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Zero-Emission Zones: Turning Ideas into Action

C40 Cities, a consortium of cities worldwide with the collective goal of reducing greenhouse gas emissions, introduced an initiative in 2017 to create “Zero Emission Areas.” These areas, or zones, would be closed off to fossil fuel-burning vehicles and serve as a testbed for scaling up zero-emission regulation. Seattle, along with U.S. counterparts Austin, Texas and Los Angeles, CA, is a signatory to the Zero Emission Area Programme and as such, is obligated to create such an area by 2030.

Zero Emission Zones (ZEZ) can introduce obstacles to the urban freight and logistics industry. Though large delivery companies like Amazon, UPS, and FedEx are introducing electric vehicles (EVs), parcel and package delivery are not the only service included in the complex sector of urban freight. EVs are not yet widely available on the market and the high capital costs of introducing EVs into a company’s fleet can act as a barrier. However, there are strategies being tested and explored to reduce emissions including but not limited to zero emission curb zones, parcel lockers, e-cargo bikes, pricing strategies at the curb and at the point of sale (e.g. taxes and fees), consolidation centers, and other strategies. Additionally, many of these zones are being envisioned in areas with a focus on improving equity outcomes and across neighborhoods of different characteristics. However, no guidance exists for cities about how to approach the selection of these areas or tactics co-developed with the private sector.

Research Objectives

  • Develop a framework for evaluating geographic locations, existing policy tools, and key learning objectives or measures of success based on two different neighborhood typologies
  • Incorporate private sector stakeholders into the design process


  • Task 1: Define the characteristics and goals of a zero-emission delivery zone
  • Task 2: Perform literature and policy scan on existing tools to push deliveries towards zero emission (industry and consumer-side)
  • Task 3: Identify 2 different neighborhood typologies in Seattle for analysis and define the study area boundaries
    • One neighborhood should meet existing definitions of a Justice 40 or equity focus area community as defined by City of Seattle (e.g. Georgetown)
    • One neighborhood should represent high-density demand for e-commerce and congestion (define?) (e.g. Capital Hill, South Lake Union)
  • Task 4: Collect publicly-available baseline data on neighborhood characteristics collect data (land use, types of businesses, demographics of residents)
  • Task 5: Develop potential scenarios, tactics, and metrics that reflect the unique characteristics of the chosen neighborhoods/typologies
    • The team will leverage existing relationships to perform private sector outreach, based on interviews: understand their priorities, reactions to scenarios under development.
  • Task 6: Recommendations and framework
    • How do you choose the site / site selection criteria and methodology
    • Tactics based on neighborhood typology characteristics- using policies available right now or with limited policy effort
    • Equity-Community metrics- How does the makeup of the zone/neighborhood impact tactics + metrics?
    • Key metrics- What are you trying to test and how will you measure?
    • Tools to accelerate the implementation of zero-emission deliveries.


Create a framework for zero emission zone design and case study of two different neighborhoods in Seattle.


Developing Better Curb Management Strategies through Understanding Commercial Vehicle Driver Parking Behavior in a Simulated Environment

Publication: Harvard Dataverse
Publication Date: 2023

Three different data types were obtained from Oregon State Driving and Bicycling Simulator Laboratory for purpose of this report and they are as follow:

