Article

More Online Shopping Means More Delivery Trucks. Are Cities Ready?

URL: https://theconversation.com/more-online-shopping-means-more-delivery-trucks-are-cities-ready-67686

Publication: The Conversation

Publication Date: 2016

Summary:

Two converging trends — the rise of e-commerce and urban population growth — are creating big challenges for cities. Online shoppers are learning to expect the urban freight delivery system to bring them whatever they want, wherever they want it, within one to two hours. That’s especially true during the holidays, as shipping companies hustle to deliver gift orders on time.

City managers and policymakers were already grappling with high demand and competing uses for scarce road, curb, and sidewalk space. If cities do not act quickly to revamp the way they manage increasing numbers of commercial vehicles unloading goods in streets and alleys and into buildings, they will drown in a sea of double-parked trucks.

The University of Washington has formed a new Urban Freight Lab to solve delivery system problems that cities and the business sector cannot handle on their own. Funders of this long-term strategic research partnership include the City of Seattle Department of Transportation (SDOT) and five founding corporate members: Costco, FedEx, Nordstrom, UPS, and the U.S. Postal Service.

The core problem facing cities is that they are trying to manage their part of a sophisticated data-powered 21st-century delivery system with tools designed for the 1800s — and they are often trying to do it alone. Consumers can order groceries, clothes, and electronics with a click, but most cities only have a stripe of colored paint to manage truck parking at the curb. The Urban Freight Lab brings building managers, retailers, logistics and tech firms, and city government together to do applied research and develop advanced solutions.

Moving more goods, more quickly

We have reached the point where millions of people who live and work in cities purchase more than half of their goods online. This trend is putting tremendous pressure on local governments to rethink how they manage street curb parking and alley operations for trucks and other delivery vehicles. It also forces building operators to plan for the influx of online goods. A few years ago, building concierges may have received a few flower bouquets. Now many are sorting and storing groceries and other goods for hundreds of residents every week.

In the first quarter of 2016, almost 8 percent of total U.S. retail sales took place online. Surging growth in U.S. online sales has averaged more than 15 percent year-over-year since 2010. Black Friday web sales soared by 22 percent from 2015 to 2016.

Online shoppers’ expectations for service are also rising. Two out of three shoppers expect to be able to place an order as late as 5:00 p.m. for next-day delivery. Three out of five believe orders placed by noon should be delivered the same day, and one out of four believe orders placed by 4:00 p.m. or later should still be delivered on the same day.

City living and shopping is still all about location, location, location. People are attracted to urban neighborhoods because they prefer to walk more and drive less. Respondents in the 2015 National Multifamily Housing Council-Kingsley Apartment Resident Preferences Survey preferred walking to grocery stores and restaurants rather than driving by seven points. But this lifestyle requires merchants to deliver goods to customers’ homes, office buildings or stores close to where they live.

Smarter delivery systems

SDOT recently published Seattle’s first draft Freight Master Plan, which includes high-level strategies to improve the urban goods delivery system. But before city managers act, they need evidence to prove which concepts will deliver results.

To lay the groundwork for our research, an SCTL team led by Dr. Ed McCormack and graduate students Jose Machado Leon and Gabriela Giron surveyed 523 blocks of Seattle’s downtown (including Belltown, the commercial core, Pioneer Square and International District), South Lake Union and Uptown urban centers in the fall of 2016. They compiled GIS coordinates and infrastructure characteristics for all observable freight loading bays within buildings. Our next step is to combine this information with existing GIS layers of the city’s curbside commercial vehicle load zones and alleys to produce a complete map of Seattle’s urban delivery infrastructure.

In our first research project, the Urban Freight Lab is using data-based process improvement tools to purposefully manage both public and private operations of the Final-50-Feet space. The final 50 feet of the urban delivery system begins when a truck stops at a city-owned curb, commercial vehicle load zone or alley. It extends along sidewalks and through privately owned building freight bays, and may end in common areas within a building, such as the lobby.

One key issue is failed deliveries: Some city residents don’t receive their parcels due to theft or because they weren’t home to accept them. Could there be secure, common drop-off points for multiple carriers to use, attached to bus stops or on the sidewalk?

The most pressing issue is the lack of space for trucks to park and deliver goods downtown. It may be possible to use technology to get more use out of existing commercial vehicle load zones. For example, trucks might be able to use spaces now reserved exclusively for other uses during off-peak hours or seasons.

To analyze the fundamental problems in the urban logistics system, our research team will create process flow maps of each step in the goods delivery process for five buildings in Seattle. We will collect data and build a model to analyze “what if” scenarios for one location. Then we will pilot test several promising low-cost, high-value actions on Seattle streets in the fall of 2017. The pilots may involve actively managing city load zones and alleys to maximize truck use, or changing the way people use freight elevators.

By using information technologies and creative planning, we can make receiving online goods as efficient as ordering them — without clogging our streets or losing our packages.

Authors: Dr. Anne GoodchildBarbara Ivanov

Recommended Citation:
Goodchild, A., & Ivanov, B. (2016, December 20). More online shopping means more delivery trucks. Are cities ready? The Conversation. https://theconversation.com/more-online-shopping-means-more-delivery-trucks-are-cities-ready-67686.

