Paper

Delivery by Drone: An Evaluation of Unmanned Aerial Vehicle Technology in Reducing CO2 Emissions in the Delivery Service Industry

URL: https://doi.org/10.1016/j.trd.2017.02.017

Publication: Transportation Research Part D: Transport and Environment

Volume: 61

Pages: 58-67

Publication Date: 2018

Summary:

This research paper estimates carbon dioxide (CO2) emissions and vehicle-miles traveled (VMT) levels of two delivery models, one by trucks and the other by unmanned aerial vehicles (UAVs), or “drones.”

Using several ArcGIS tools and emission standards within a framework of logistical and operational assumptions, it has been found that emission results vary greatly and are highly dependent on the energy requirements of the drone, as well as the distance it must travel and the number of recipients it serves.

Still, general conditions are identified under which drones are likely to provide a CO2 benefit – when service zones are close to the depot, have small numbers of stops, or both. Additionally, measures of VMT for both modes were found to be relatively consistent with existing literature that compares traditional passenger travel with truck delivery.

Authors: Dr. Anne Goodchild, Jordan Toy

Recommended Citation:
Goodchild, Anne, and Jordan Toy. "Delivery by Drone: An Evaluation of Unmanned Aerial Vehicle Technology in Reducing CO2 Emissions in the Delivery Service Industry" Transportation Research Part D: Transport and Environment 61 (2018): 58-67.

Presentation

Using a GIS-based Emissions Minimization Vehicle Routing Problem with Time Windows (EVRPTW) Model to Evaluate CO2 Emissions and Costs: Two Case Studies Comparing Changes Within and Between Fleets

Publication: Transportation Research Board 90th Annual Meeting

Publication Date: 2010

Summary:

Growing pressure to limit greenhouse gas emissions is changing the way businesses operate. A model was developed in ArcGIS to evaluate the trade-offs between cost, service quality (represented by time window guarantees), and emissions of urban pickup and delivery systems under these changing pressures.

A specific case study involving a real fleet with specific operational characteristics is modeled as an emissions minimization vehicle routing problem with time windows (EVRPTW). Analyses of different external policies and internal operational changes provide insight into the impact of these changes on cost, service quality, and emissions. Specific considerations of the influence of time windows, customer density, and vehicle choice are included.

The results show a stable relationship between monetary cost and kilograms of CO2, with each kilogram of CO2 associated with a $3.50 increase in cost, illustrating the influence of fuel use on both cost and emissions. In addition, customer density and time window length are strongly correlated with monetary cost and kilograms of CO2 per order. The addition of 80 customers or extending the time window 100 minutes would save approximately $3.50 and 1 kilogram of CO2 per order. Lastly, the evaluation of four different fleets illustrates significant environmental and monetary gains can be achieved through the use of hybrid vehicles.

Authors: Erica Wygonik

Recommended Citation:
Wygonik, Erica and Anne V. Goodchild. “Using a GIS-based emissions minimization vehicle routing problem with time windows (EVRPTW) model to evaluate emissions and cost trade-offs in a case study of an urban delivery system.” Proc., 90th Annual Meeting of the Transportation Research Board, Transportation Research Board, Washington, DC.

Student Thesis and Dissertations

Emissions, Cost, and Customer Service Trade-off Analyses in Pickup and Delivery Systems

URL: https://orbiscascade-washington.primo.exlibrisgroup.com/permalink/01ALLIANCE_UW/1juclfo/alma99149478340001452

Publication Date: 2011

Summary:

As commercial vehicle activity grows, the environmental impacts of these movements have increasing negative effects, particularly in urban areas. The transportation sector is the largest producer of CO2 emissions in the United States, by end-use sector, accounting for 32% of CO2 emissions from fossil fuel combustion in 2008. Medium and heavy-duty trucks account for close to 22% of CO2 emissions within the transportation sector, making systems using these vehicles key contributors to air quality problems. An important well-known type of such systems is the “pickup and delivery” in which a fleet of vehicles pickups and/or delivers goods from customers.

Companies operating fleet of vehicles reduce their cost by efficiently designing the routes their vehicles follow and the schedules at which customers will be visited. This principle especially applies to pickup and delivery systems. Customers are spread out in urban regions or are located in different states which makes it critical to efficiently design the routes and schedules vehicles will follow. So far, a less costly operation has been the main focus of these companies, particularly pickup and delivery systems, and less attention has been paid to understand how cost and emissions relate and how to directly reduce the environmental impacts of their transportation activities. This is the research opportunity that motivates the present study.