  1. Speed data consists of subject number, average speed, minimum speed, and all the independent variables. Speed data were collected based on the truck’s speed while driving through a certain scenario (out of 24). For each scenario, the average and minimum speed (mph) of 12 drivers were recorded along each segment (scenario) from the start of the road to 150 feet before the intersection (traffic signals).
  2. Eye tracking data consists of subject number, total fixation duration (TFD) in milliseconds, area of interest (AOI), and all the independent variables. TFD data were collected while the truck driver maneuvers through a certain scenario (out of 24). For each scenario, the TFD for each AOI was recorded for 11 subjects along each segment (scenario) from the start of the road to 150 feet before the intersection (traffic signals). AOI represent the area of interest that a driver fixates for a certain of time to generate the total fixation duration.
  3. Eye tracking data consists of subject number, GSR in peaks per minute, and all the independent variables. GSR data were collected while the truck driver maneuvers through a certain scenario (1 out of 24). For each scenario, the peaks per minute data was recorded for 11 subjects along each segment (scenario) from the start of the road to 150 feet before the intersection (traffic signals). Peaks per minute represents the emotional arousal (i.e., something is scary, threating, joyful, etc.) that a driver generates when reacting to a particular event. Fourteen participants were recruited, two of them had a simulator sickness so they were excluded from the data and the analysis. While there are no quality or consistency issues with this data set, it should be noted that the sample is on the smaller side and that should be considered when interpreting derived results. The average values were calculated to apply robust statistical analysis for such data (speed and lateral position). As the experiment consists of 2x2x2x3 factorial design, each participant had to driver through 24 scenarios; therefore, 288 scenario observations were obtained and recorded in the excel file.
Recommended Citation:
Goodchild, Anne; McCormack, Ed; Ranjbari, Andisheh; Hurwitz, David, 2023, "Developing Better Curb Management Strategies through Understanding Commercial Vehicle Driver Parking Behavior in a Simulated Environment", Harvard Dataverse.

Simulation-Based Analysis of Different Curb Space Type Allocations on Curb Performance

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Publication: Transportmetrica B: Transport Dynamics
Volume: 11 (1)
Pages: 1384-1405
Publication Date: 2023

Curbspace is a limited resource in urban areas. Delivery, ridehailing and passenger vehicles must compete for spaces at the curb. Cities are increasingly adjusting curb rules and allocating curb spaces for uses other than short-term paid parking, yet they lack the tools or data needed to make informed decisions. In this research, we analyze and quantify the impacts of different curb use allocations on curb performance through simulation. Three metrics are developed to evaluate the performance of the curb, covering productivity and accessibility of passengers and goods, and CO2 emissions. The metrics are calculated for each scenario across a range of input parameters (traffic volume, parking rate, vehicle dwell time, and street design speed) and compared to a baseline scenario. This work can inform policy decisions by providing municipalities tools to analyze various curb management strategies and choose the ones that produce results more in line with their policy goals.

Authors: Thomas MaxnerDr. Andisheh RanjbariŞeyma Güneş, Chase Dowling (Pacific Northwest National Laboratory)
Recommended Citation:
Thomas Maxner, Andisheh Ranjbari, Chase P. Dowling & Şeyma Güneş (2023) Simulation-based analysis of different curb space type allocations on curb performance, Transportmetrica B: Transport Dynamics, 11:1, 1384-1405, DOI: 10.1080/21680566.2023.2212324

Revenue-Related Strategies for New Mobility Options

The Urban Freight Lab (UFL) is partnering with ECONorthwest and Cityfi to develop a research product for the National Cooperative Highway Research Program (NCHRP) on the topic of revenue strategies for new mobility options. The team will analyze the public sector’s potential role in using revenue-related strategies to encourage or discourage new mobility options in personal mobility and goods delivery.

Transportation services often operate in publicly owned and publicly managed spaces, make use of public rights-of-way, and produce mobility benefits for a broad array of users. The public sector is responsible for managing and pricing those rights-of-way and delivering services in an equitable way. Recovering the public costs of management and provisioning from private transportation services and their users is essential for maintaining public benefit. And sometimes the public sector needs to help private services to thrive.

The research methodology for this project is designed to be iterative: activities and research will build on previous research and activities. We will begin with the development of a revenue framework informed by a broad review of the literature, a policy scan, and workshop sessions with transportation and other public agency representatives that regulate and collect revenue from new mobility services. The framework will include revenue-related strategies based on:

    • (a) identifiable need
    • (b) nexus to cost responsibility
    • (c) policy outcome
    • (d) other factors such as access to technology and ease of administration.