Report

The Final 50 Feet of the Urban Goods Delivery System: Completing Seattle’s Greater Downtown Inventory of Private Loading & Unloading Infrastructure (Phase 2)

Download PDF (2.35 MB)

Publication Date: 2020

Summary:

This report describes the Urban Freight Lab (UFL) work to map the locations of all private loading docks, loading bays, and loading areas for commercial vehicles in Seattle’s First Hill and Capitol Hill neighborhoods and document their key design and capacity features, as part of our Final 50 Feet Research Program.

Taken together with the UFL’s earlier private freight infrastructure inventory in Downtown Seattle, Uptown, and South Lake Union, this report finalizes the creation of a comprehensive Greater Downtown inventory of private loading/unloading infrastructure. The Seattle Department of Transportation (SDOT) commissioned this work as part of its broader effort with UFL to GIS map the entire Greater Downtown commercial load/unload network, which includes alleys, curbs and private infrastructure.

The research team could find no published information on any major U.S. or European city that maintains a database with the location and features of private loading/unloading infrastructure (meaning, out of the public right of way): Seattle is the first city to do so.

By supporting and investing in this work, SDOT demonstrates that it is taking a high-level conceptual view of the entire load/unload network. The city will now have a solid baseline of information to move forward on myriad policy decisions. This commitment to creating a private load/unload infrastructure inventory is significant because infrastructure is often identified as an essential element in making urban freight delivery more efficient. But because these facilities are privately owned and managed, policymakers and stakeholders lack information about them—information critical to urban planning. By and large, this private infrastructure has been a missing piece of the urban freight management puzzle. The work represented in this section fills a critical knowledge gap that can help advance efforts to make urban freight delivery more efficient in increasingly dense, constrained cities, like Seattle.

Without having accurate, up-to-date information on the full load/unload network infrastructure—including the private infrastructure addressed here—cities face challenges in devising effective strategies to minimize issues that hamper urban freight delivery efficiency, such as illegal parking and congestion. Research has shown that these issues are directly related to infrastructure (specifically, a lack thereof). (4) A consultant report for the New York Department of Transportation found that the limited data on private parking facilities for freight precluded development of solutions that reduce double parking, congestion and other pertinent last-mile freight challenges. (5) The report also found that the city’s off-street loading zone policy remained virtually unchanged for 65 years (despite major changes like the advent and boom of e-commerce.)

Local authorities often rely heavily on outside consultants to address urban freight transport issues because these authorities generally lack in-house capacity on urban freight. (6) Cities can use the replicable data-collection method developed here to build (and maintain) their own database of private loading/unloading infrastructure, thereby bolstering their in-house knowledge and planning capacity. Appendix C includes a Step-by-Step Toolkit for a Private Load/Unload Space Inventory that cities, researchers, and other parties can freely use.

The method in that toolkit builds—and improves—on the prior data-collection method UFL used to inventory private infrastructure in the dense urban neighborhoods of Downtown Seattle, Uptown and South Lake Union in early 2017 (Phase 1). The innovative, low-cost method ensures standardized, ground-truthed, high-quality data and is practical to carry out as it does not require prior permission and lengthy approval times to complete.

This inventory report’s two key findings are:

Data collectors in this study identified, examined, and collected key data on 92 private loading docks, bays and areas across 421 city blocks in the neighborhoods of Capitol Hill, First Hill, and a small segment of the International District east of I-5. By contrast, the early 2017 inventory in Downtown Seattle, Uptown, and South Lake Union identified 246 private docks, bays and areas over 523 blocks—proportionally more than twice the density of private infrastructure of Capitol Hill and First Hill. This finding is not surprising. While all the inventoried neighborhoods are in the broad Greater Downtown, they are fundamentally different neighborhoods with different built environments, land use, and density. Variable demand for private infrastructure—and the resulting supply—stems from those differences.
A trust relationship with the private sector is essential to reduce uncertainty in this type of work. UFL members added immense value by ground-truthing this work and playing an active role in improving inventory results. When data collectors in the field found potential freight loading bays with closed doors (preventing them from assessing whether the locations were, in fact, used for freight deliveries), UPS had their local drivers review the closed-door locations as part of their work in the Urban Freight Lab. The UPS review allowed the researchers to rule out 186 of the closed-door locations across this and the earlier 2017 data collection, reducing uncertainty in the total inventory from 33% to less than 1%.

This report is part of a broader suite of UFL research to date that equips Seattle with an evidence-based foundation to actively and effectively manage Greater Downtown load/unload space as a coordinated network. The UFL has mapped the location and features of the legal landing spots for trucks across the Greater Downtown, enabling the city to model myriad urban freight scenarios on a block-by-block level. To the research team’s knowledge, no other city in the U.S. or the E.U. has this data trove. The findings in this report, together with all the UFL research conducted and GIS maps and databases produced to date, give Seattle a technical baseline to actively manage the Greater Downtown’s load/unload network to improve the goods delivery system and mitigate gridlock.

The project partners will integrate sensor technologies, develop data platforms to process large data streams, and publish a prototype app to let delivery firms know when a parking space is open – and when it’s predicted to be open so they can plan to arrive when another truck is leaving. This is the nation’s first systematic research pilot to test proof of concept of a functioning system that offers commercial vehicle drivers and dispatchers real-time occupancy data on load/unload spaces–and test what impact that data has on commercial driver behavior. This pilot can help inform other cities interested in taking steps to actively manage their load/unload network.

