Blog

Goods Movement 2030: What Have We Done and What is Next?

URL: https://www.goodsmovement2030.com/post/goods-movement-2030-so-what-have-we-done-here-and-whats-next

Publication: Goods Movement 2030: An Urban Freight Blog

Publication Date: 2023

Summary:

A year and a half ago, our members decided to dig into four topics for the Goods Movement 2030 project (Electrification, Digital Transformation, Planning Streets for People and Goods, and Microfreight). They all — public and private sector alike — saw these areas as transformative. And they identified six priorities around which we hope to see improved outcomes for 2030 (Reducing CO2 Emissions, Reducing Congestion, Reducing Roadway Fatalities, Increasing and Improving Protected Spaces for Vulnerable Users, Making Transparent the Cost of Delivery, and Improving Equity).

From myriad lively discussions, debates, and expert-led learning over the last 18 months, this much is clear: Each of the four topics we’ve explored together cries out for deep and broad collaboration between the public and private sectors if we’re going to move the needle on our consensus priorities.

And the good news? Our members have already shown that they’re willing and able to approach that needed collaboration with curious minds and radical transparency (not to mention their demonstrated commitment to innovating and having tough conversations.) All of this bodes well for both the present — and the future we’ve all been working to imagine and shape.

While all six priorities surfaced throughout this project, it’s decarbonization that came up in virtually every discussion on every topic. On equity, we had to grapple early on with what that even means in urban freight.

This blog presents a Cliffs Notes recap of big-picture project takeaways.

Authors: Urban Freight Lab

Recommended Citation:
“Goods Movement 2030: What Have We Done and What Is Next?” Goods Movement 2030 (blog). Urban Freight Lab, October 24, 2023. https://www.goodsmovement2030.com/post/goods-movement-2030-so-what-have-we-done-here-and-whats-next.

White Paper

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

Download PDF (1.79 MB)

URL: https://doi.org/10.6069/REXD-W642

Publication Date: 2023

Summary:

The distribution of goods and services in North American cities has conventionally relied on diesel-powered internal combustion engine (ICE) vehicles. Recent developments in electromobility have provided an opportunity to reduce some of the negative externalities generated by urban logistics systems.

Cargo e-bikes — electric cycles specially designed for cargo transportation — represent an alternative environmentally friendly and safer mode for delivering goods and services in urban areas. However, lack of infrastructure, legal uncertainties, and a cultural and economic attachment to motorized vehicles has hindered their adoption. Cities play a crucial role in reducing these barriers and creating a leveled playing field where cargo e-bikes can be essential to urban logistics systems.

This paper aims to inform urban planners about what cargo e-bikes are, how they have been successfully deployed in North America to replace ICE vehicles, and identify actionable strategies cities can take to encourage their adoption while guaranteeing safety for all road users.

Gathering data and opinions from key public and private sector stakeholders and building on the expertise of the Urban Freight Lab, this paper identifies nine recommendations and 21 actions for urban planners across the following four main thematic areas:

Infrastructure: cycling, parking infrastructure, and urban logistics hubs
Policy and Regulation: e-bike law, safety regulation, and policies de-prioritizing vehicles
Incentives: rebates and business subsidies
Culture and Education: labor force training, educational programs, and community-driven adoption

Acknowledgements

The Urban Freight Lab acknowledges the following co-sponsors for financially supporting this research: Bosch eBike Systems, Fleet Cycles, Gazelle USA, Michelin North America, Inc., Net Zero Logistics, Pacific Northwest Transportation Consortium (PacTrans) Region 10, Seattle Department of Transportation, and Urban Arrow.

Technical contributions and guidance: Amazon, B-Line (Franklin Jones), Cascade Bicycle Club, Coaster Cycles, City of Boston, City of Portland, Downtown Seattle Business Association (Steve Walls), New York City Department of Transportation, People for Bikes (Ash Lovell), Portland Bureau of Transportation, University of Washington Mailing Services (Douglas Stevens), UPS,

Authors: Dr. Giacomo Dalla ChiaraRishi VermaKelly RulaDr. Anne Goodchild

Recommended Citation:
Dalla Chiara, G., Verma, R., Rula, K., Goodchild, A. (2023). Biking the Goods: How North American Cities Can Prepare for and Promote Large-Scale Adoption of Cargo e-Bikes. Urban Freight Lab, University of Washington.

