may impact the outcomes being derived from the traffic analysis. Alternatively, if the risk of using COVID data is too high and the degree of uncertainty with using historical data or ranges is not acceptable to an agency, there are other risk mitigation options that can be considered. For example, when the risk being considered is whether or not a roadway improvement is needed and who should bear those costs, alternative funding arrangements can help to mitigate the risk and protect the agency from paying a disproportionate share of the improvement costs or constructing improvements that may not needed based on actual traffic volumes. These options can include private agreements, fee in- lieu arrangements, traffic impact fees, and escrow payments, should future improvements be required. Considering new alternatives to the timing and funding of improvements to the transportation network will provide agencies with greater flexibility given the uncertainty regarding post-COVID traffic patterns. Documentation of Data When an agency decides to move forward with data collected during the COVID-19 pandemic, additional care needs to be given to documenting the details of the data. Data collected during

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the pandemic will need to be identified with specific details regarding the dates of the data collection, the sample of data collected (peak vs single or multi day collection), and the external factors such as stay-at-home orders, mode shift, and travel pattern changes that may impact traffic volumes and patterns. It will be important as time goes on that this data is not included in larger samplings of data without clearly indicating that the data may not represent pre- or post- pandemic traffic. Agencies should consider developing new data collection standards that will provide important context to the data such as the timeframe of data collection, the geographic scale of the collection, and other ancillary factors that may have influenced traffic patterns during the data collection period. Any time this data is utilized, this additional context should be disclosed and clearly documented. This documentation and disclosure should also be required of any external parties who may be using traffic data as part of their projects so that the agency can evaluate the quality and validity of the data and analysis. In pre-pandemic data collection, the documentation of traffic data often relied on a few key factors such as timeframe and location. Going forward, additional information and supporting detail should be documented in order to provide the greatest amount of context possible. Similar to baseball statistics from the steroid era, data collected during the COVID-19 pandemic should come with an asterisk and disclaimer that will cause any user to dig further into what that disclaimer may mean for their analysis. External resources should be utilized and documented so that policies such as stay-at-home orders, school closures, and reopening plan phasing can be referenced when the data is utilized. It is also not anticipated that external sources, especially electronic references, will be maintained in the long term. So rather than reference a state’s COVID-19 webpage, databases should be expanded so that detailed notes can be added that provide a greater understanding of traffic patterns at the time of data collection. Information regarding state executive orders, school closures, reopening phasing plans, transit ridership, and airport demand can all help to provide important context to data both now and in the future. Similarly, documenting conversations with visitor bureaus, transit agencies, major trip generators such as stadiums, etc. can help to quantify what may be impacting traffic volumes and patterns. It may also be necessary to document surrounding land uses since future users may not realize that the data collected was adjacent to a land use that may have experienced a significant change in traffic patterns, i.e., a hospital or stadium. A simple “windshield survey” of parking occupancy could be a quick tool to determine “normal” if facilities at typical levels. ITE Parking Generation Manual can be utilized as a basis for comparison to pre-pandemic parking demand. The COVID-19 pandemic also presents an opportunity to work with peer agencies who may have data or other information that can provide further context or serve as an alternative data source for consideration. Developing a peer network will not only provide assistance during the pandemic, but will also serve as a long-term resource. Finally, while pre-pandemic counts may have been used as the sole data point in decision making (i.e., traffic volumes over a certain threshold require a dedicated turn lane or warrant a traffic control signal), the uncertainty surrounding traffic patterns post-COVID will require that

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agencies use traffic data as one factor to be considered as part of any analysis and decision- making process. Focusing on the need for the data, the risk associated with using data collected during the pandemic, and the external factors that may be influencing traffic patterns, will be critical to allowing agencies to understand how they can mitigate the risks and potential impacts of relying solely on COVID-19 data. This is most critical for studies such as intersection control evaluations. Since the establishment of new trends can only be realized and understood in hindsight, detailed documentation will be valuable in determining what data may be considered part of stabilized, post-COVID norms. Data collection during COVID-19 continues to be important, however the ambiguity about what post-COVID traffic patterns will look like and when they will stabilize means that agencies will need to avoid waiting for a “new normal” and instead will need to shift their focus to documenting and disclosing the details surrounding their data collection.