While emissions from transportation activities are mostly understood broadly, this research looks carefully at relationships between cost, emissions and service quality at an individual-fleet level. This approach enables evaluation of the impact of a variety of internal changes and external policies based on different time window schemes, exposure to congestion, or impact of CO2 taxation. It this makes it possible to obtain particular and valuable insights from the changes in the relationship between cost, emissions and service quality for different fleet characteristics.

In an effort to apply the above approach to real fleets, two different case studies are approached and presented in this thesis. Each of these cases has significant differences in their fleet composition, customers’ requirements and operational features that provide this research with the opportunity to explore different scenarios.

Three research questions guide this research. They are explained in more detailed below. The present study does not seek to provide a conclusive answer for each of the research questions but does shed light on general insights and relationships for each of the different features presented in the road network, fleet composition, and customer features.

In summary, this research provides a better understanding of the relationships between fleet operating costs, emissions reductions and impacts on customer service. The insights are useful for companies trying to develop effective emission-reduction strategies. Additionally, public agencies can use these results to develop emissions reductions policies.

Authors: Felipe Sandoval

Recommended Citation:
Sandoval, Felipe (2011). Emissions, Cost, and Customer Service Trade-off Analyses in Pickup and Delivery Systems, University of Washington Master's Degree Thesis.

Thesis: Array

Student Thesis and Dissertations

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

URL: https://digital.lib.washington.edu/researchworks/handle/1773/27219

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

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

Download PDF (2.21 MB)

URL: https://trid.trb.org/view.aspx?id=1334572

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.

Paper

Evaluation of Emissions Reduction in Urban Pickup Systems Heterogeneous Fleet Case Study

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URL: https://doi.org/10.3141/2224-02

Publication: Transportation Research Record: Journal of the Transportation Research Board

Volume: 2224

Pages: 8-16

Publication Date: 2011

Summary:

A case study of the University of Washington Mailing Services, which operates a heterogeneous fleet of vehicles, provides insight into the impact of operational changes on cost, service quality, and emissions. An emissions minimization problem was formulated and solutions were identified with a creation and local search algorithm based on the I1 and 2-opts heuristics.

The algorithm could be used to find many solutions that could improve existing routing on both cost and emissions metrics, reduce emissions by an average of almost 6%, and reduce costs by an average of 9%. More significant cost and emissions savings could be found with service quality reductions. For example, reducing delivery frequency to once a day could lead to emissions and cost savings of close to 35% and 3%, respectively.

Rules of thumb for vehicle assignment within heterogeneous fleets were explored to gain an understanding of simple implementations, such as assigning cleaner vehicles to routes with more customers and longer travel distances.

This case study identified significant emissions reductions that could be obtained with minimal effects on cost and service and that offered new, practical applications that could be used by fleet managers interested in reducing their carbon footprint.

Authors: Dr. Anne Goodchild, Kelly Pitera, Felipe Sandoval

Recommended Citation:
Pitera, Kelly, Felipe Sandoval, and Anne Goodchild. "Evaluation of Emissions Reduction in Urban Pickup Systems: Heterogeneous Fleet Case Study." Transportation Research Record 2224, no. 1 (2011): 8-16.

Biking for Goods: A Case Study on the Seattle Pedaling Relief Project

1. Introduction
One of the disruptions brought by the COVID-19 pandemic was the reduction of in-store shopping, and the consequent increase in online shopping and home deliveries. However, not everyone had equal access to online shopping and home-delivery services. Customers relying on food banks were forced to shop in-store even during the pandemic. In 2020, the Cascade Bicycle Club started the Pedaling Relief Project (PRP) – a not-for-profit home delivery service run by volunteers using bikes to pick up food at food banks and deliver to food bank customers, among other services.

The Urban Freight Lab collaborates with the Cascade Bicycle Club (CBC) to study and improve PRP operations. For this work, students in Prof. Anne Goodchild’s Transportation Engineering course on Transportation Logistics (CET 587) are undertaking a case study: to analyze the transport and logistics system of the Pedaling Relief Project and provide recommendations for how to improve operations.

