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Student Thesis and Dissertations

Moving Goods to Consumers: Land Use Patterns, Logistics, and Emissions

Publication Date: 2014
Summary:

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.

Authors: Erica Wygonik
Recommended Citation:
Wygonic, Erica. 2014, Moving Goods to Consumers: Land Use Patterns, Logistics, and Emissions, University of Washington, Doctoral Dissertation.
Thesis: Array
Technical Report

Freight and Transit Lane Case Study

 
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Publication Date: 2020
Summary:

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.

Recommended Citation:
Urban Freight Lab (2020). Freight and Transit Lane Case Study. 
Student Thesis and Dissertations

Finding a (Food) Way: A GIS Modeling Approach to Quantifying Local Food Transportation Systems

Publication Date: 2017
Summary:

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.

Recommended Citation:
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.
Thesis: Array
Technical Report

Common MicroHub Research Project: Research Scan

 
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Publication Date: 2020
Summary:

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.

Recommended Citation:
Urban Freight Lab (2020). Common MicroHub Research Project: Research Scan.
Chapter

Are Cities’ Delivery Spaces in the Right Places? Mapping Truck Load/Unload Locations

 
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Publication: City Logistics 2: Modeling and Planning Initiatives (Proceedings of the 2017 International Conference on City Logistics)
Volume: 2
Pages: 351-368
Publication Date: 2018
Summary:

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.

Recommended Citation:
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

Dr. Anne Goodchild
Dr. Anne Goodchild
  • Founder, Urban Freight Lab
  • Professor, Civil and Environmental Engineering
annegood@uw.edu  |  206-543-3747  |  Wilson Ceramics Lab 103
  • Urban goods delivery systems and land use
  • Logistics hubs and ports
  • Sustainable freight transportation systems
  • Supply chain management and freight transportation

Dr. Anne Goodchild is interested in the intersection between supply chain management and freight transportation. As an example of this, recent research is evaluating the changing nature of shopping and implications for goods delivery on CO2 emissions, local pollutants, and vehicle miles travelled. Her interest in economic and environmental sustainability is also demonstrated by her work looking at CO2 emissions in strategic routing and schedule planning in urban pick-up and delivery systems. Dr. Goodchild’s work in understanding supply chains, as they relate to the transport system, is demonstrated by her research funded by the SHRP2 freight data and modeling program, NCFRP 20, the FHWA’s Behavioral based National Freight Demand Model, and surveys and analysis funded by both the Washington and Oregon Departments of Transportation.

  • Innovation in Education Award, Institute of Transportation Engineers (ITE) Transportation Education Council (2021)
  • Outstanding Researcher Award, Pacific Northwest Transportation Consortium (PacTrans) (2021)
  • Outstanding Mentor Award, Department of Civil and Environmental Engineering (2020)
  • Person of the Year, Transportation Club of Seattle (2017)
  • Allan and Inger Osberg Endowed Professorship (2012 – 2016)
  • Community of Innovators Junior Faculty Research Award, College of Engineering (2012)
  • 2nd Prize, College-Industry Council on MH Education Outstanding Material Handling and Logistics paper (2008)
  • Dissertation Prize Honorable Mention, INFORMS Transportation Science and Logistics (2006)
  • PRISMS Presentation Competition Finalist, Institute for Operations Research and Management Science (2003)
  • Ph.D., Civil and Environmental Engineering, UC Berkeley (2005)
    (Dissertation: Crane Double Cycling in Container Ports: Algorithms, Evaluation, and Planning)
  • M.S., Civil and Environmental Engineering, UC Berkeley (2003)
  • B.S., Mathematics, UC Davis (1995)

Dr. Anne Goodchild leads the University of Washington’s academic and research efforts in the area of supply chain, logistics, and freight transportation. She is Professor of Civil and Environmental Engineering, and Founding Director of both the Supply Chain Transportation & Logistics online Master’s degree program and the Urban Freight Lab (UFL).