FORECASTING The use of traffic counts/data in developing horizon year traffic volumes has become complex with the traffic pattern changes related to COVID19. Complexity arises from impacts of WFH, staggered work hours, transit demand changes (particularly rail transit), quarantine, closed businesses, and proximity to sensitive land uses/areas. Sensitive land uses/areas are ones that may be impacted more than others due to the threat/fear of risk of infection levels and changes in society based on social distancing. Some of the sensitive land uses/areas could include the following: Central Business Districts, schools, college towns, airports, hotels, convention centers, stadiums, arenas, sports venues, hospitals, doctor/dental offices and shopping malls.

Even in some of the sensitive land use areas, commuter traffic is the predominant factor influencing our system of peak hour analysis. Ultimately whether we forecast more or less traffic on our roads in the short and mid-term ranges depends on the balance between more commuters on the roads during peak hours due to mode shift away from transit and high-occupancy vehicles to single occupancy vehicles vs. fewer commuters on the road during peak hours because of WFH policies and shifted scheduling.

Recent Commuting Trends

In thinking about how these mode splits could shift, a review of the 2017 American Community Survey conducted by the University of Toronto School of Cities and covered in this January 2019 Bloomberg CityLab article reveals that only 5 percent of Americans commute via public transit, and only 9 percent commute in a carpool, while more than three-quarters (76.4 percent) drive to work alone.

So while we may expect a drop in the transit and carpool users, even a 50 percent reduction of those modes combined could be offset by less than a 10 percent reduction of single occupancy commuters caused by WFH in many areas. According to a Harris Poll published April 6, 2020, just over half (51 percent) of the 1,200 employed U.S. adults surveyed responded that they had

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shifted to working from home, and 65 percent feel that their productivity increased working from home.

Two other recent studies mentioned in this article estimate that nearly 40 percent of all jobs can be performed from home.

We expect that many of the commuters who are no longer willing to use transit or carpool will continue to work from home until those options return to viability. However, a recent Gallup poll indicated that nearly 60 percent of American workers who have been working from home desire to continue to do so as much as possible going forward. The ability of WFH to offset “rebounding” vehicle trips that migrate away from transit post-COVID will vary by community. In lower transit areas, the return of congestion may not be as significant or is lower in some corridors due to the WFH offset. An initial equilibrium will likely be established eventually. For metro areas with greater transit mode share (Table 1), it appears that WFH is offsetting temporary transit reductions. However, congestion on certain corridors could become worse until a vaccine is in place and transit levels can rebound. For these regions, greater WFH could be anticipated (or is needed) to offset increased congestion and slower travel times. Table 1 Top Transit Commute to Work Mode Choice in the USA

Region Share

New York City 57%

Washington DC 37%

Boston 34%

San Francisco 33%

Chicago 27%

Philadelphia 26%

Seattle 20%

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Source: 2015 American Community Survey (ACS) Table 2 shows a model for how an analyst might estimate possible changes to WFH mode share. The impacts are subtle to create a doubling of mode share. The COVID numbers reflect the results of a recent survey about the role people expect telecommuting to play in their own future WFH trips. The pre- and post- numbers are estimates. While these estimate percentages are hypothetical, they provide a tool for understanding and describing how the changes to travel may arise going forward. This also outlines the role that a significant shift to WFH plays in not only offsetting a decline in transit mode share (leading to reduced congestion during COVID), but WFH’s greater role in future commute mode choice. Table 2 Work From Home Mode Choice Estimating Tool

Shares of Work Force

Work Factor Pre-COVID* COVID** Post-COVID*

Do Not Work from Home: Never 0% 60% 14% 50%

Work from Home: Once a month 5% 20% 13% 18%

Every other week 10% 10% 13% 15%

Once a week 20% 7% 23% 10%

Twice a week 40% 2% 23% 2%

Daily 100% 1% 14% 5%

WFH Mode Share: 5% 30% 10%

* - Estimates of WFH profiles. Pre-COVID profile set to match ACS 5% findings and Post-COVID assuming if only conservative changes to WFH are made after a vaccine ** - Data from a Kittelson Associates stated preference survey of 1000+ USA workers, 2020.

The summary of this data appears to indicate that peak hour traffic volumes across the board may take even longer to return to prior established patterns than some of the sensitive land uses mentioned above.

