Report

Analysis of Online Shopping and Shopping Travel Behaviors in West Seattle

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

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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).

Report

Final Report: Technology Integration to Gain Commercial Efficiency for the Urban Goods Delivery System, Meet Future Demand for City Passenger and Delivery Load/Unload Spaces, and Reduce Energy Consumption

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Publication Date: 2022

Summary:

This three-year project supported by the U.S. Department of Energy Vehicle Technologies Office has the potential to radically improve the urban freight system in ways that help both the public and private sectors. Working from 2018-2021, project researchers at the University of Washington’s Urban Freight Lab and collaborators at the Pacific Northwest National Laboratory have produced key data, tested technologies in complex urban settings, developed a prototype parking availability app, and helped close major knowledge gaps.

All the fruits of this project can be harnessed to help cities better understand, support and actively manage truck load/unload operations and their urban freight transport infrastructure. Project learnings and tools can be used to help make goods delivery firms more efficient by reducing miles traveled and the time it takes to complete deliveries, benefitting businesses and residents who rely on the urban freight system for supplies of goods. And, ultimately, these project learnings and tools can be used to make cities more livable by minimizing wasted travel, which, in turn, contributes to reductions in fuel consumption and emissions.

Cities today are challenged to effectively and efficiently manage their infrastructure to absorb the impacts of ever-increasing e-commerce-fueled delivery demand. All delivery trucks need to park somewhere to unload and load. Yet today’s delivery drivers have no visibility on available parking until they arrive at a site, which may be full. That means they can wind up cruising for parking, which wastes time and fuel and contributes to congestion. Once drivers do find parking, the faster they can unload at the spot, the faster they free up space for other drivers, helping others avoid circling for parking. This makes the parking space—and thus the greater load/unload network—more productive.

To this end, the research team successfully met the project’s three goals, developing and piloting strategies and technologies to:

Reduce parking-seeking behavior in the study area by 20%
Reduce parcel truck dwell time (the time a truck spends in a spot to load/unload) in the study area by 30%
Increase curb space, alley space, and private loading bay occupancy rates in the study area

The research team met these goals by creating and piloting on Seattle streets OpenPark, a first-of-its-kind real-time and forecasting curb parking app customized for commercial delivery drivers—giving drivers the “missing link” in their commonly used routing tools that tell them how best to get to delivery locations, but not what parking is available to use when they get there. Installing in-ground sensors on commercial vehicle load zones (CVLZs) and passenger load zones (PLZs) in the 10-block study area in Seattle’s downtown neighborhood of Belltown let researchers glean real-time curb parking data. The research team also met project goals by piloting three parcel lockers in public and private spaces open to any delivery carrier, creating a consolidated delivery hub that lets drivers complete deliveries faster and spend less time parked. Researchers collected and analyzed data to produce the first empirical, robust, statistically significant results as to the impact of the lockers, and app, on on-the-ground operations. In addition to collecting and analyzing sensor and other real-time and historical data, researchers rode along with delivery drivers to confirm real-world routing and parking behavior. Researchers also surveyed building managers on their private loading bay operations to understand how to boost usage.

Key findings that provide needed context for piloting promising urban delivery solutions:

After developing a novel model using GPS data to measure parking-seeking behavior, researchers were able to quantify that, on average, a delivery driver spends 28% of travel time searching for parking, totaling on average one hour per day for a parcel delivery driver. This project offers the first empirical proof of delivery drivers’ cruising for parking.
While many working models to date have assumed that urban delivery drivers always choose to double-park (unauthorized parking in the travel lane), this study found that behavior is rare: Double parking happened less than 5% of the times drivers parked.
That said, drivers do not always park where they are supposed to. The research team found that CVLZ parking took place approximately 50% of the time. The remaining 50% included mostly parking in “unauthorized” curb spaces, including no-parking zones, bus zones, entrances/exits of parking garages, etc.
Researcher ride-alongs with delivery drivers revealed parking behaviors other than unauthorized parking that waste valuable time and fuel: re-routing (after failing to find a desired space, giving up and doubling back to the delivery destination later in the day) and queuing (temporarily parking in an alternate location and waiting until the desired space becomes available).
Some 13% of all parking events in CVLZ spaces were estimated as overstays; the figure was 80% of all parking events in PLZ spaces. So, the curb is not being used efficiently or as the city intended as many parking events exceed the posted time limit.
Meantime, there is unused off-street capacity that could be tapped in Seattle’s Central Business District. Estimates show private loading bays could increase area parking capacity for commercial vehicles by at least 50%. But surveys show reported use of loading bays is low and property managers have little incentive to maximize it. Property managers find curb loading zones more convenient; it seems delivery drivers do, too, as they choose to park at the curb even when loading bay space is available.

Key findings from the technology and strategies employed:

Carriers give commercial drivers routing tools that optimize delivery routes by considering travel distance and (often) traffic patterns—but not details on parking availability. Limited parking availability can lead to significant driver delays through cruising for parking or rerouting, and today’s drivers are largely left on their own to assess and manage their parking situation as they pull up to deliver.

The project team worked closely with the City of Seattle to obtain permission to install parking sensors in the roadway and communications equipment to relay sensor data to project servers. The team also developed a fully functional and open application that offers both real-time parking availability and near-time prediction of parking availability, letting drivers pick forecasts 5, 15, or 30 minutes into the future depending on when the driver expects to arrive at the delivery destination. Drivers can also enter their vehicle length to customize availability information.

After developing, modeling, and piloting the real-time and forecasting parking app, researchers conducted an experiment to determine how use of the app impacted driver behavior and transportation outcomes. They found that:

Having access to parking availability via the app resulted in a 28% decrease in the time drivers spent cruising for parking. Exceeding our initial goal of reducing parking seeking behavior by 20%. In the study experiment, all drivers had the same 20-foot delivery van and the same number of randomly sampled delivery addresses in the study area. But some drivers had access to the app; others did not.
Preliminary results based on historic routing data show that the use of such a real-time curb parking information and prediction app can reduce route time by approximately 1.5%. An analysis collected historic parking occupancy and cruising information and integrated it into a model that was then used to revise scheduling and routing. This model optimally routed vehicles to minimize total driving and cruising time. However, since the urban environment is complex and consists of many random elements, results based on historic data underly a high amount of randomness. Analysis on synthetic routes suggests including parking availability in routing systems is especially promising for routes with high delivery density and with stops where the cruising time delays vary a lot along the planned time horizon; here, route time savings can reach approximately 20.4% — conditions outlined in the report.
The central tradeoff among four approaches to parking app architecture going forward is cost and accuracy. The research team found that it is possible to train machine learning models using only data from curb occupancy sensors and reach a higher than 90% accuracy. Training of state-space models (those using inputs such as time of day, day of the week, and location to predict future parking availability) is computationally inexpensive, but these models offer limited accuracy. In contrast, deep-learning models are highly accurate but computationally expensive and difficult to use on streaming data.

Common carrier lockers create delivery density, helping delivery people complete their work faster. The driver parks next to the locker system, loads packages into it, and returns to the truck. When delivery people spend less time going door-to-door (or floor-to-floor inside a building), it cuts the time their truck needs to be parked, increasing turnover and adding parking capacity in crowded cities. This project piloted and collected data on common carrier lockers in three study area buildings.

From piloting the common carrier parcel lockers, researchers found that:

The implementation of the parcel locker allowed delivery drivers to increase productivity: 40%-60% reduction in time spent in the building and 33% reduction in vehicle dwell time at the curb.

Authors: Dr. Anne GoodchildDr. Giacomo Dalla ChiaraFiete KruteinDr. Andisheh RanjbariDr. Ed McCormackElizabeth Guzy, Dr. Vinay Amatya (PNNL), Ms. Amelia Bleeker (PNNL), Dr. Milan Jain (PNNL)

Recommended Citation:
Urban Freight Lab (2022). Final Report: Technology Integration to Gain Commercial Efficiency for the Urban Goods Delivery System.