Under Goodchild’s leadership, the UFL coined the increasingly used term “Final 50 Feet” and defined it as the last leg of the supply chain for urban deliveries—including finding parking, moving items from a delivery vehicle, navigating traffic, sidewalks, intersections, bike lanes, and building security, and ending with the recipient. In addition to being key to customer satisfaction, this final segment is both the most expensive (where an estimated 25-50% of total supply chain costs are incurred) and most time-consuming part of the delivery process—and ripe for improvement. One of the hurdles in the final 50 feet is that many different parties are involved—city departments of transportation, delivery carriers, property owners, residents, and consumers—making a collaborative effort between sectors essential for developing mutually beneficial solutions. Using a systems engineering approach, the UFL has completed innovative research projects that provide foundational data and proven strategies, such as:

Dr. Goodchild’s contributions to transportation engineering in the U.S. and abroad have been significant. She is an expert in international border and port operations and has been instrumental in bringing supply chain concepts to freight model architectures. She has worked at the forefront of GPS data applications, identifying observable transportation characteristics that statistically predict transportation behavior.

She is the author or co-author of more than 100 research publications, and serves as associate editor for the peer-reviewed scientific journal Transportation Letters. From 2016 to 2018 she chaired the National Academies of Science, Engineering, and Medicine’s Transportation Research Board (TRB) Freight and Marine Chairs group, the top national research organization in her field. She teaches logistics and analysis, global trade, transportation & logistics management, and advises graduate students in transportation engineering, and has won several teaching and research awards.

Dr. Goodchild is the recipient of numerous research grants, including recent awards from the U.S. Department of Transportation, PacTrans (Regional University Transportation Center for Federal Region 10), Seattle Department of Transportation, Federal Highway Administration’s Strategic Highway Research Program (SHRP2), TRB’s National Cooperative Freight Research Program, and the Washington and Oregon State Departments of Transportation.

Dr. Goodchild holds both a doctorate (2005) and a master’s degree (2003) in civil and environmental engineering from the University of California, Berkeley, and a bachelor’s degree (with high honors) in mathematics from University of California, Davis. Before earning her Ph.D. she worked for PricewaterhouseCoopers LLP and Applied Decision Analysis Inc. in Europe and North America designing efficient airline schedules and optimizing research portfolios. She joined the Department of Civil and Environmental Engineering faculty at the University of Washington in 2005. In addition, she holds a Visiting Professorship at the University of Gothenburg in Sweden and a Research Affiliateship at Urban@UW (an initiative of the Office of Research and CoMotion at the University of Washington).

  • Adjunct Professor, Industrial & Systems Engineering, University of Washington
  • Visiting Professor, School of Business, Economics and Law, University of Gothenburg (Sweden)
  • Affiliate, Urban @ UW, University of Washington
  • Co-Chair, Aurora Urban Freight Consortium
  • Member, NECTAR (The Network on European Communications and Transport Activity Research) Cluster 3 Organizing Committee, Logistics and Freight
  • Member, Washington State Freight Advisory Committee (Chair, 2011-2013)
  • Organizing Committee, International Urban Freight Conference (I-NUF), Long Beach, CA (2017, 2019, 2021)
  • Associate Editor, Transportation Research Record (TRR) (2019-2020)
  • Member, National Academies of Sciences, Engineering, and Medicine, Transportation Research Board (TRB), Taskforce on Development of Freight Fluidity Performance Measures (2016-2019)
  • Group Chair, National Academies of Sciences, Engineering, and Medicine, Transportation Research Board (TRB), Freight Group (2016-2019)
  • Chair, National Academies of Sciences, Engineering, and Medicine, Transportation Research Board (TRB), Freight and Marine Chairs Group (2016-2018)
  • Chair, National Academies of Sciences, Engineering, and Medicine, Transportation Research Board (TRB) Standing Committee on Intermodal Freight Transportation (AT045) (2013-2016)
  • Member, National Academy of Sciences, Committee for Study of Freight Rail Transportation and Regulation (2014-2015)
  • Editor, International Journal of Logistics and Transportation Research (2013-2014)
  • Member, Puget Sound Regional Council Freight Advisory Panel (2008-2011)
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:

  1. 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.
  2. 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.

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.
Technical Report

Changing Retail Business Models and the Impact on CO2 Emissions from Transport: E-commerce Deliveries in Urban and Rural Areas

 
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Publication: Pacific Northwest Transportation Consortium (PacTrans)
Volume: 2013-S-UW-0023
Publication Date: 2014
Summary:

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.

Authors: Dr. Anne Goodchild, Erica Wygonik
Recommended Citation:
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.