We will then take a deeper dive into each personal mobility mode and goods delivery market segment to apply the framework. We will also provide examples to illustrate the opportunities and challenges of a variety of revenue strategies. We will also conduct additional workshops with public agency representatives, industry representatives, and other transportation stakeholders. Finally, we will create a spreadsheet-based Revenue Calculator that allows interested individuals to estimate how much revenue could be generated using different assumptions and strategies. The work will culminate with the development of a Toolkit that will be submitted to NCHRP and made available for wider distribution.


The objective of this research is to develop a toolkit for transportation agencies that addresses how revenue-related strategies (e.g., taxes, fees, and subsidies) support policy objectives and shape the deployment of new mobility options. The toolkit will assist agencies to develop, evaluate, implement, and administer revenue-related strategies for new mobility options that transport people and goods.

The research will include:

  1. New and evolving transportation options for people and goods that interact with the existing built environment and travel throughout an area
  2. Incentives and disincentives that result from revenue-related strategies
  3. Policy implications of revenue-related strategies for new mobility options including revenue potential, mobility, travel demand, safety, equity, environment, economic development, infrastructure design, operations, and maintenance
  4. Mechanisms for revenue collection and distribution for different mobility options in different scenarios
  5. The ease and difficulty of implementing and enforcing different revenue-related strategies for new mobility options
  6. Potential roles and responsibilities of governmental organizations and private entities

Last-Mile Freight Curb Access: Digitizing the Last Mile of Urban Goods to Improve Curb Access and Use

The U.S. Department of Transportation (USDOT) awarded a $2 million grant under its SMART (Strengthening Mobility and Revolutionizing Transportation) grant program to support the development of the Last-Mile Freight Curb Access Program: Digitizing the Last Mile of Urban Goods to Improve Curb Access and Utilization, a collaboration between the Urban Freight Lab, Seattle Department of Transportation, and Open Mobility Foundation. This project will develop sensor-based technology solutions that address to transportation problems, enabling commercial vehicles to make faster, safer, and more efficient deliveries with reduced vehicle emissions.

The Last Mile Freight Curb Access Program focuses on providing commercial vehicle drivers with real-time information to park legally and expedite deliveries. Research from a 2019 Urban Freight Lab study showed that more than 40% of commercial vehicles in downtown Seattle park in unauthorized locations. Another study showed that equipping commercial vehicles with real-time parking availability and load zone information could reduce their “cruising” time by nearly 30%. The project aims to make information about curbside regulations digitized and more accessible to commercial drivers, and leverage this data to improve regulations.

Other cities including Portland, San Francisco, San Jose, Los Angeles, Minneapolis, Philadelphia, and Miami-Dade County have also received SMART grants to implement similar technology-based solutions for improving curb access.


Since 2010, the Seattle Department of Transportation (SDOT) has been a national leader in data-driven curbside management by using parking occupancy data to set on-street parking rates. We proposed to extend our data-driven pricing and curb literacy to a new use: designated commercial vehicle load zones (CVLZ) and the commercial vehicle permit (CVP). Our plan is to establish new CVP policies in close collaboration with urban freight companies, adjacent businesses, and other critical stakeholders; implement a digital CVP built on the Curb Data Specification (CDS) that enables capture of curb utilization measurements and communicates demand management policies; and transform our legacy digital curb inventory to the national CDS standard.


To address these challenges, SDOT proposes a SMART project that will use a combination of digital technologies coupled with targeted outreach. This approach will be implemented through three key strategies:

  1. Engage with local businesses and urban freight companies to understand challenges and build a foundation of trust SDOT will engage with a variety of stakeholders including local neighborhood businesses, commercial vehicle users from large carriers, and commercial vehicle permit (CVP) holders from small and local businesses. The goal is to build trust and work collaboratively with our users to modernize and improve our existing CVP to create a system that works for urban freight companies, local businesses, and benefits the community at large.
  2. Prototype a digital CVP and use findings to modernize and scale the system SDOT will conduct a vendor procurement to prototype and assess a wireless vehicle-to-curb infrastructure (V2I) communication system, built on top of the Curb Data Specification (CDS) standard as a new way to manage our CVP. Data collected through this prototype will be leveraged by the UFL to conduct research to develop standardized data collection efforts for commercial curb use and create new data-driven policy and permit recommendations.
  3. Collaborate with a national cohort of cities implementing the Curb Data Specification SDOT will partner with the Open Mobility Foundation (OMF) and collaborate with a national cohort of OMF member cities to support the shared objectives in how CDS can help cities and companies pilot and scale dynamic curb use. SDOT will share lessons from Stage 1 prototyping with OMF cohort cities to strengthen all CDS-related SMART grant projects and better position proven technologies to be implemented at scale for a Stage 2 project. SDOT is uniquely positioned to deliver a successful Stage 1 project focusing on commercial vehicle curb access and utilization given our existing CVP and leadership in data driven curbside management. Specifically, this project will directly address the SMART goals of equity and access, partnerships, and integration and build the foundation for dramatic improvements in safety, reliability, and climate in Stage 2. Our goal is that the Stage 1 learnings will allow us to scale a digital CVP for citywide adoption in Stage 2, thus promoting interoperability of technology solutions to improve curb access for commercial curb users citywide. Our approach centers on stakeholder and community partnerships, data-driven assessment, and technical capacity-building. Potential outcomes for testing and implementation in Stage 2 include updated policies or curb allocations that might address inequities through deeper understanding of the variety of commercial users of the curb, reduced carbon emissions by creating or incenting CV zero emission zones, and decreased impacts to vulnerable road users through optimized curb allocation.


The expected benefits of Stage 1 will be threefold:

    1. Rigorously assess the piloted technology system to understand its scaling potential: The project will develop a technology assessment methodology that will look critically at accuracy and data use model development. This assessment will be transparent and developed in collaboration with OMF cohort cities to ensure solutions are scalable while meeting the core needs of Seattle’s digital CVP.
    2. Create a CDS framework for standardizing data collection efforts of commercial curb space: SDOT will share lessons learned from Stage 1 prototyping and policy recommendations with OMF cohort cities to collectively strengthen all CDS-related SMART grant projects and better position proven technologies to be implemented at scale.
    3. Create new data-driven commercial vehicle policy and permit recommendations to be enacted during Stage 2 of this grant

The recommendations will be informed by data models created by the UFL using utilization data from the project overlayed with characteristics of adjacent urban form and land use. These models will help SDOT identify areas for adjustments to existing curb allocation as well as establish a deeper understanding of the variety of commercial vehicle user behavior at the curb to meet climate goals. We anticipate these policies will benefit both curb users and local community members by reducing congestion and creating safer streets.


Success Factors for Urban Logistics Pilot Studies

Publication: The Routledge Handbook of Urban Logistics
Publication Date: 2023

The last mile of delivery is undergoing major changes, experiencing new demand and new challenges. The rise in urban deliveries amid the societal impacts of the COVID-19 pandemic has dramatically affected urban logistics. The level of understanding is increasing as cities and companies pilot strategies that pave the way for efficient urban freight practices. Parcel lockers, for instance, have been shown to reduce delivery dwell times with such success that Denmark increased its pilot program of 2,000 lockers to 10,000 over the past two years. This chapter focuses on challenges faced during those pilots from technical, managerial and operational perspectives, and offers examples and lessons learned for those who are planning to design and/or run future pilot tests. On-site management proved to be critical for locker operations.