Report

Understanding and Mitigating Freight-Related Impacts from the West Seattle Bridge Closure

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Publication Date: 2022

Summary:

West Seattle (WS) is a part of the city of Seattle, Washington, but is located on a peninsula west of the Duwamish River. The West Seattle High-Rise Bridge serves as the primary connector between West Seattle and the rest of the city, carrying some 84,000 vehicles on average each day. On March 23, 2020, that high bridge was suddenly closed to all vehicle traffic for safety reasons due to greater-than-expected structural deterioration. The high bridge is now being repaired with a reopening planned for 2022. With the closure, vehicles have needed to take alternative routes to and from the peninsula, including the 1st Avenue South Bridge and the South Park Bridge, located some 2.1 and 3.4 miles south of the high bridge (see Figure 1). After the closure, the number of available vehicle traffic lanes across the river dropped from 21 to 12, with eight lanes on the 1st Avenue South Bridge and four on the South Park Bridge [2]. Before the closure, drivers also used the two-lane Spokane Street Low Bridge under the high bridge to access West Seattle. But after the closure, low bridge use was initially (as of March 2021) restricted from 5:00 am to 9:00 pm to authorized vehicles only, including emergency vehicles, public transit, and 10,000+ pound gross weight freight vehicles.

The unexpected high bridge closure disrupted passenger and freight mobility to and from WS, increasing travel times and creating bottlenecks on the remaining bridges. This has had negative impacts on the peninsula’s economy, as well as its livability. Concerns also persist regarding the environmental and health impacts of traffic detours into Duwamish Valley neighborhoods that are already disproportionately impacted by air pollution and asthma [4]. As traffic demand increases with the gradual recovery from the COVID-19 pandemic, the negative impacts could worsen. Notably, the timing of the high bridge closure coincided with the start of the pandemic and the resulting economic shutdowns and slowdowns that continue as of this writing. As such, it is difficult at times in this report to entirely disentangle the broader effects of the pandemic from the more specific effects of the bridge closure. This challenge surfaces especially in our interviews with study area businesses and with carriers performing deliveries and pick-ups in the study area: They report definite impacts, but it is not always clear how much of the impact stems from the bridge closure alone versus the bridge closure on top of the pandemic’s myriad ripple effects. That said, this study seeks to:

Document the impacts of the high bridge closure on freight flow, businesses, and carriers.
Understand current freight movements and quantify freight demand.
Identify mitigation strategies for freight flow to/from WS, both during the bridge closure and beyond.

Authors: Dr. Anne GoodchildDr. Giacomo Dalla ChiaraNota GoulianouŞeyma Güneş

Recommended Citation:
Urban Freight Lab (2022). Understanding and Mitigating Freight-Related Impacts from the West Seattle Bridge Closure.

Report

NYC Zero-Emissions Urban Freight and Green Loading Zones Market Research

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Publication Date: 2022

Summary:

In an effort to reduce emissions from last-mile deliveries and incentivize green vehicle adoption, The New York City Department of Transportation (NYC DOT) is seeking to implement a Green Loading Zone (GLZ) pilot program. A Green Loading Zone is curb space designated for the sole use of “green” vehicles, which could include electric and alternative fuel vehicles as well as other zero-emission delivery modes like electric-assist cargo bikes. To inform decisions about the program’s siting and regulations, this study was conducted by the University of Washington’s Urban Freight Lab (UFL) in collaboration with NYC DOT under the UFL’s Technical Assistance Program.

The study consists of three sources of information, focusing primarily on input from potential GLZ users, i.e., delivery companies. An online survey of these stakeholders was conducted, garnering 13 responses from 8 types of companies. Interviews were conducted with a parcel carrier and an electric vehicle manufacturer. Additionally, similar programs from around the world were researched to help identify current practices. The major findings are summarized below, followed by recommendations for siting, usage restriction and pricing of GLZs. It is important to note that these recommendations are based on the survey and interview findings and thus on benefits to delivery companies. However, other important factors such as environmental justice, land use patterns, and budgetary constraints should be considered when implementing GLZs.