Data Forecasting

When faced with the need to forecast traffic volumes, resources that should be consulted include the following:

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○ Historical count records from DOT/MPO/County/City ○ Prior land use approval records - TIAs ○ Transportation projects/corridor studies (EIS, EIR, .…) ○ Transportation plans (area wide, City, County, State)

Historical count data can potentially be used as the basis for traffic growth projections. Counts from 2018 and 2019 would commonly be considered acceptable replacements to current counts. Some agencies are expanding the time frame for the consideration of historical counts given the pandemic (some as far back as five or more years old). Analysts would need to consider factoring aged data based on historical growth rates (daily and/or turning movement counts), using permanent count stations or historic probe-based data sets. Other considerations should address impacts from pandemic-related outcomes such as WFH, potential staggered schedule travel patterns, transit/carpool activity changes, and potential influences from adjacent sensitive land uses.

Collection of current traffic volumes can be helpful to quantify the differences between historical volumes and 2020 data. Based on a review of adjacent land uses along with historic and current traffic volumes, the determination of horizon year forecast/volume factors can be based on the professional’s judgement as to the appropriate methodology for horizon year traffic volumes. The volume forecasting should take into consideration the context of the data use in decision making such as the following: land use review, mitigation, roadway project sizing, counting program, and HPMS data.

Traffic volumes collected after March 1, 2020, are considered “post quarantine.” It is recommended that post-quarantine data should be asterisked (*) and called out uniquely to the circumstances. After July, vehicle volumes may have returned to non-COVID-like conditions in many areas and routes, however this assessment is extremely region-specific. Special consideration should be made for these counts to determine their relative value using various resources such as regional continuous count stations, regional active traffic management system data sets, and probe-based data sets.

Where forecasts are necessary for horizon years beyond a few years, risk analysis should be undertaken to determine the basis of projections. This may include establishing ranges of likely scenarios and testing outcomes in a sensitivity analysis approach to see if findings change based upon these scenarios. There are risks to forecast using various approaches, highlighted below:

Factoring - While substantial data to establish trends is available from historic DOT (HPMS/count programs) and probe data, the trends have been disrupted and in some cases they may resume (rural, suburban) and others likely not (CBD). This approach requires investigation or many data systems.

“Pancaking” Trip Generation - Adding project and surrounding development on top of a “base” count using trip generation has two major issues. Obtaining the proper base count requires assessment and timing of performing new counts or adjusting older data in lieu of current counts. Second, trip generation rates are impacted (see section below) disproportionately during and following the pandemic affecting outcomes. Additionally, long-term consequences of trip generation (i.e., impacts of WFH) are yet to be researched.

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Travel Models - Every urban region has a travel demand forecast model that has been calibrated in pre-COVID conditions. The travel model allows the ability to test scenarios with different trip generation, mode split, and peaking factors. For major transportation project analysis, travel model test scenarios would likely be needed.

One closing note; the 2020 Census in the United States was conducted in April 2020. For future use in forecasting and projections, the travel demand data from this census will need to be considered with great care.

TRIP GENERATION Trip generation for some land use types has been impacted more substantially than others. For traffic counts and transportation studies, it will be important in the coming months of 2020 and 2021 to assess economic activity and impacts of social distancing on trip generation. One way to conduct quick assessments of context with transportation impact studies is to conduct brief “windshield surveys” of significant nearby land uses, using parking facilities as a casual indicator. Where parking occupancy is substantially below trends expressed in ITE’s Parking Generation Manual or known historic trends, care should be taken in accepting traffic counts as normal. With big data emerging in its application of probe data sets on a continuous and real-time basis, the pandemic has put on display the power of these data sets. There are many resources for analysts to consider in traffic counts and studies involving land uses. The following summary by land use (ITE Trip Generation Manual land use code) is provided to highlight a few of these data sets. Hopefully this allows analysts to consider these big data sources in applying judgement of travel patterns which may affect counts and studies for some time to come. Terminals (000)/Airports (021): The substantial reduction in air travel makes any counts and studies complex. Historic data will be important to access. Parking facilities will provide a quick visual assessment of when normal may be back; however, most airports have boarding data readily available to assess. Given the long recoveries after 9/11 and the Great Recession, analysts should assume this land use will also be slow to recover compared to other uses. Rail terminals are down significantly also. Transit ridership is also impacting park-and-ride facilities. https://www.bts.gov/newsroom/week-transportation Industrial (100): Staffing levels are behind historic levels and likely subject to economic, e-commerce and work from home issues. Within the industrial sector, warehousing has been at