Actively managing the load/unload network is more imperative as the city grows denser, the e-commerce boom continues, and drivers of all vehicle types—freight, service, passenger, ride-sharing and taxis—jockey for finite (and increasingly valuable) load/unload space. Already, Seattle ranks as the sixth most-congested city in the country.

Authors: Urban Freight Lab

Recommended Citation:
Urban Freight Lab (2020). The Final 50 Feet of the Urban Goods Delivery System: Phase 2, Completing Seattle’s Greater Downtown Inventory of Private Loading/Unloading Infrastructure.

Report

The Final 50 Feet of the Urban Goods Delivery System: Tracking Curb Use in Seattle

Download PDF (4.54 MB)

Publication Date: 2019

Summary:

Vehicles of all kinds compete for parking space along the curb in Seattle’s Greater Downtown area. The Seattle Department of Transportation (SDOT) manages use of the curb through several types of curb designations that regulate who can park in a space and for how long. To gain an evidence-based understanding of the current use and operational capacity of the curb for commercial vehicles (CVs), SDOT commissioned the Urban Freight Lab (UFL) at the University of Washington Supply Chain Transportation & Logistics Center to study and document curb parking in five selected Greater Downtown areas.

This study documents vehicle parking behavior in a three-by-three city block grid around each of five prototype Greater Downtown buildings: a hotel, a high-rise office building, an historical building, a retail center, and a residential tower. These buildings were part of the UFL’s earlier SDOT-sponsored research tracking how goods move vertically within a building in the final 50 feet.

The areas around these five prototype buildings were intentionally chosen for this curb study to deepen the city’s understanding of the Greater Downtown area.

Significantly, this study captures the parking behavior of commercial vehicles everywhere along the curb as well as the parking activities of all vehicles (including passenger vehicles) in commercial vehicle loading zones (CVLZs). The research team documented: (1) which types of vehicles parked in CVLZs and for how long, and; (2) how long commercial vehicles (CVs) parked in CVLZs, in metered parking, and in passenger load zones (PLZ) and other unauthorized spaces.

Four key findings, shown below, emerged from the research team’s work:

Commercial and passenger vehicle drivers use CVLZs and PLZs fluidly: commercial vehicles are parking in PLZs, and passenger vehicles are parking in CVLZs. Passenger vehicles made up more than half of all vehicles observed parking in CVLZs (52%). More than one-quarter of commercial vehicle drivers parked in PLZs (26 %.) This fact supports more integrated planning for all curb space, versus developing standalone strategies for passenger vehicle and for commercial vehicle parking.
Most commercial vehicle (CV) demand is for short-term parking: 15 or 30 minutes. Across the five locations, more than half (54%) of all CVs parked for 15 minutes or less in all types of curb spaces. Nearly three-quarters of all CVs (72%) parked for 30 minutes or less. When considering just the delivery CVs, an even higher percentage, 60%, parked for 15 minutes or less. Eighty-one percent of the delivery CVs parked for 30 minutes or less.
Thirty-six percent of the total CVs parked along the curb were service CVs, showing the importance of factoring their behavior and future demand into urban parking schemes. In contrast to delivery CVs that predominately parked for 30 minutes or less, service CVs’ parking behavior was bifurcated. While 56% of them parked for 30 minutes or less, 44% parked for more than 30 minutes. And more than one quarter (27%) of the service CVs parked for an hour or more. Because service vehicles make up such a big share of total CVs at the curb, this may have an outsize impact on parking space turn rates at the curb.
Forty-one percent of commercial vehicles parked in unauthorized locations. But a much higher percentage parked in unauthorized areas near the two retail centers (55% – 65%) when compared to the predominately office and residential areas (27% – 30%). The research team found that curb parking behavior is associated with granular, building-level urban land use. This occurred even as other factors such as the total number, length and ratio of CVLZs versus PLZs varied widely across the five study areas.

The occupancy study documents that each building and the built environment surrounding it has unique features that impact parking operations. As cities seek to more actively manage curb space, the study’s findings illuminate the need to plan a flexible network with capacity for distinct types (time and space requirements) of CV parking demand.

This study also drives home that the curb does not function in isolation, but instead forms one element of the Greater Downtown’s broader, interconnected load/unload network, which includes alleys, the curb, and private loading bays and docks. (1,2,3) SDOT commissioned this work as part of its broader effort with the UFL to map—and better understand—the entire Greater Downtown area’s commercial vehicle load/unload space network. Cities and other parties interested in the details of how to conduct a commercial vehicle occupancy study can see a step-by-step guide in Appendix C.

In this study, researchers deployed six data collectors to observe each curb study area for three days over roughly six weeks in October and December 2017. To make the data produced in this project as useful as possible, the research team designed a detailed vehicle typology to track specific vehicle categories consistently and accurately. The typology covers 10 separate vehicle categories, from various types of trucks and vans to passenger vehicles to cargo bikes. Passenger vehicles in this study were not treated as commercial vehicles, due to challenges in systematically identifying whether passenger vehicles were making deliveries or otherwise carrying a commercial permit.