2. Background
2.1. Food rescue at a glance
An estimated 94,500 tons of food from Seattle business establishments end up in compost and landfills each year, while many members of our community remain food insecure. The process of food rescuing consists of the gleaning of edible food from business establishments – called donor businesses such as grocery stores, restaurants, and commissary kitchens – that otherwise would enter the waste stream and be re-distributed to local food programs. Hunger relief agencies, also referred to as food banks, are non-profit organizations that collect rescued food, either directly from businesses or through food rescue distributors (such as Food Lifeline or Northeast Harvest) and re-distribute it to the community through meal programs, walk-ins, and pop-up food pantries, student backpack programs, among others.

Read more about the Seattle food rescue system in SCTL’s report (2020) on “Improving Food Rescue in Seattle: What Can Be Learned from a Supply Chain View?”

2.2. Pedaling Relief Project
In 2020 the Cascade Bicycle Club started the Pedaling Relief Project (PRP), a volunteer-based program that collaborates with local food banks to offer three main types of services — (1) grocery delivery, (2) food rescue, (3) little free pantry restocking — coordinating a network of volunteers on bikes.

Grocery delivery (GD) service consists of picking up grocery bags from food banks and performing delivery routes, distributing food to food bank customers that asked for home delivery services.
Food rescue (FR) services support the existing distributors by picking up food at business establishments and carrying rescued food to local food banks.
Little free pantries restocking (LFPR) services consist of picking up food at local food banks and carrying it to neighborhood micro pantries –containers placed on local streets and open to everyone to store food from donors to whoever needs it. Learn more about the Little free pantries project on thelittlefreepantries.org.

Volunteers use their own bikes, with some cargo carry capacity, or can request a bike trailer or cargo bike from the Cascade Bicycle Club.

2.3. Cargo Bikes
Cargo bikes are two/three/four-wheel bikes with some cargo-carrying capacity. They are increasingly used as an alternative mode to trucks and vans to transport goods in urban areas. Cargo bikes are often supported by an electric motor that assists the driver when pedaling. Compared to internal combustion engine vehicles, cargo bikes do not produce tailpipe emissions and they consume less energy than electric vans (Verlinghieri et al., 2021). They also offer several operational advantages: they are more agile in navigating urban road traffic, they can use alternative road infrastructure such as bike lanes and sidewalks to drive and park, they can park closer to their delivery destination, reducing walking distances and parking dwell times (Dalla Chiara et al., 2020).

3. Project instructions

The CBC provided access to anonymous data on the PRP operations for the exclusive use of the 2022 CET 587 course student cohort final projects. Students are asked to individually perform empirical research using the provided data and/or self-collected data on the PRP operations with the following objectives:

Empirically analyze and describe PRP operations.
Provide recommendations on what actions can be taken to improve PRP operations.

Projects will meet the following two requirements:

Use the provided data and/or self-collected and/or publicly sourced data to perform empirical analysis
Provide justified and concrete recommendations on how to improve the PRP.
Complete deliverables 1 and 2 (see below), which consist of 2 presentations, a project proposal, and a final project report.

Project progress timeline and deliverables:

Weeks	Progress & Deliverables
1-2	Become familiar with R language programming; PRP background and data
3	CBC gives a guest lecture about PRP
4-5	Project proposal; 2-minute lightning talk about the project proposal Deliverable 1: 1-page project proposal
6-10	Implement proposed methodology and perform research
11	Each student will give a 15-minute presentation of the main results of the project Deliverable 2: Final report

The following are potential project directions:

Analyze current routes performed by volunteers. How can they be improved? Get the work done more quickly, or with fewer bikes?
Analyze data from little free pantries restocking. Collect additional data on the use of Little Free Pantries by manual observations or by installing sensors in a few of them. Can we model demand and supply for food donations?
Collect and analyze GPS data by signing up and performing some of the PRP routes yourself. What type of infrastructure do cargo bikes need and how does street and curb use behavior differ between cargo bikes and vans? What can the city do to better support this type of activity?
Analyze volunteers’ behaviors data. Is it possible to model the supply of volunteers? Can you simulate different scenarios of volunteer supply?
Develop your own direction with approval.

Students will be provided with a base dataset on PRP operations. Students are encouraged to use other datasets self-collected or from public data sources (e.g. check out the SDOT Open Data Portal), to share ideas in class and among each other, to use as much as possible class time, guest lectures and office hours to ask questions and share ideas.