Chapter

Overview on Stakeholder Engagement

URL: https://doi.org/10.4337/9781800370173.00026

Publication: Handbook on City Logistics and Urban Freight

Publication Date: 2023

Summary:

Until recently, urban transport authorities often overlooked freight, concentrating their attention on the movement of people. Even when motivated to tackle urban freight, many city authorities find it difficult to mobilize their own resources, and address the complex set of differing views of a large variety of stakeholders.

Historically, the role of city authorities, or local authorities within cities, has been confined largely to one of regulation as opposed to collaborative planning. Correspondingly, until recently there has been limited engagement of private companies in the local-authority transport-planning process.

Engaging stakeholders is very important as without their involvement it is very difficult to motivate changes in the urban freight and logistics system or design policies that might be mutually beneficial; successful implementation of effective urban logistics initiatives demands a solid understanding of both freight activity and the supply chains serving the urban area.

This chapter examines these issues and addresses how cities can more effectively engage with stakeholders. There is a strong need to identify obstacles, propose solutions and define implementation paths that consider the concerns of all stakeholders involved. This sounds rather straightforward but in practice there are many conflicts among and within public and private-interest groups and these often result in obstacles to success.

This chapter will address the range of complex issues involved and establish a framework for understanding the options related to stakeholder engagement to improve urban freight sustainability.

Authors: Dr. Anne Goodchild, Michael Browne (University of Gothenburg)

Recommended Citation:
Michael Browne & Anne Goodchild, 2023. "Overview on stakeholder engagement," Chapter in: Edoardo Marcucci & Valerio Gatta & Michela Le Pira (ed.), Handbook on City Logistics and Urban Freight, chapter 15, pages 311-326, Edward Elgar Publishing.

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?

Technical Report

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

Download PDF (2.46 MB)

Publication: U.S. Department of Energy

Publication Date: 2021

Summary:

The objectives of this project are to develop and implement a technology solution to support research, development, and demonstration of data processing techniques, models, simulations, a smart phone application, and a visual-confirmation system to:

Reduce delivery vehicle parking seeking behavior by approximately 20% in the pilot test area, by returning current and predicted load/unload space occupancy information to users on a web-based and/or mobile platform, to inform real-time parking decisions
Reduce parcel truck dwell time in pilot test areas in Seattle and Bellevue, Washington, by approximately 30%, thereby increasing productivity of load/unload spaces near common carrier locker systems, and
Improve the transportation network (which includes roads, intersections, warehouses, fulfillment centers, etc.) and commercial firms’ efficiency by increasing curb occupancy rates to roughly 80%, and alley space occupancy rates from 46% to 60% during peak hours, and increasing private loading bay occupancy rates in the afternoon peak times, in the pilot test area.

The project team has designed a 3-year plan to achieve the objectives of this project.

In Year 1, the team developed integrated technologies and finalized the pilot test parameters. This involved finalizing the plan for placing sensory devices and common parcel locker systems on public and private property; issuing the request for proposals; selecting vendors; and gaining approvals necessary to execute the plan. The team also developed techniques to preprocess the data streams from the sensor devices, and began to design the prototype smart phone parking app to display real-time load/unload space availability, as well as the truck load/unload space behavior model.

In Year 2, the team executed the implementation plan:

oversaw installation of the in-road sensors, and collecting and processing data,
managed installation, marketing and operations of three common locker systems in the pilot test area,
tested the prototype smart phone parking app with initial data stream, and
developed a truck parking behavior simulation model.

Authors: Urban Freight Lab

Recommended Citation:
Urban Freight Lab (2021). Year Two Progress Report: Technology Integration to Gain Commercial Efficiency for the Urban Goods Delivery System.

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.

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.