The five prototype Seattle buildings studied are Seattle Municipal Tower (also the site of a common carrier parcel locker pilot), Dexter Horton, Westlake Center, and Insignia Towers. (4) The study shows how different building and land uses interact with the broader load/unload network. By collecting curb occupancy data in the same locations as their earlier work, the research team added a new layer of information to help the city evaluate—and manage—the Greater Downtown area load/unload network more comprehensively.

This report is part of a broader suite of UFL research to date that equips Seattle with an evidence-based foundation to actively and effectively manage Greater Downtown load/unload space as a coordinated network. The UFL has mapped the location and features of the legal landing spots for trucks across the Greater Downtown, enabling the city to model myriad urban freight scenarios on a block-by-block level. To the research team’s knowledge, no other city in the U.S. or the E.U. has this data trove. The findings in this report, together with all the UFL research conducted and GIS maps and databases produced to date, give Seattle a technical baseline to actively manage the Greater Downtown’s load/unload spaces as a coordinated network to improve the goods delivery system and mitigate gridlock.

The UFL will pilot such active management on select Greater Downtown streets in Seattle and Bellevue, Washington, to help goods delivery drivers find a place to park without circling the block in crowded cities for hours, wasting time and fuel and adding to congestion. The U.S. Department of Energy’s Office of Energy Efficiency and Renewable Energy under the Vehicles Technologies Office is funding the project. (5) The project partners will integrate sensor technologies, develop data platforms to process large data streams, and publish a prototype app to let delivery firms know when a parking space is open – and when it’s predicted to be open so they can plan to arrive when another truck is leaving. This is the nation’s first systematic research pilot to test proof of concept of a functioning system that offers commercial vehicle drivers and dispatchers real-time occupancy data on load/unload spaces–and test what impact that data has on commercial driver behavior. This pilot can help inform other cities interested in taking steps to actively manage their load/unload network.

The UFL is a living laboratory made up of retailers, truck freight carriers and parcel companies, technology companies supporting transportation and logistics, multifamily residential and retail/commercial building developers and operators, and SDOT. Current members are Boeing HorizonX, Building Owners and Managers Association (BOMA) – Seattle King County, curbFlow, Expeditors International of Washington, Ford Motor Company, General Motors, Kroger, Michelin, Nordstrom, PepsiCo, Terreno, USPack, UPS, and the United States Postal Service (USPS).

Authors: Urban Freight Lab

Recommended Citation:
Urban Freight Lab (2019). The Final 50 Feet of the Urban Goods Delivery System: Tracking Curb Use in Seattle.

Technical Report

Development and Analysis of a GIS-Based Statewide Freight Data Flow Network

Download PDF (4.92 MB)

URL: https://rosap.ntl.bts.gov/view/dot/39538

Publication: Washington State Department of Transportation

Publication Date: 2009

Summary:

In the face of many risks of disruptions to our transportation system, this research improves WSDOT’s ability to manage the freight transportation system so that it minimizes the economic consequences of transportation disruptions.

Faced with a high probability that major disruptions to the transportation system will
harm the state’s economy, the Washington State Department of Transportation
(WSDOT), in partnership with Transportation Northwest (TransNow) commissioned
researchers at the University of Washington and Washington State University to
undertake freight resiliency research to:

Understand how disruptions of the state’s freight corridors change the way
trucking companies and various freight-dependent industries route goods,
Plan to protect freight-dependent sectors that are at high risk from these disruptive
events, and
Prioritize future transportation investments based on the risk of economic loss to
the state

To accurately predict how companies will route shipments during a disruption,
this research developed the first statewide multimodal freight model for Washington
State. The model is a GIS-based portrayal of the state’s freight highway, arterial, rail,
waterway and intermodal network and can help the state prioritize strategies that protect industries most vulnerable to disruptions.

The report features two case studies showing the model’s capabilities: the potato growing and processing industry was chosen as a representative agricultural sector, and diesel fuel distribution for its importance to all industry sectors. The case studies are found in sections 5.2 and 5.3 in the report and show how the statewide freight model can:

Predict how shipments will be re-routed during disruptions, and
Analyze the level of resiliency in various industry sectors in Washington State

The two case studies document the fragility of the state’s potato growing and processing
sectors and its dependence on the I-90 corridor, while showing how the state’s diesel
delivery system is highly resilient and isn’t linked to I-90.

As origin-destination data for other freight-dependent sectors is added to the model,
WSDOT will be able to evaluate the impact of freight system disruptions on each of
them. This will improve WSDOT’s ability to develop optimal strategies for highway
closures, and prioritize improvements to the system based on the relative impact of the
disruption.

This research addressed several technical areas that would need to be resolved by any
organization building a state freight model. First, the researchers had to decide on the
level of spatial and temporal detail to include in the statewide GIS freight model. This
decision has significant consequences for data resolution requirements and results.
Including every road in Washington would have created a cumbersome model with a
large number of links that weren’t used. However, in order to analyze routing during a
disruption all possible connections must exist between origin and destination points in the model. While the team initially included only the core freight network in the model,
ultimately all road links were added to create complete network connectivity.