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:

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

Truck Trip Generation by Grocery Stores

 
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Publication: Washington State Transportation Innovations Unit and Washington State Transportation Commission
Publication Date: 2010
Summary:
Quantifying the relationship between the number and types of truck trips generated by different land uses provides information useful for traffic demand analyses, forecasting models, and a general understanding of the factors that affect truck mobility. This project evaluated data collection methodologies for determining truck trip generation rates by studying a specific kind of establishment. This effort focused on grocery stores and collected both interview and manual count data from eight supermarkets in the Puget Sound region.
We selected grocery stores for this project because they constitute a common land use that is present in almost every type of neighborhood in the metropolitan region. Grocery stores generate truck trips that have the potential to affect all levels of the transportation roadway network, from local roads in neighborhoods to highways. The eight stores in the Puget Sound region identified for this study were diverse and included both national and local chains. The stores ranged in size from 23,000 to 53,500 square feet and included a variety of urban and suburban locations.
Methodologies for gathering trip generation information were identified in the literature. Telephone interviews and manual counts, which are frequently used data collection methodologies, were explored in this project. The project started with telephone interviews of four distribution centers. This step helped to refine the interview approach and helped to determined that data from larger warehouses could not be easily used to develop information on the number of trips traveling to individual stores. A second round of interviews, lasting between 10 and 15 minutes, was then conducted with the managers or receivers of the nine grocery stores. In addition to the number of truck trips that the store generated, the interviews explored a range of topics related to the busiest days and their delivery windows. This information was used to set up manual, on-site truck counts at each of the grocery stores.
We concluded that a combination of telephone interviews and manual counts is a reasonable way to collect accurate truck trip generation rates. Telephone interviews were an important first step. They established contact with grocery stores, which then provided permission for on-site manual counts. Information elicited from store interviews also included the days and times when the viii truck deliveries occurred so that the manual counts could be scheduled to reflect optimal times. In addition, the interview conversations provided sometimes unanticipated but valuable information that was relevant to understanding truck trip-generation rates. Because it is cost prohibitive and inefficient to send manual counting teams to observe facilities for long shifts, information from store managers regarding their delivery windows and hours made the counts more feasible.
The Puget Sound grocery stores in the study (all of which were conventional supermarkets) generated an average of 18 truck trips per day on typical weekdays. These daily counts were probably low, as some of the stores accepted a few late deliveries outside of the receiving windows. Most of these truck arrivals occurred before noon, and the average delivery time was 27 minutes. Although peak days of the week varied across the sample set, all reported higher volumes during holidays.
The manual counts (15 site observations) provided more accurate truck trip generation rates than did telephone interviews. The interview responses indicated approximately ten to twelve trucks per day in comparison to the average of 18 trucks per day counted at each store by observers. The telephone interviewees at the grocery stores clearly underestimated the number of trucks and provided only minimal information on truck characteristics. Manual counts also provided more detailed information regarding truck type, delivery location (loading docks or front door), average delivery time, and product mix.
Few grocery store characteristics that could be directly related to truck trip generation rates were identified. The project team reviewed literature discussing both trip generation data collection and grocery store management and could not identify any specific characteristic that could be used to quantify the number of truck trips generated by different stores. While size or employment is often related to truck trips in the ITE Trip Generation Manual, this effort did not find any direct relationship with these variables, with a possible exception related to a store’s size. This finding, that smaller stores generated more trucks trips, suggests that one promising area to explore is the linkage between the level at which stores are served by regional warehouses or direct service delivery (DSD) and the number and type of truck trips. The manual counts indicated variability in the nature and size of the delivery trucks, which in turn related to ix whether the deliveries were at the front door (often small trucks and DSD) or loading dock (larger trucks from warehouses with consolidated loads). Smaller stores often use more DSD, which may result in more truck trips generated. It is also possible that smaller stores had smaller stock rooms, requiring more frequent deliveries. Other census-related variables such median household income, residential density and jobs-housing balance, were evaluated, but no significant relationships to truck trip rates were found.

 

Authors: Dr. Ed McCormack, Alon Bassok, Emily Fishkin, Chilan Ta
Recommended Citation:
McCormack, E., Ta, C., Bassok, A., & Fishkin, E. (2010). Truck Trip Generation by Grocery Stores. (No. TNW2010-04).