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or above historic levels, depending upon the type of commerce they engage in (e-commerce is up). https://www2.staffingindustry.com/eng/Editorial/Industrial-Staffing-Report/June-18-2020/Industrial-staffing-the-most-impacted-segment https://www.moodysanalytics.com/-/media/whitepaper/2020/ma-reis_why_industrial_warehouse_is_likely_to_fare_better.pdf Residential (200): Trip levels are down due to work from home, recreation, and school schedule impacts. Peak periods are also impacted. The pre-vaccine travel demand is lower especially in the morning peaks (WFH, home delivery, and schools). The post-vaccine may also be likely disrupted, potentially lower. Apartment demand is projected to have reduced absorption as a result of economic consequences of the pandemic that could extend for a few years. Senior housing was expected to be on an upward trend for the decade, but pandemic- related visitation restrictions are reducing travel in the near term, pre-vaccine. https://www.us.jll.com/en/trends-and-insights/research/seniors-housing-and-care-investor-survey-and-trends-outlook-spring-2020 Lodging (300)/Hotels (310): With air travel and conferences substantially down, the hospitality industry is not anticipated to recover as quickly as other land uses. Some motels, suites, and suburban sites may be approaching normal in the summer of 2020 (particularly those outside of CBDs). However, hotels near CBDs and resorts that depend on long-distance travel are projected to have occupancies well below historic occupancy patterns (40 percent lower) and may stay there until the vaccine and better economic conditions emerge. Counts or studies near concentrations of these uses should assess occupancy. https://www.ahla.com/covid-19s-impact-hotel-industry

Recreational (400)/Movie Theaters (445), Sports Venues (462), Fitness Center (492): Professional athletics are not likely to resume “typical” operations until 2021 or 2022 at the earliest. Limitations on large gatherings will likely have effects on large venues until past the vaccine.

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Movie Theaters: Attendance at movie theaters is off dramatically from historic levels and will likely not recover until a vaccine is in place. Large gatherings are prohibited in many localities during the pandemic, resulting in 80 percent reductions to normal operation. https://www.the-numbers.com/market/ Fitness Centers: The pandemic is likely to have some long-lasting impacts on this industry that are unknown at this time. Mindsets toward fitness without going to the center and hybrid virtual models will likely emerge and smaller footprint businesses may change travel patterns. Institutional (500)/Schools: With massive closures and conversion to virtual, all schools— from K-12 to universities, public to private—will have substantially reduced travel until the vaccine emerges. This includes trip activity associated with school grounds used for recreational leagues and youth sports. Hybrid models will emerge in the 2020-2021 year, but a return to “normal” is likely within a few years (unlike long-standing changes for other uses). Look for pick-up, drop off, and school busing to be areas of change when normal does return to these uses for K-12. Universities may have longer-term consequences of virtual delivery of education which could affect campus, student housing, and sports venues that require monitoring for several years. Convention Center/Meetings (595): While limited data exists in the sector, conferences and large convention center gatherings have been prohibited by many states and localities. Until a vaccine is in place, these land uses will be highly-underutilized. This, along with other ancillary activities (hotels) and office travel changes are significantly impacting travel in CBDs. Medical (600): The immediate impact on travel to medical uses was a substantial reduction in activity as people avoided contact, eliminated appointments, and used tele-health. Doctor visit patterns have displayed a “Nike swoosh” pattern of recovery from March until July, now approaching pre-COVID visit patterns. The optimization of tele-health likely will have consequential impacts on medical offices and facilities (and their potential growth) just like the pandemic’s increased caseloads. Forecasts for medical office buildings show resumption of an upward trend line in activity after the pandemic. However, after the vaccine, the tele-health aspects will continue to play a role in trip generation. As with many uses, context is important as reduced trips to pediatricians, pulmonologists, several surgical specialties continue, while at the same time, trips have returned to pre-COVID levels for dermatology and rheumatology.