1: 1-page project proposal and 2-minute lightning talk describing motivation, project objective(s) and research question(s), proposed methodology (data to use/collect, methods to implement), and expected results.

2: Final report and 10-minute presentation describing data used, including sample size and sample statistics, how data collection was performed, empirical analysis performed using data and results from the analysis, and conclusions, key findings, and key recommendations.

Roadblocks to Sustainable Urban Freight

While freight transportation is a necessary activity to sustain cities’ social and economic life, enabling the movement and deployment of goods and services in and between urbanized areas, it also accounts for a significant portion of greenhouse gas (GHG) emissions, and therefore it is a major contributor to climate change. Guaranteeing an efficient and sustainable urban freight transport ecosystem is necessary for cities to survive and tackle the climate emergency.

Several stakeholders in the private and public sectors are currently taking action and drafting roadmaps to achieve such goals. However, as the urban freight ecosystem is a complex network of stakeholders, achieving such sustainability goals requires collaboration and coordination between multiple agents.

The project will collect and synthesize expert views from both the private and public sectors on what is needed to sustainably deliver the last mile and aims at identifying the roadblocks towards this goal. All types of goods and services will be considered, with the end goal of raising the entire industry’s understanding of the barriers to achieving sustainable urban freight.

Approach

Task 1: Research Scan (September-November 2020) Subtasks:

identify an accepted and shared definition of sustainable urban freight;
identify and classify the main agents of the urban freight system from both the private and public sectors and their main role in the last-mile ecosystem;
identify and classify the main accepted strategies currently adopted towards sustainability.

The research team will also define the boundaries of the study, including the geographical region of concentration.

Task 2: Private sector expert interviews (December 2020-April 2021)

The main private sector agents identified in Task 1 will include vehicle manufacturers, retailers, carriers and more. The research team will identify and reach out to representatives of at least 15 companies. Participants will be interviewed using an open question format and will have an optional follow-up online survey. The objectives of the interviews and surveys are:

listing the current strategies adopted to reach sustainable urban freight;
understanding what the impacts are of other private and public sectors agents’ decisions on their sustainability strategies;
identifying agents’ needs and obstacles to achieve their stated sustainable goals.

Task 3: Public sector expert interviews (December 2020-April 2021)

The research team will identify different urban typologies, classifying cities into homogeneous groups according to economic, demographic, urban form, mobility and sustainability indicators. The typologies will be used to sample cities from each identified urban typology.

The team will then reach out to representatives from the public sector agents from the sampled cities, including regulators, planners and public utility representatives, and perform a combination of online survey and online/phone interviews. At least 15 representatives from public sector agents will be contacted. The objectives of the interviews are:

listing the current policies adopted by cities towards sustainable urban freight, including infrastructure investments and transport demand management;
understanding what the obstacles are to achieve sustainability goals.

Task 4: Synthesizing research and identifying roadblocks (May-June 2021)

Synthesizing the work of the previous 3 tasks, and applying the research team’s own expertise, this task will identify the key obstacles to sustainable urban freight. Through a review of existing writings, discussions with experts, and their own domain expertise, the research team will identify the obstacles in the areas of transportation technology, infrastructure, and policy. This review will consider the obstacles in public sector, barriers to private business decision making, and where the two sectors need to take a collaborative approach. The results obtained in the study will be made available publicly as a white paper or submitted for scientific journal publication.

UPS E-Bike Delivery Pilot Test in Seattle: Analysis of Public Benefits and Costs (Task Order 6)

The City of Seattle granted a permit to United Parcel Service, Inc. (UPS) in fall 2018 to pilot test a new e-bike parcel delivery system in the Pioneer Square/Belltown area for one year. The Seattle Department of Transportation (SDOT) commissioned the Urban Freight Lab (UFL) to quantify and document the public impacts of this multimodal delivery system change in the final 50 feet of supply chains, to provide data and evidence for development of future urban freight policies.

The UFL will conduct analyses into the following research questions:

What are the total changes in VMT and emissions (PM and GHG) to all three affected cargo van routes due to the e-bike pilot test in the Pike Place Market and neighboring areas?
What is the change in the delivery van’s dwell time, e.g. the amount of time the van is parked, before and after introducing the e-bike?
How does the e-bike system affect UPS’ failed first delivery (FFD) attempt rate along the route?
If UPS begins to stage drop boxes along the route for the e-bike (instead of having to replenish from the parked trailer) what are the impacts to total VMT and emissions?
How do e-bike delivery operations impact pedestrian, other bike, and motor traffic?