Literature Review Findings

Green Loading Zones are a relatively novel approach to incentivizing electric vehicle (EV) adoption. Two relevant pilot programs exist in the United States, one in Santa Monica, CA and the other one in Los Angeles, CA. Both are “zero-emission” delivery programs, meaning alternative fuel vehicles that reduce emissions (compared to fossil fuel vehicles) are not included in the pilot’s parking benefits (dedicated spaces and free parking). Other cities including Washington, DC and Vancouver, Canada are also creating truck-only zones and dedicating parking to EVs in their efforts to reduce emissions. Bremen, Germany also has a similar program called an Environmental Loading Point.

Many cities in Europe are implementing low- or zero-emission zones. These are different than GLZs in that entire cities or sections of cities are restricted to vehicles that meet certain emissions criteria. London, Paris, and 13 Dutch municipalities are all implementing low-emission zones. These zones have achieved some success in reducing greenhouse gas emissions: in London, CO2 from vehicles has been reduced by 13 percent. Companies operating in those cities have opted to purchase cleaner vehicles or to replace trucks with alternative modes like cargo bikes. In addition to demonstrating similar goals as NYC DOT, these programs provide insights to the siting and structure of GLZs. Loading zones have been selected based on equity concerns, delivery demand, and commercial density. Every city in the literature review has installed specific signage for the programs to clearly convey the regulations involved.

Survey and interview Findings

A range of company types replied to the survey: parcel carriers (large shippers), small shippers, e-commerce and retail companies, freight distributors, a truck dealer, a liquid fuel delivery company, and a logistics NYC association (answering on behalf of members). The majority of these companies will be increasing their fleet sizes over the next ten years, and most plan to increase the share of EVs in their fleets while doing so. A smaller share (4 of 13) also plans to increase their share of alternative fuel vehicles. The most cited reasons for increasing fleet size and green vehicle share are: 1) internal sustainability goals, 2) social responsibility, and 3) new vehicles/models coming to the market.

Green vehicle adoption is not without its challenges. For EV adoption specifically, companies identified three major barriers: 1) competition in the EV market, 2) electric grid requirements upstream of company-owned facilities, and 3) lack of adequate government-supported purchasing subsidies. To overcome these barriers, respondents would like larger or more government purchasing incentives and reduced toll or parking rates for EVs. However, the majority of companies also expressed a willingness to pay for GLZs at similar rates to other commercial loading zones.

As for area coverage, all respondents deliver to Manhattan, Queens, and Brooklyn. 11 of 13 deliver to Staten Island and the Bronx as well. All EV and cargo bike operators deliver to Manhattan, whereas only one EV operator and one cargo bike operator deliver to all five boroughs of NYC. Respondents deliver at all times of day, but the busiest times are between 9:00AM and 4:00PM (stated by 8 of 13 respondents). Peak periods are busiest for four companies in the morning (6:00AM-9:00AM) and six companies in the evening (4:00PM-9:00PM).

The interviews supported findings from the survey. Both interviewed companies have a vested interest in reducing their environmental footprint and plan to use or produce exclusively zero-emission vehicles by 2050 (carrier) or 2035 (manufacturer). However, they noted challenges to electrifying entire fleets for cities. Charging infrastructure needs to be expanded, but incentives are also needed (parking benefits, subsidies, expedited permitting) to make the market viable for many delivery companies.