Second, as state- and corridor-level commodity flow data is practically non-existent, data
collection for the two case studies was resource intensive. Supply chain data is held by
various stakeholders and typically not listed on public websites, and it isn’t organized by
those stakeholders for use in a freight model. In most cases it’s difficult to assure data
quality. The team learned that the most difficult data to obtain is data on spatially or
temporally variable attributes, such as truck location and volume. So they developed a
method to estimate the importance of transportation links without commodity flow data.

Third, the freight model identified the shortest route, based on travel time, between any
origin and destination (O/D) pair in the state, and the shortest travel-time re-route for
each O/D pair after a disruption. The routing logic in the model is based on accepted
algorithms used by Google Maps and MapQuest. Phase III of the state’s freight
resiliency research was funded by WSDOT and will result in improved truck freight
routing logic for the model in 2011.

The two case studies showed how the state’s supply chains use infrastructure differently,
and that some supply chains have built flexibility into their operations and are resilient
while others are not, which leads to very different economic consequences. The results
of these case studies significantly contributed to WSDOT’s understanding of goods
movement and vulnerability to disruptions.

In the future, Washington State will need corridor-level commodity flow data to
implement the research findings and complete the state freight model. In 2009, the
National Cooperative Freight Research Program (NCFRP) funded development of new
methodology to collect and analyze sub-national commodity flow information. This
NCFRP project, funded at $500,000, will be completed in 2010 and provide a mechanism for states to accurately account for corridor-level commodity flows. If funds are available to implement the new methodology in Washington State, the state’s freight
model will use the information to map these existing origin destination commodity flows
onto the freight network, evaluate the number of re-routed commercial vehicles, and their increased reroute distance from any disruption. This will allow WSDOT to develop
prioritized plans for supply chain disruptions, and recommend improvements to the
system based on the economic impact of the disruption.

This report summarizes 1) the results from a thorough review of resilience literature and resilience practices within enterprises and organizations, 2) the development of a GIS-based statewide freight transportation network model, 3) the collection of detailed data regarding two important industries in Washington state, the distribution of potatoes and diesel fuel, and 4) analysis of the response of these industries to specific disruptions to the state transportation network.

The report also includes recommendations for improvements and additions to the GIS model that will further the state’s goals of understanding the relationship between infrastructure availability and economic activity, as well as recommendations for improvements to the statewide freight transportation model so that it can capture additional system complexity.

Authors: Dr. Anne GoodchildDr. Ed McCormack, Eric Jessup, Derik Andreoli, Kelly Pitera, Sunny Rose, Chilan Ta

Recommended Citation:
Goodchild, Anne V., Eric L. Jessup, Edward D. McCormack, Derik Andreoli, S Rose, Chilan Ta and Kelly Pitera. “Development and Analysis of a GIS-Based Statewide Freight Data Flow Network.” (2009).

Report

Seattle Center City: Alley Infrastructure Inventory and Occupancy Study

Download PDF (2.84 MB)

Publication Date: 2018

Summary:

The Supply Chain and Transportation Logistics (SCTL) Center conducted an alley inventory and truck load/unload occupancy study for the City of Seattle. Researchers collected data identifying the locations and infrastructure characteristics of alleys within Seattle’s One Center City planning area, which includes the downtown, uptown, South Lake Union, Capitol Hill, and First Hill urban centers. The resulting alley database includes GIS coordinates for both ends of each alley, geometric and traffic attributes, and photos. Researchers also observed all truck load/unload activity in selected alleys to determine minutes vacant and minutes occupied by trucks, vans, passenger vehicles, and cargo bikes. The researchers then developed alley management recommendations to promote safe, sustainable, and efficient goods delivery and pick-up.

Key Findings:

The first key finding of this study is that more than 90% of Center City alleys are only one lane wide. This surprising fact creates an upper limit on alley parking capacity, as each alley can functionally hold only one or two vehicles at a time. Because there is no room to pass by, when a truck, van, or car parks it blocks all other vehicles from using the alley. When commercial vehicle drivers see that an alley is blocked they will not enter it, as their only way out would be to back up into street traffic. Seattle Municipal Code prohibits this, as well as backing up into an alley, for safety reasons.

When informed by the second key finding—68% of vehicles in the alley occupancy study parked there for 15 minutes or less—it is clear that moving vehicles through alleys in short time increments is the only reasonable path to increase productivity. As one parked vehicle operationally blocks the entire alley, the goal of new alley policies and strategies should be to reduce the amount of time alleys are blocked to additional users.

The study surfaces four additional key findings:

87% of all vehicles in the 7 alleys studied parked for 30 minutes or less. Given the imperative to move alley traffic quickly, vehicles that need more parking time must be moved out of the alleys and onto the curb where they don’t block others.
15% of alleys’ pavement condition is so poor that delivery workers can’t pass through with loaded hand carts. Although trucks can drive over fairly uneven pavement without difficulty, it is not the case for delivery people walking with fully loaded handcarts. The alley pavement rating was done with a qualitative visual inspection to identify obvious problems; more detailed measurements would be needed to fully assess conditions.
73% of Center City area alleys contain entrances to passenger parking facilities. Placing garage entrances in alleys has been a city policy goal for years. But it increases the frequency of cars in alleys and adds demands on alley use. Understanding why cars are queuing for passenger garages located off alleys, and providing incentives and disincentives to reduce that, would help make alleys more productive.
Alleys are vacant about half of the time during the business day. While at first blush this suggests ample capacity, the fact that an alley can only hold one-to-two parked trucks at a time means alleys are limited operationally and therefore are not a viable alternative to replace the use of curb CVLZs on city streets.