Common Microhub (Seattle Neighborhood Delivery Hub)

Background

The importance of efficient urban logistics has never been greater. The response to COVID-19 has put new constraints and demands on the urban freight system but also highlighted the essential and critical nature of delivery and distribution. New requirements for reducing human contact only add weight to many of the strategies such as neighborhood kitchens, locker deliveries, and autonomous driverless delivery vehicles, already envisioned before the coronavirus pandemic. Social distancing and virus vector management also add new requirements and metrics for evaluating and managing logistics that are catalyzing innovation and motivating change in the urban logistics space.

What is a Common Microhub?

Also known as an urban consolidation center or a delivery transfer point, a microhub is a central drop-off/pick-up location for goods and services, which can be used by multiple delivery providers, retailers, and consumers. Microhubs can reduce energy consumption, noise pollution, congestion, and cost, and increase access, sustainability, and livability in cities, by allowing the final mile of delivery to be shifted to low-emission vehicles or soft transportation modes (cargo bike or walking), In addition to allowing for consolidation or deconsolidation of shipments, the design also enables neighbors to engage with additional services.

Microhubs provide:

access points for shared mobility
touchless pick-up and drop-off points
a home base for zero-emissions last-mile delivery, autonomous, and modalities
a shared public space
charging infrastructure
increased delivery density, reducing traffic and delivery vehicle dwell time
trip chaining capability

Urban Freight Lab’s Common Microhub Pilot: The Seattle Neighborhood Delivery Hub

The Urban Freight Lab’s Common Microhub project—the Seattle Neighborhood Delivery Hub—provides an opportunity for members to test and evaluate urban logistics strategies on the ground in Seattle’s Uptown neighborhood. As third-party logistics companies entering the last-mile space and more cities committing to environmental focus and zero-emissions vision, the interest in creating logistics places in urban proximity is growing. The outcomes of this research can guide the development of future microhub implementations in other cities. Participating stakeholders, while collaborative, operate with relative independence within the hub space. Data collection and analysis are ongoing; key indicators being measured include both operator performance and expected local impacts. In addition, lessons learned are encountered continuously and shared with UFL members as the project progresses.

Participants and Products

	Product: Common Carrier Parcel Lockers Host: Urban Freight LabDescription: The Urban Freight Lab is operating a common carrier parcel locker — a secure, automated, self-service storage system designed to accommodate deliveries from multiple transportation providers delivering a range of parcel sizes and open to all neighbors and commuters. Such lockers create delivery density, enabling vehicles to transport many packages to a single stop, rather than making multiple trips to accomplish the same task. This new approach reduces dwell time and failed first deliveries, both of which produce congestion and emissions, and increase costs. During the COVID-19 pandemic, the lockers also provide a no-contact solution for customers.
	Product: Neighborhood Kitchen and Infrastructure Host: REEF Description: Neighborhood kitchens are non-customer-facing modular vessels where food is prepared for mobile app or delivery orders. Removing front-of-house operations reduces a restaurant’s footprint, increases sustainability, and gives food entrepreneurs a platform by reducing overhead costs. REEF is also the infrastructure partner, leveraging their parking lot holdings for the Seattle Neighborhood Delivery Hub location.
	Product: Electric-Assist Cargo Bike Fleet Host: Coaster Cycles Description: Montana-based Coaster Cycles is providing an electric-assist cargo trikes fleet. These trikes are customized to carry BrightDrop EP1s, providing an agile, sustainable last-mile delivery solution in dense urban areas, reducing the emissions, congestion, and noise produced by traditional truck delivery. (Watch the Coaster Cycle / EP1 deployment: https://vimeo.com/528552173)
	Product: Last-Mile Delivery Routing Software Host: AxleHire Description: Berkeley-based logistics startup Axlehire provides last-mile delivery routing software that creates the fastest, most efficient routes possible. AxleHire is using the Seattle Neighborhood Delivery Hub site as a transshipment point, where trucks will transfer packages transported from a suburban depot to smaller, more nimble Coaster Cycle electrically-assisted bicycles, which are driven by Axlehire operators to a final customer.
	Product: Electric Pallet (EP1) Host: BrightDrop (General Motors) Description: BrightDrop (a subsidiary of General Motors) focuses on electrifying and improving the delivery of goods and services. BrightDrop’s first product to market is the EP1, a propulsion-assisted electric pallet designed to easily move goods over short distances. Because the pallet is electric-powered, it supports sustainability efforts, improves driver safety and freight security, lowers labor costs, and reduces errors and package touches.
	Product: MUST Devices and Data Collection Host: University of Washington Smart Transportation Application & Research (STAR) Lab Description: To assess performance, researchers have deployed a multitude of sensors, including STAR Lab’s Mobile Unit for Sensing Traffic (MUST) sensors, cameras with vehicle recognition technology, GPS tracking sensors, and parking occupancy sensors. Researchers can gain a comprehensive understanding of delivery operations (such as miles traveled, infrastructure usage, speed, battery usage, interaction with other vehicles, bikes, and pedestrians) and activities at the site itself (such as parking occupancy, duration and, mode distribution of vehicle types at the site).