Paper

Empirical Analysis of Relieving High-Speed Rail Freight Congestion in China

Download PDF (0.94 MB)

URL: https://doi.org/10.3390/su12239918

Publication: Sustainability

Volume: 12(23)

Publication Date: 2020

Summary:

This paper discusses how to promote high-speed rail (HSR) freight business by solving the congestion problem. First, we define the existing operation modes in China and propose the idea of relieving congestion by reserving more carriages of HSR passenger trains for freight between cities with large potential volume or small capacity. Second, we take one HSR corridor as a case to study, and use predictive regression and integrated time series methods to forecast the growth of HSR freight volume along the corridor. Finally, combined with forecast results and available capacity during the peak month of 2018, we offer suggestions on the mode adoption in each segment during the peak month from 2019 to 2022. Results demonstrate: (1) Among all 84 Origin-Destination (OD) city flows, the percentage of those monthly volumes over 1 ton increases from 17.9% in 2018 to 84.6% in 2022, and those over 30 tons rise from 3.6% to 26.2%. (2) Among the segments between seven main cities in the HSR corridor, T-J should be given priority to operate trains with reserved mode; the segment between X and J deserves to reserve most carriages during the peak month in the future. Specifically, our model suggests reserving 5.3–10.1 carriages/day for J-X, and 4.8–16.3 carriages/day for X-J during the peak month from 2019 to 2022.

Authors: Hanlin GaoDr. Anne Goodchild, Meiqing Zhang

Recommended Citation:
Hanlin Gao, Meiqing Zhang, & Anne Goodchild. (2020). Empirical Analysis of Relieving High-Speed Rail Freight Congestion in China. Sustainability (Basel, Switzerland), 12(23). https://doi.org/10.3390/su12239918

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

The Urban Freight Lab (UFL) received $1.5 million in funding from the U.S. Department of Energy to help goods delivery drivers find a place to park without driving around the block in crowded cities for hours, wasting time and fuel and adding to congestion. The project partners will integrate sensor technologies, develop data platforms to process large data streams, and publish a prototype app to let delivery drivers 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.

The UFL will also pilot test common carrier locker systems in public and private load/unload spaces near transit stops. Transit riders, downtown workers, and residents will be able to pick up packages they ordered online from any retailer in a convenient and secure locker in a public plaza or outside their office. The benefits don’t stop there. Common carrier lockers create delivery density that increases the productivity of parking spaces and provides significant commercial efficiencies. They do this by reducing the amount of time it takes delivery people to complete their work. The driver parks next to the locker system, loads packages into it, and returns to the truck. When delivery people spend less time going door-to-door, it decreases the time their truck needs to be parked, increasing turnover and adding parking capacity in crowded cities.

This is a timely project as cities are looking for new strategies to accommodate the rapid growth of e-commerce. Online shopping has grown by 15% annually for the past 11 years, and is now 9% of total retail sales in the U.S., with $453.5 billion in revenue in 2017. Many online shoppers want the goods delivery system to bring them whatever they want, where they want it, in one to two hours. At the same time, many cities are replacing goods delivery load/unload spaces with transit and bike lanes. Cities need new load/unload space concepts supported by technology to make the leap to autonomous cars and trucks in the street, and autonomous freight vehicles in the Final 50 Feet of the goods delivery system. The Final 50 feet segment starts when a truck parks in a load/unload space, and includes delivery persons’ activities as they maneuver goods along sidewalks and into urban towers to make their deliveries.

The goals of this project are to:

Reduce parking seeking behavior by 20% in the pilot test area by returning current and predicted load/unload space occupancy information to users on a web-based and/or mobile platform to inform real-time parking decisions.
Reduce parcel truck dwell time in pilot test area locations by 30%, thereby increasing productivity of load/unload spaces near common carrier locker systems.
Increase network and commercial firms’ efficiency by increasing curb and alley space occupancy rates, and underutilized private loading bay occupancy in the p.m. peak, in the pilot test area.

Cost-share partnering organizations are:

Seattle Department of Transportation
Bellevue Department of Transportation
CBRE Seattle
King County Metro Transit
Kroger Company
Puget Sound Clean Air Agency
Sound Transit

Members of the UFL are also participating in the project. Pacific National National Laboratory (PNNL) is a partner, completing several of the project tasks.

Report

Cargo E-Bike Delivery Pilot Test in Seattle

Download PDF (2.98 MB)

Publication Date: 2020

Summary:

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

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

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

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

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

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

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

Authors: Urban Freight Lab

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