These findings indicate that, due to the fixed alley width constraint, load/unload space inside Seattle’s existing Center City area alleys is insufficient to meet additional future demand.

Authors: Urban Freight Lab

Recommended Citation:
Urban Freight Lab (2018). Seattle Center City: Alley Infrastructure Inventory and Occupancy Study.

Biking the Goods: How North American Cities Can Prepare for and Promote Large-Scale Adoption

With the rise in demand for home deliveries and the boom of the e-bike market in the U.S., cargo cycles are becoming the alternative mode of transporting goods in urban areas. However, many U.S. cities are struggling to decide how to safely integrate this new mode of transportation into the pre-existing urban environment.

In response, the Urban Freight Lab is developing a white paper on how cities can prepare for and promote large-scale adoption of cargo cycle transportation. Sponsors include freight logistics providers, bicycle industry leaders, and agencies Bosch eBike Systems, Fleet Cycles, Gazelle USA, Michelin North America, Inc., Net Zero Logistics, the Seattle Department of Transportation, and Urban Arrow.

The Urban Freight Lab is internationally recognized as a leader in urban freight research, housing a unique and innovative workgroup of private and public stakeholders and academic researchers working together to study and solve urban freight challenges. The Urban Freight Lab has previously worked on evaluating, studying, and deploying cargo cycles in Asia and the U.S, and is recognized as an expert leader in North America on cargo cycle research.

Objectives
The objectives of the white paper are the following:

Define and understand what types of cargo bikes exist in North America, their main features, how they are operated, and the infrastructure they need.
Identify opportunities for and challenges to large-scale adoption of cargo cycles in North American cities.
Learn from case studies of U.S. cities’ approaches to regulating and promoting cargo cycles.
Provide recommendations for how cities can safely recognize, enable and encourage large-scale adoption of cargo bikes, including infrastructure, policy, and regulatory approaches.

West Seattle Bridge Case Study (Phase II)

This project is a continuation of the West Seattle Bridge Case Study Phase I.

Background:
West Seattle (WS) is an area of the city of Seattle, Washington, located on a peninsula west of the Duwamish waterway and east of the Puget Sound. In March 2020, the West Seattle High Bridge (WSHB), the main bridge connecting WS to the rest of the city, was closed to traffic due to its increasing rate of structural deterioration.

The Seattle Department of Transportation (SDOT) has engaged the Supply Chain Transportation and Logistics Center (SCTL) at the University of Washington, to conduct research to understand current freight movements and freight demands in WS and identify challenges related to the bridge closure to inform data-driven mitigation strategies.

In project Phase 1 the research team performed a freight trip generation (FTG) estimation and conducted interviews with local business establishments, carriers, and the Port of Seattle. As a result of the FTG modeling, the research team estimated that 94 percent of the freight trips generated by WS are destined to residential buildings. Moreover, the interviews identified disruptions in the supply chains of small and medium-size local businesses as well as carriers facing longer travel times to access the peninsula.

Research Objectives:
In Phase 2 of the project, the research team will shift the focus from business establishments to consumers. In particular, we will explore consumer behavior, defined as how people choose to buy goods and services and where they buy them, to better understand residential demand and accessibility of goods for WS residents.

This study will make use of a consumer survey for Seattle residents to:

Describe consumer behavior and buying habits for Seattle residents, in particular, we will address how (online vs. in-person and with which travel mode), where (locally or not-locally), and how often people shop.
Better understand what drives consumer behavior, in particular how consumer behavior is impacted by urban form (transport infrastructure available, land uses, urban density, etc.), access to transportation, local access to stores, and socioeconomic characteristics.

Tasks:

Gather public datasets and review previous consumer surveys: The research team will review and summarize publicly available datasets that contain information on consumer behaviors and urban form for Seattle residents, for instance, the Puget Sound Regional Council (PSRC) data, the National Household Travel Survey (NHTS), the Freight Trip Generation (FTG) estimates from Phase 1, the Google Maps APIs and the publicly available Seattle Department of Transportation (SDOT) GIS layers. The research team will also scan the scientific literature and reports to inform the design of the survey on consumer behavior.
Survey Design: The research team will design a consumer survey and a method of survey distribution. The survey will include socioeconomic data (e.g. age, gender, income, education, household composition, car ownership), geographical location (where the interviewee lives), consumer behavior (e.g. types of goods purchased, the amount spent, where goods are purchased, mode of travel, whether goods were purchased online or in-person, how often the purchases take place). SDOT will be provided the opportunity to review and give comments on the draft survey before the survey roll-out.
Survey roll-out: The approved survey will be distributed to residents of the agreed study area. The survey will be drafted as an online survey. SDOT will reserve the option to further expand the survey reach, for instance by creating and distributing a paper version of the survey, translating the survey to other languages, use SDOT channels to distribute the survey.
Analysis of survey data: Data from the survey will be analyzed. A descriptive statistical analysis will be performed, addressing questions such as how people consume, how far people travel to purchase goods, what is the preferred mode of transportation for shopping trips, and how frequently people purchase things online vs. in person. A second part of the analysis will focus on understanding the relationship between socioeconomic variables and urban form variables with consumer behavior variables.
Reporting: A final report will be drafted reporting on the survey design and method, a data description, and data analysis addressing the project goals. SDOT will review and confirm the final report before publication on the SCTL website.

