Research Topic: Urban Goods Delivery and Land Use
Urban goods delivery and land use planning is a specialized aspect of urban planning that focuses on the efficient and sustainable management of land and infrastructure to support the delivery of goods in urban areas.
A Policy-Sensitive Model of Parking Choice for Commercial Vehicles in Urban Areas
Understanding factors that drive the parking choice of commercial vehicles at delivery stops in cities can enhance logistics operations and the management of freight parking infrastructure, mitigate illegal parking, and ultimately reduce traffic congestion. In this paper, we focus on this decision-making process at large urban freight traffic generators, such as retail malls and transit terminals, that attract a large share of urban commercial vehicle traffic. Existing literature on parking behavior modeling has focused on passenger vehicles. This paper presents a discrete choice model for commercial vehicle parking choice in urban areas. The model parameters were estimated by using detailed, real-world data on commercial vehicle parking choices collected in two commercial urban areas in Singapore. The model analyzes the effect of several variables on the parking behavior of commercial vehicle drivers, including the presence of congestion and queuing, attitudes toward illegal parking, and pricing (parking fees). The model was validated against real data and applied within a discrete-event simulation to test the economic and environmental impacts of several parking measures, including pricing strategies and parking enforcement.
Dalla Chiara, Giacomo and Cheah, Lynette and Azevedo, Carlos Lima and Ben-Akiva, Moshe E. (2020). A Policy-Sensitive Model of Parking Choice for Commercial Vehicles in Urban Areas. Transportation Science, 54(3), 606–630. https://doi.org/10.1287/trsc.2019.0970
Moving Goods to Consumers: Land Use Patterns, Logistics, and Emissions
Worldwide, awareness has been raised about the dangers of growing greenhouse gas emissions. In the United States, transportation is a key contributor to greenhouse gas emissions. American and European researchers have identified a potential to reduce greenhouse gas emissions by replacing passenger vehicle travel with delivery service. These reductions are possible because, while delivery vehicles have higher rates of greenhouse gas emissions than private light-duty vehicles, the routing of delivery vehicles to customers is far more efficient than those customers traveling independently. In addition to lowering travel-associated greenhouse gas emissions, because of their more efficient routing and tendency to occur during off-peak hours, delivery services have the potential to reduce congestion. Thus, replacing passenger vehicle travel with delivery service provides opportunity to address global concerns – greenhouse gas emissions and congestion. While addressing the impact of transportation on greenhouse gas emissions is critical, transportation also produces significant levels of criteria pollutants, which impact the health of those in the immediate area. These impacts are of particular concern in urban areas, which due to their constrained land availability increase proximity of residents to the roadway network. In the United States, heavy vehicles (those typically used for deliveries) produce a disproportionate amount of NOx and particulate matter – heavy vehicles represent roughly 9% of vehicle miles travelled but produce nearly 50% of the NOx and PM10 from transportation. Researchers have noted that urban policies designed to address local concerns including air quality impacts and noise pollution – like time and size restrictions – have a tendency to increase global impacts, by increasing the number of vehicles on the road, by increasing the total VMT required, or by increasing the amount of CO2 generated. The work presented here is designed to determine whether replacing passenger vehicle travel with delivery service can address both concerns simultaneously. In other words, can replacing passenger travel with delivery service reduce congestion and CO2 emissions as well as selected criteria pollutants? Further, does the design of the delivery service impacts the results? Lastly, how do these impacts differ in rural versus urban land use patterns? This work models the amount of VMT, CO2, NOx, and PM10 generated by personal travel and delivery vehicles in a number of different development patterns and in a number of different scenarios, including various warehouse locations. In all scenarios, VMT is reduced through the use of delivery service, and in all scenarios, NOx and PM10 are lowest when passenger vehicles are used for the last mile of travel. The goods movement scheme that results in the lowest generation of CO2, however, varies by municipality. Regression models for each goods movement scheme and models that compare sets of goods movement schemes were developed. The most influential variables in all models were measures of roadway density and proximity of a service area to the regional warehouse. These results allow for a comparison of the impacts of greenhouse gas emissions in the form of CO2 to local criteria pollutants (NOx and PM10) for each scenario. These efforts will contribute to increased integration of goods movement in urban planning, inform policies designed to mitigate the impacts of goods movement vehicles, and provide insights into achieving sustainability targets, especially as online shopping and goods delivery becomes more prevalent.