Location

The Seattle Neighborhood Delivery Hub is located at 130 5th Ave. N. in Seattle’s Uptown neighborhood.

Goals

The goals of the Common Microhub Research Project are to:

1. Conduct a research scan of published reports that provide data-based evidence of the results of projects that have elements that are similar to Common Microhubs.
2. Identify and characterize informal microhub activities observed in cities worldwide.
3. Solicit input from UFL members as to the perceived benefits of microhubs and the desired physical characteristics of a microhub
4. Compare and contrast the priorities of UFL members with established metrics in the literature.
5. Seek agreement from UFL members as to the microhub characteristics and location that would be feasible and desirable to operate in the Seattle region. Priority will be given to current UFL members, but should a third party external to UFL be necessary to run the microhub, proposals to host the microhub would be sought.
6. Collect and analyze field data to measure both operator performance (including VMT, parking demand, fuel, and energy consumption) and expected local impacts (including travel and parking activity) before and after implementation. Data collection will rely on VMT, GPS, and travel time sources where available, but we expect to develop and implement customized methods to collect additional traffic and travel time data as needed. We may also interview the microhub operator and users to obtain qualitative data on the operations. The following tasks will be completed by the Urban Freight Lab in the two-year project.

Project Tasks

The following tasks will be completed by the Urban Freight Lab in the two-year project.

Task 1: Research Scan

Subtasks:

Conduct a research scan of published reports that provide data-based evidence of the results of projects that have elements that are similar to Common MicroHubs.
Identify and characterize informal microhub activities observed in cities worldwide.
Write a summary of the results.

Task 2: Develop MicroHub Priorities

Subtasks:

Solicit input from UFL members as to:
- the perceived benefits of microhubs
- the desired physical characteristics of a microhub
Compare and contrast the priorities of UFL members with priorities demonstrated in the literature.

Task 3: Select Operator and Define Operational Model

Subtasks:

With the help of a microhub operator, seek agreement from UFL members as to the microhub characteristics, services, operational goals and location that would be feasible and desirable to operate in the Seattle region.
- Priority will be given to current UFL members to operate the Hub, but should a third party external to UFL be necessary to run the microhub, proposals to host the microhub would be sought.
Go/No Go decision by researchers, UFL members, and microhub operator as to whether a pilot test will move forward.
- Sufficient interest amongst participating UFL members and an understanding of the operating model and participants’ business objectives will be necessary to move forward as per the operator’s approval.
- The operator will work independently with participants and/or the University of Washington to establish operating model(s) under separate agreement(s).

Task 4: Select Operator and Define Operational Model

Subtasks:

Define key metrics for evaluation and data collection plan.
With the support of UFL members participating in the pilot, collect “before” data to contrast with data collected during pilot operations.

Task 5: Implementation

Subtasks:

Support the implementation of a microhub with UFL partners that have agreed to the terms of the pilot.
Project schedule will allow for 6 months of operations, followed by 3 months for analysis.
Collect and analyze field data to measure both operator performance (including VMT, parking demand, fuel, and energy consumption) and expected local impacts (including travel and parking activity) after implementation. Data collection will rely on VMT, GPS, and travel time sources where available, but we expect to develop and implement customized methods to collect additional traffic and travel time data as needed. We may also interview the operator and users to obtain qualitative data on the operations.

Task 6: Evaluate Operations

Subtasks:

Provide progress reports at quarterly UFL meetings.
Final report with key project findings.