Deliverables: Final project report and executive summary

Budget: $60,000
Timeline: January to December 2022

West Seattle Bridge Case Study (Phase I)

Background
West Seattle is an area of the city of Seattle located on a peninsula west of the Duwamish waterway and east of the Puget Sound. In March 2020, the West Seattle High Bridge (WSHB), the main bridge connecting West Seattle to the rest of the city, was closed indefinitely to traffic due to its increasing rate of structural deterioration. Moreover, access to the Spokane Street Lower Bridge, a smaller bridge connecting West Seattle with Harbor Island and the rest of the city, was also restricted; prioritizing heavy freight, public transit, and emergency vehicles. After the bridge closure and restrictions, the total number of vehicle travel lanes crossing the Duwamish River was reduced from 21 to 12.

The unexpected closure of WSHB disrupted passenger and freight mobility to and from West Seattle, increasing travel times and generating bottlenecks on the remaining bridges, which can potentially negatively impact the livability of the peninsula as well as its economy and the environment. The situation might further deteriorate as traffic demand to and from West Seattle increases during recovery from the COVID-19 pandemic.

The Seattle Department of Transportation (SDOT) is taking actions to monitor changes in travel behavior to/from West Seattle and identify and implement strategies that could mitigate the negative impacts caused by the WSHB closure.

Goals
SDOT has engaged the Urban Freight Lab to conduct research to explore strategies to alleviate congestion impacts and minimize the disruption of goods and service delivery to West Seattle.

The purpose of this study is to support SDOT to:

understand current freight movements and freight demand in West Seattle;
identify a data-driven mitigation strategy for freight and service flow to and from West Seattle;
assess ex-ante the effectiveness of an implemented strategy.

The freight operations considered and analyzed within the scope of the project are consumer goods and services destined for West Seattle residents and businesses. Intermediate goods and raw materials destined for construction of production and other goods transiting through West Seattle but not destined for local residents or businesses will not be studied.

Continuation
This project continues with the West Seattle Bridge Case Study Phase II.

Report

Analysis of Online Shopping and Shopping Travel Behaviors in West Seattle

Download PDF (1.27 MB)

Publication Date: 2023

Summary:

The purpose of this research is to explore consumers’ online shopping and in-person shopping travel behaviors and the factors affecting these behaviors within the geographical context of the study area of West Seattle.

West Seattle is a peninsula located southwest of downtown Seattle, Washington State. In March 2020, the West Seattle High Bridge, the main bridge connecting the peninsula to the rest of the city, was closed to traffic due to its increased rate of structural deterioration. The closure resulted in most of the traffic being re-distributed across other bridges, forcing many travelers to re-route their trips in and out of the peninsula. At about the same time, the COVID-19 pandemic caused business-shuttering lockdowns. Both events fundamentally changed the nature of shopping and the urban logistics system of the study area.

The Seattle Department of Transportation (SDOT) engaged the Urban Freight Lab (UFL) at the University of Washington to conduct research to understand current freight movements and goods demands in West Seattle and identify challenges related to the bridge closure to inform data-driven mitigation strategies. The study took place in two phases: the first phase documented the challenges experienced by local businesses and carriers through a series of interviews and quantified the freight trip generated by land use in the case study area1 ; the second phase, described in the current report, performed an online survey to understand online shopping and in-person shopping travel behaviors for West Seattle residents.

The main objectives of the current study are twofold:

Describe online shopping and shopping travel consumer behaviors for West Seattle residents.
Understand what factors influence consumer shopping behaviors, from accessibility to local stores, to the characteristics of goods purchased, to socio-economic factors.

Methods

To address these objectives, the research team designed an online questionnaire that was advertised through a West Seattle Bridge Closure-related SDOT newsletter and other local online media outlets during the spring and summer of 2022. The questionnaire asked respondents about their socioeconomic conditions (age, income, education, etc.), where they live and their access to transportation (vehicle ownership and types of vehicles), their online shopping behavior, the impact of the West Seattle High Bridge closure on their shopping habits, and about their most recent purchase for a given category of goods among clothing items, groceries, restaurant food, and household supplies. The questionnaire was collected anonymously, and no personally identifiable information was collected. A total of 1,262 responses were collected, and after data processing, the final sample data consisted of 919 responses, corresponding approximately to 1 percent of the study area population.

Comparing the socioeconomic characteristics of the sample with those of the West Seattle study population it should be noted that individuals identifying themselves as white and female and of older age were oversampled, while individuals with lower than a college degree and with annual income less than $50,000 were under-sampled. Therefore, the sample in general is more representative of a more affluent, older population.

Key Findings

The key findings are summarized as follows:

Online shopping is widespread for clothing items and restaurant food.