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https://www.commonwealthfund.org/publications/2020/jun/impact-covid-19-pandemic-outpatient-visits-practices-adapting-new-normal https://www.greenstreetadvisors.com/insights/blog/u-s-commercial-real-estate-cross-sector-overview-amid-covid-19 Office (700): Office trip generation is likely one of the biggest unknowns going forward. Shelter- in-place substantially reduced travel to/from these uses in the first half of 2020, and with the “awakening” of WFH and staggered work schedules (long-desired transportation demand management strategies) the long-term implications of travel are not clear but are likely to change significantly. CBD offices are impacted by changes in attitudes about transit, likely offset by WFH and staggered hours. AM and PM patterns have been disrupted. This is an area in the coming year where new trip generation data collection will become needed (both urban and suburban). For example, a transit mode share of 6 percent that drops to 1 percent may be offset by a WFH of 5 percent increasing to 10 percent. On the surface this may create a “normal” appearance but below the skin of the onion may rest a fully-changed travel pattern. Office uses will require close observation in any studies or counts. Retail (800) and Services (900): Shopping centers were struggling pre-COVID to match trip generation (economic activity) of the 1990s and 2000s due to e-commerce. COVID only accelerated those patterns. While several retail and service sectors never experienced significant trip generation changes or have even seen increases (big box, grocery store, home improvement stores), others such as restaurants were substantially impacted (anecdotally, were dining out dollars and trips traded for home improvement trips during the pandemic?). The data on foot traffic is updated daily and provides a tool to assess impacts on trip generation. https://www.safegraph.com/dashboard/covid19-commerce-patterns

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https://www.geotab.com/covid-19-recovery/

For sit-down restaurants, unless social distancing requirements are relaxed or restaurants can expand their service areas (e.g., patio, sidewalk, or closed street seating areas), customer trips to and from restaurants cannot physically reach pre-COVD numbers. Some types (fast food - 934) appear to be approaching that faster while others (bars, coffee shops - 936) appear to be lagging in the recovery. These patterns should be watched closely as they evolve. Again, as with many other uses, the types of uses that are in CBDs (sit down dining - 930/931) are behind other uses found in non-CBD settings. Some uses experienced an impact initially during the pandemic and then reset to typical travel activity. Auto loans as a surrogate for activity as auto dealerships (840) indicate that trip generation at these uses may have stabilized. Auto service (943) was not as impacted.

Source: Federal Reserve https://www.spglobal.com/en/research-insights/articles/daily-update-july-2-2020

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Conclusions It is safe to assume that, for most land use types, trip generation rates during the pandemic are significantly different from the empirically-based trip generation rates currently contained in ITE’s Trip Generation Manual. By the summer of 2020, many land uses will be approaching pre-COVID activity levels. For those land uses that may incur a long-term impact to trip generation (e.g., office, residential) it could be many years before we have supporting empirical evidence. Data observations in the post-vaccine era (2021/2022) will be important for studies involving these land uses. Particularly, observations of travel patterns will be needed for both rate and timing of peak periods (daily trip generation rates, weekday, and weekend trip generation rates, AM and PM peak hour trip generation rates, and “peak hour of the generator” trip generation rates). These changes will be the result of several contributing factors, including changes in trip-making propensity, average vehicle occupancy (for example, less carpooling), mode split (for example, less transit), and trip-making behaviors (for example, impacts on trip chaining). Unfortunately, using empirical data is a slow process and patterns can change rapidly, before research is shared. Using historic trip generation data has the potential for overestimating the trip-making potential of some land use types, including office, residential, and institutional, in particular. While using data different than ITE Trip Generation may be warranted, this should be done with supporting analysis. A stated preference survey process to adjust trip generation using currently-available predictive tools for estimating updated trip generation rates is possible.

● Stated preference surveys can give professionals a “look ahead” capability so they can anticipate how trip making behaviors will change before these changes actually take place.

● Such a survey would ideally be administered to a representative cross-section of the population within a given city, region, or state.

● The stated preference survey would elicit before-and-after responses to questions about travel mode, time, and frequency associated with home-based work trips, home-based other trips, and non-home-based trips, in addition to basic information about the respondent (e.g., zip code location, type of industry, and part-time/full-time/retired work status).

● A scenario planning approach could be applied in conjunction with the analysis of the stated preference survey results to determine worst case, likely, and best case trip generation rate scenarios, upon which guiding agency policies and procedures could rely.

● The scenarios can pair actions that could sustain higher WFH levels (communication, networks, technology, expanded use, functionality and application of video tools (Zoom, Meet, GoToMeeting, Teams, WebEx)) rather than traditional mitigation measures.

Analysts will carry the burden of documenting analysis assumption changes in a transparent way that highlight differences in trip generation/travel patterns and what sustainable actions align with those analysis assumptions. Using profiles of WFH, transit use, and carpool as the most likely impacted modes. This will require greater than “normal” levels of collaboration.