Wygonic, Erica. 2014, Moving Goods to Consumers: Land Use Patterns, Logistics, and Emissions, University of Washington, Doctoral Dissertation.
Freight and Transit Lane Case Study
The Seattle Department of Transportation (SDOT) engaged the Urban Freight Lab at the Supply Chain Transportation and Logistics Center at the University of Washington to conduct research on the impacts of a freight and transit (FAT) lane that was implemented in January 2019 in Seattle. To improve freight mobility in the City of Seattle and realize the objectives included in the city’s Freight Master Plan (FMP), the FAT lane was opened upon the closing of the Alaskan Way Viaduct.
The objective of this study was therefore to evaluate the performance and utilization of the FAT lane. Street camera video recordings from two separate intersection locations were used for this research.
Vehicles were categorized into ten different groups, including drayage with container and drayage without container, to capture their different behavior. Drayage vehicles are vehicles transporting cargo to a warehouse or to another port. Human data reducers used street camera videos to count vehicles in those ten designated groups.
The results of the traffic volume analysis showed that transit vehicles chose the FAT lane over the general purpose lane at ratios of higher than 90 percent. By the time of day, transit vehicle volumes in the FAT lane followed a different pattern than freight vehicles. Transit vehicle volumes peaked around afternoon rush hours, but freight activity decreased during that same time. Some freight vehicles used the FAT lane, but their ratio in the FAT lane decreased when bus volumes increased. The ratio of unauthorized vehicles in the FAT lane increased during congestion.
Further analysis described in this report included a multinomial logistic regression model to estimate the factors influencing the choice of FAT lane over the regular lane. The results showed that lane choice was dependent on the day of week, time of day, vehicle type, and location features. Density, as a measure of congestion, was found to be statistically insignificant for the model.
Urban Freight Lab (2020). Freight and Transit Lane Case Study.
Finding a (Food) Way: A GIS Modeling Approach to Quantifying Local Food Transportation Systems
In recent years the focus on and prioritization of the notion of local food, food access and sustainability has been increasing throughout the U.S., especially in urban areas. The rising demand and growing preference for local produce in turn leads to changes in how we transport food. The supply chains found in urban areas are already complicated and costly, and as demand changes this poses a challenge if the local food movement is to be accommodated in our cities. A new initiative seeks to mitigate these challenges through the introduction of a mobile application that allows users to order local produce online. Logistics modeling was conducted as a case study to support this effort. The goal of the research was to be able to inform and support decision-making on the logistics to support agricultural development and equal food access. The research found that there is opportunity for improvement to how local food is accessed, and that these mobile applications have the possibility to address food accessibility, economic vitality and sustainability, with a lower negative impact on the transportation environment.
Bovbjerg Alligood, Anna (2017). Finding a (Food) Way: A GIS Modeling Approach to Quantifying Local Food Transportation Systems, University of Washington Master's Degree Thesis.
Common MicroHub Research Project: Research Scan
This research scan revealed a lack of an established and widely accepted definition for the concept of consolidation centers or microhubs. Many recent implementations of urban freight consolidation have focused on bundling goods close to the delivery point by creating logistical platforms in the heart of urban areas. These have shared a key purpose: to avoid freight vehicles traveling into urban centers with partial loads.
To establish definitions of micro-consolidation and its typologies, it is important to review previous efforts in the literature that have explained and evaluated urban consolidation centers and lessons that have led to the search for new alternatives. Starting in 1970s, the urban consolidation center (UCC) concept was implemented in several European cities and urban regions. These were mostly led by commercial enterprises with temporary or even structural support from the government to compensate for additional transshipment costs. Allen et. al. defined the UCC as a “logistic base located in the vicinity of the place of performing services (e.g., city centers, whole cities, or specific locations like shopping malls) where numerous enterprisers deliver goods destined for the serviced area from which consolidated deliveries as well as additional logistic and retailed services are realized”.
Many of these implementations failed to operate in the long term because of low throughput volumes, the inability to operate without financial support from government, and dissatisfaction with service levels. The cost of having an additional transshipment point often prevented the facilities from being cost-effective, and they could not operate when governmental subsidies were removed (4). From a commercial perspective, experiences with publicly operated UCCs were mostly negative, and centers that have operated since 2000 are often run single-handedly by major logistics operators.