Respondents receive on average 5 deliveries per week, across all goods categories. 38.7 percent of the respondents reported performing their most recent shopping activity online, considering all goods categories. However, the frequency of online shopping varied across different goods categories. Most of the respondents that purchased groceries or household supplies reported having shopped in person (89 and 75 percent of the respondents respectively), while, in contrast, for those that purchased restaurant food and clothing items, two-thirds of respondents reported buying online in both categories. Online shopping is widespread in the clothing and restaurant food markets, but less in grocery and household supplies markets. Of the consumers that shopped online for restaurant food, 76 percent of them decided to travel to take out (also referred to as curbside pickup), and only 24 percent of them chose to have the meal delivered directly to their home.

Online shopping is more widespread among mobility-impaired individuals

Participants were asked whether they had a disability that limited physical activities such as carrying, walking, lifting, etc. Of the 918 participants, 98 (11%) responded that they did have a disability that fit this description. The share of respondents that shop online was higher among mobility-impaired individuals (30 percent online for delivery and 19 percent online for pick-up) compared to individuals that did not report any mobility impairment (23 percent online for delivery and 12 percent online for pick-up).

Driving is the predominant shopping travel mode

Of the sample of respondents, 96 percent reported having access to a motorized vehicle within their household. Driving is also the most common shopping mode of in-person travel, with 81.3 percent of respondents reporting that they drove to a store to shop. Walking is a distant second preferred shopping travel mode, with 13.1 percent of respondents reporting having walked to a store. Biking and public transit were rarely adopted as a shopping travel mode, together they were observed 5.6 percent of the time. Though included as a travel option, only 1 participant reported using a rideshare vehicle to shop.

Electrification in West Seattle

Of the respondents that have access to a motorized vehicle in their households, 9.8 percent of them reported owning an electric vehicle. Car ownership is much more widespread than bike ownership, with 51.6 percent of the respondents reporting having access to a bike. Among these, 15.5 percent of them said that at least one of their bikes is electric.

The 10-minute city

The average walking time across all types of goods purchased was 10 minutes. The average driving time, for those respondents that reported driving to a store, was also about 10 minutes, except for those who reported purchasing clothing items, which reported on average of 27-minute trip time (both using a private car or using public transit). The longest travel times are seen mostly for respondents that took public transit as a shopping travel mode.

Living in proximity to stores reduces driving and online deliveries

A higher number of stores within a 10-minute walking distance (0.5 miles) is correlated with a higher number of consumers choosing to walk to a store, compared to those that chose to drive to a store or that shopped online. This is true across all goods types, but it is more significantly seen in grocery shopping. Moreover, accessibility to commercial establishments at a walking distance has a stronger impact on reducing the likelihood of driving, and at a lesser magnitude, reduces the propensity of shopping online.

Delivery to the doorstep is the most common destination for online deliveries

For those that chose to buy online, the most common delivery destination was at the respondents’ home doorstep (84 percent of respondents reported receiving online deliveries at home). The second most frequently used delivery destination was parcel lockers (15 percent of respondents), with 12 percent of respondents making use of private lockers, while only 3 percent made use of public lockers. The remaining one percent received deliveries at other destinations (e.g. office or nearby store).

The West Seattle High Bridge closure incentivized local shopping

When asked about the impacts of the West Seattle Bridge closure on individual online and shopping travel behaviors, more respondents reported buying more locally and online, vs. traveling farther for shopping and buying in person.

Authors: Dr. Anne GoodchildDr. Giacomo Dalla ChiaraRishi VermaKelly Rula

Recommended Citation:
Goodchild, A., Dalla Chiara, G., Verma, R., Rula, K. (2023) Analysis of Online Shopping and Shopping Travel Behaviors in West Seattle, Urban Freight Lab.

Report

Supporting Comprehensive Urban Freight Planning by Mapping Private Load and Unload Facilities

Download PDF (1.27 MB)

Publication Date: 2023

Summary:

Freight load and unload facilities located off the public right-of-way are typically not documented in publicly available databases. Without detailed knowledge of these facilities, i.e. private freight load and unload infrastructure, cities are limited in their ability to complete system-wide freight planning and to comprehensively evaluate the total supply of load and unload spaces in the city. To address this challenge, this research describes the development and application of a data collection methodology and a typology of private freight load/unload facilities for their inventory and documentation in dense urban centers.

The tools developed in this research are practice-ready and can be implemented in other cities to support research, policy and planning approaches that aim to improve the urban freight system. Assessment of the degree of harmonization between the current delivery vehicle dimensions and infrastructure they service is a crucial step of any policy that addresses private freight load/unload infrastructures. This includes providing: the adequate access dimensions, capacity to accommodate the volume and vehicle type, and an effective connecting design between the facilities and the public right-of-way.

A case study in Downtown Seattle found more than 337 private freight facilities for loading/unloading of goods but that translates into only 5% of the buildings in the densest areas of the city had these facilities. Alleys were found to play a critical role since 36% of this freight infrastructure was accessed through alleys.

This research results in the first urban inventory of private freight load/unload infrastructure, which has been shown to be a valuable resource for the City of Seattle that can be used to better understand and plan for the urban freight system.

Authors: José Luis Machado LeónGabriela Girón-ValderramaDr. Anne GoodchildDr. Ed McCormack

Recommended Citation:
Machado León, J., Girón-Valderrama, G., Goodchild, A., & McCormack, E. Supporting Comprehensive Urban Freight Planning by Mapping Private Load and Unload Facilities (2023).