Recommendations

The preceding findings informed four key recommendations:

GLZs should be made available to multiple modes: green vehicles and cargo bikes. Adequate curb space might be needed to accommodate multiple step-side vans plus a small vehicle and cargo bikes, but this should be balanced against curb utilization rates and anticipated dwell times to maximize curb use.
Explore piloting GLZs in Lower Manhattan and commercial areas of Midtown Manhattan; they could be the most beneficial locations for the pilot according to survey respondents.
The preferred layout for GLZs is several spaces distributed across multiple blocks.
DOT can charge for the GLZ use. It is recommended that rates not exceed current parking prices in the selected neighborhood, but some companies are willing to pay a modest increase over that rate to avoid parking tickets.

Authors: Thomas MaxnerNota GoulianouDr. Andisheh RanjbariDr. Anne Goodchild

Recommended Citation:
Urban Freight Lab (2022). NYC Zero-Emissions Urban Freight and Green Loading Zones Market Research.

Report

Mapping the Challenges to Sustainable Urban Freight

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Publication Date: 2022

Summary:

Just as there has been a push for more climate-friendly passenger travel in recent years, that same push is building for freight travel. At the same time ecommerce is booming and goods delivery in cities is rising, sustainability has become a policy focus for city governments and a corporate priority for companies.

Why? Cities report being motivated to be responsive to residents, businesses, and the goals of elected leaders. Companies report being motivated by cost reduction, efficiency, branding and customer loyalty, and corporate responsibility.

For its part, Amazon in 2019 pledged to become a net-zero carbon business by 2040. In the wake of that pledge, Amazon financially supported this Urban Freight Lab research examining two key questions:

What is the current state of sustainable urban freight planning in the United States?
What are the challenges to achieving a sustainable urban freight system in the United States and Canada?

Because the research literature reveals that denser, more populous cities are the areas most impacted by climate change, we focused our analysis on the 58 cities representing the largest, densest, and fastest-growing cities in the U.S. found within the nation’s 25 largest, densest, and fastest-growing metro areas. Our population, growth, and density focus resulted in heavy concentration in California, Texas, and Florida and light representation in the Midwest.

Within those 58 cities, we reviewed 243 city planning documents related to transportation and conducted 25 interviews with public and private stakeholders. We intentionally sought out both the public and private sectors because actors in each are setting carbon-reduction goals and drafting plans and taking actions to address climate change in the urban freight space.

In our research, we found that:

The overwhelming majority of cities currently have no plans to support sustainable urban freight. As of today, ten percent of the cities considered in this research have taken meaningful steps towards decarbonizing the sector.
Supply chains are complex and the focus on urban supply chain sustainability is relatively new. This reality helps explain the myriad challenges to moving toward a sustainable urban freight system.
For city governments, those challenges include a need to adapt existing tools and policy levers or create new ones, as well as a lack of resources and leadership to make an impact in the industry.
For companies, those challenges include concerns about the time, cost, technology, and labor complexity such moves could require.

“Sustainability” can mean many things. In this research, we define sustainable urban freight as that which reduces carbon dioxide emissions, with their elimination—which we refer to as decarbonization—as the ultimate end goal. This definition represents just one environmental impact of urban freight and does not include, for example, noise pollution, NOx or SOx emissions, black carbon, or particulate matter.

We define urban freight as last-mile delivery within cities, including parcel deliveries made by companies like Amazon and UPS and wholesale deliveries made by companies like Costco and Pepsi. We do not include regional or drayage/port freight as those merely transit through cities and face distinct sustainability barriers.

Authors: Urban Freight Lab

Recommended Citation:
Urban Freight Lab (2022). Mapping the Challenges to Sustainable Urban Freight.

Report

The Seattle Neighborhood Delivery Hub Pilot Project: An Evaluation of the Operational Impacts of a Neighborhood Delivery Hub Model on Last-Mile Delivery

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Publication Date: 2021

Summary:

As one of the nation’s first zero-emissions last-mile delivery pilots, the Seattle Neighborhood Delivery Hub served as a testbed for innovative sustainable urban logistics strategies on the ground in Seattle’s dense Uptown neighborhood. Providers could test and evaluate new technologies, vehicles, and delivery models — all in service of quickly getting to market new more fuel- and resource-efficient solutions, reducing emissions and congestion, and making our cities more livable and sustainable.