Although it appears that many UCCs were not successful, that does not mean that the idea of an additional transshipment point should be sidelined completely (4). Several studies have mentioned the micro-consolidation concept as a transition from the classic UCC. Learning from previous experiences, Janjevic et. al. defined micro-consolidation centers as facilities that are located closer to the delivery area and have a more limited spatial range for delivery than classic UCCs. Similarly, Verlinde et. al., referred to micro-consolidation centers as “alternative” additional transshipment points that downscale the scope of the consolidation initiative further than a UCC.
In this project, a delivery microhub (or simply a microhub) was defined as a special case of UCC with closer proximity to the delivery point and serving a smaller range of service area. A microhub is a logistics facility where goods are bundled inside the urban area boundaries, that serves a limited spatial range, and that allows a mode shift to low-emission vehicles or soft transportation modes (e.g., walking or cargo bikes) for last-mile deliveries.
Urban Freight Lab (2020). Common MicroHub Research Project: Research Scan.
Are Cities’ Delivery Spaces in the Right Places? Mapping Truck Load/Unload Locations
Two converging trends – the rise of e‐commerce and urban population growth – challenge cities facing competing uses for road, curb and alley space. The University of Washington has formed a living Urban Freight Lab to solve city logistics problems that cross private and public sector boundaries. To assess the capacity of the city’s truck load/unload spaces, the lab collected GIS coordinates for private truck loading bays, and combined them with public GIS layers to create a comprehensive map of the city’s truck parking infrastructure. The chapter offers a practical approach to identify useful existent urban GIS data for little or no cost; collect original granular urban truck data for private freight bays and loading docks; and overlay the existing GIS layers and a new layer to study city‐wide truck parking capacity. The Urban Freight Lab’s first research project is addressing the “Final 50 Feet” of the urban delivery system.
Goodchild, Anne, Barb Ivanov, Ed McCormack, Anne Moudon, Jason Scully, José Machado Leon, and Gabriela Giron Valderrama. Are Cities' Delivery Spaces in the Right Places? Mapping Truck Load/Unload Locations: Modeling and Planning Initiatives. City Logistics 2: Modeling and Planning Initiatives (2018): 351-368. 10.1002/9781119425526.ch21
Dr. Anne Goodchild

- Founder, Urban Freight Lab
- Professor, Civil and Environmental Engineering
The Final 50 Feet of the Urban Goods Delivery System: Completing Seattle’s Greater Downtown Inventory of Private Loading & Unloading Infrastructure (Phase 2)
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 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. (7) One of the pilot’s goals is to add more parking capacity by using private infrastructure more efficiently, such as by inviting building managers in the test area to offer off-peak load/unload space to outside users. The U.S. Department of Energy’s Office of Energy Efficiency and Renewable Energy under the Vehicles Technologies Office is funding the project.
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.
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.
Changing Retail Business Models and the Impact on CO2 Emissions from Transport: E-commerce Deliveries in Urban and Rural Areas
While researchers have found relationships between passenger vehicle travel and smart growth development patterns, similar relationships have not been extensively studied between urban form and goods movement trip-making patterns. In rural areas, where shopping choice is more limited, goods movement delivery has the potential to be relatively more important than in more urban areas. As such, this work examines the relationships between certain development pattern characteristics including density and distance from warehousing. This work models the amount of carbon dioxide (CO2), nitrogen oxides (NOx), and Particle Matter (PM10) generated by personal travel and delivery vehicles in several different scenarios, including various warehouse locations. Linear models were estimated via regression modeling for each dependent variable for each goods movement strategy. Parsimonious models maintained nearly all of the explanatory power of more complex models and relied on one or two variables – a measure of road density and a measure of distance to the warehouse. Increasing road density or decreasing the distance to the warehouse reduces the impacts as measured in the dependent variables (vehicle miles traveled (VMT), CO2, NOx, and PM10). The authors find that delivery services offer relatively more CO2 reduction benefit in rural areas when compared to CO2 urban areas, and that in all cases delivery services offer significant VMT reductions. Delivery services in both urban and rural areas, however, increase NOX and PM10 emissions.
Goodchild, Anne, and Erica Wygonik. Changing retail business models and the impact on CO2 emissions from transport: e-commerce deliveries in urban and rural areas. No. 2013-S-UW-0023. Pacific Northwest Transportation Consortium, 2014.