These technologies are also an important part of the City of Seattle’s Transportation Electrification Blueprint, including the goal of transitioning 30% of goods delivery to zero emissions by 2030.

Authors: Urban Freight Lab

Recommended Citation:
Urban Freight Lab (2021). The Seattle Neighborhood Delivery Hub Pilot Project: An Evaluation of the Operational Impacts of a Neighborhood Delivery Hub Model on Last-Mile Delivery.

Report

Cargo E-Bike Delivery Pilot Test in Seattle

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Publication Date: 2020

Summary:

This study performed an empirical analysis to evaluate the implementation of a cargo e-bike delivery system pilot tested by the United Parcel Service, Inc. (UPS) in Seattle, Washington. During the pilot, a cargo e-bike with a removable cargo container was used to perform last-mile deliveries in downtown Seattle. Cargo containers were pre-loaded daily at the UPS Seattle depot and loaded onto a trailer, which was then carried to a parking lot in downtown.

Data were obtained for two study phases. In the “before-pilot” phase, data were obtained from truck routes that operated in the same areas where the cargo e-bike was proposed to operate. In the “pilot” phase, data were obtained from the cargo e-bike route and from the truck routes that simultaneously delivered in the same neighborhoods. Data were subsequently analyzed to assess the performance of the cargo e-bike system versus the traditional truck-only delivery system.

The study first analyzed data from the before-pilot phase to characterize truck delivery activity. Analysis focused on three metrics: time spent cruising for parking, delivery distance, and dwell time. The following findings were reported:

On average, a truck driver spent about 2 minutes cruising for parking for each delivery trip, which represented 28 percent of total trip time. On average, a driver spent about 50 minutes a day cruising for parking.
Most of the deliveries performed were about 30 meters (98 feet) from the vehicle stop location, which is less than the length of an average blockface in downtown Seattle (100 meters, 328 feet). Only 10 percent of deliveries were more 100 meters away from the vehicle stop location.
Most truck dwell times were around 5 minutes. However, the dwell time distribution was right-skewed, with a median dwell time of 17.5 minutes.

Three other metrics were evaluated for both the before-pilot and the pilot study phases: delivery area, number of delivery locations, and number of packages delivered and failed first delivery rate. The following results were obtained:

A comparison of the delivery areas of the trucks and the cargo e-bike before and after the pilot showed that the trucks and cargo e-bike delivered approximately in the same geographic areas, with no significant changes in the trucks’ delivery areas before and during the pilot.
The number of establishments the cargo e-bike delivered to in a single tour during the pilot phase was found to be 31 percent of the number of delivery locations visited, on average, by a truck in a single tour during the before-pilot phase, and 28 percent during the pilot phase.
During the pilot, the cargo e-bike delivered on average to five establishments per hour, representing 30 percent of the establishments visited per hour by a truck in the before-pilot phase and 25 percent during the pilot.
During the pilot, the number of establishments the cargo e-bike delivered to increased over time, suggesting a potential for improvement in the efficiency of the cargo e-bike.
The cargo e-bike delivered 24 percent of the number of packages delivered by a truck during a single tour, on average, before the pilot and 20 percent during the pilot.
Both before and during the pilot the delivery failed rate (percentage of packages that were not delivered throughout the day) was approximately 0.8 percent. The cargo e-bike experienced a statistically significantly lower failed rate of 0.5 percent with respect to the truck fail rate, with most tours experiencing no failed first deliveries.

The above reported empirical results should be interpreted only in the light of the data obtained. Moreover, some of the results are affected by the fact that the pilot coincided with the holiday season, in which above average demand was experienced. Moreover, because the pilot lasted only one month, not enough time was given for the system to run at “full-speed.”

Authors: Urban Freight Lab

Recommended Citation:
Urban Freight Lab (2020). Cargo E-Bike Delivery Pilot Test in Seattle.

Report

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

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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

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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.