Recommended Citation:
Ranjbari, Andisheh & Goodchild, A & Guzy, E. (2023). Success Factors for Urban Logistics Pilot Studies. 10.4324/9781003241478-27.
Student Thesis and Dissertations

Estimating the Location of Private Infrastructure for Delivery and Pick-Up Operations in Dense Urban Areas

Publication Date: 2018

The growth of home deliveries, lower inventory levels and just-in-time deliveries drive the fragmentation of freight flows, increased frequency, more delivery addresses and smaller volumes. This leads to trucks inefficiently loaded and consequently more trucks in the road contributing to the growing congestion in cities. According to a study by INRIX and the Texas Transportation Institute, travelers in the U.S. are stuck 42 hours per rush hour commuter in their cars in 2014, that is twice what it was in 1982 and the problem is four times worse than in 1982 for cities of 500,000 people or less [28]. At the same time, a historical lack of integration of the freight transportation system into city planning efforts has left local governments unprepared. Under these circumstances, there is growing need for best practices for freight planning and management in U.S. cities. There is anecdotal evidence that the lack of areas for trucks to park and load/unload freight is one of the main causes of an inefficient urban freight parking infrastructure that leads to illegal parking and more congestion. The problem of lack of parking for freight loading/unloading has been studied with a focus on on-street parking. Meanwhile, the contribution of areas out of the public right of way (i.e. private) such as loading bays in buildings has not benefited from research. More importantly, the location and features of private freight parking are often unknown by local governments due to their private character.

This thesis presents the first predictive tool to estimate the presence of private freight loading/unloading infrastructure based on observable characteristics of property parcels and their buildings. The predictive model classifies parcels with and without these infrastructures using random forest, a supervised machine learning algorithm. The model was developed based on a rich geodatabase of private truck load/unload spaces in the City of Seattle and the King County tax parcel database. The performance of the random forest model was evaluated through cross-validated estimates of the test error. The distribution of the outcome variables is unbalance with over 90% of parcels without private freight infrastructure. To consider the problem of unbalance sample, the optimum model was set to maximize the area under the ROC curve (AUC). The authors investigated the confusion matrix and the model classifier was design to balance the sensitivity and specificity of the model. Model results showed AUC of 81.5%, a true positive rate of 82.1% and a misclassification error of 22.5%.

This research provides an assessment tool that reduces the field work required to develop a quality inventory of private freight loading/unloading infrastructure by targeting the parcel stock and making data collection methods more effective. Local governments can use this research to inform efforts to revise and update delivery operations and regulations of truck parking and loading.

Recommended Citation:
Machado Leon, Jose Luis. (2018). Estimating the Location of Private Infrastructure for Delivery and Pick-Up Operations in Dense Urban Areas. University of Washington Master's Degree Thesis.
Thesis: Array

Growth of Ecommerce and Ride-Hailing Services is Reshaping Cities Connecting State and City DOTs, and Transit Agencies for Innovative Solutions

Publication: AASHTO 2018 Joint Policy Conference: Connecting the DOTs
Volume: 19-Jul-18
Publication Date: 2018

There is not enough curb capacity, now.

A recent curb parking utilization study in the City of Seattle indicated 90% or higher occupancy rates in Commercial Vehicle Load Zones (CVLZs) for some areas for much of the workday.

The Final Fifty Feet is a new research field.

The Final 50 Feet project is the first time that researchers have analyzed both the street network and cities’ vertical space as one unified goods delivery system. It focuses on:

  • The use of scarce curb, buildings’ internal loading bays, and alley space
  • How delivery people move with handcarts through intersections and sidewalks; and
  • On the delivery processes inside urban towers.
Authors: Barbara Ivanov
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

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Publication: U.S. Department of Energy
Publication Date: 2021

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:

  1. 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
  2. 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
  3. 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.
Recommended Citation:
Urban Freight Lab (2021). Year Two Progress Report: Technology Integration to Gain Commercial Efficiency for the Urban Goods Delivery System.

How Cargo Cycle Drivers Use the Urban Transport Infrastructure

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Publication: Transportation Research Part A: Policy and Practice
Volume: 167
Publication Date: 2023

Electric cargo cycles are often considered a viable alternative mode for delivering goods in an urban area. However, cities in the U.S. are struggling to regulate cargo cycles, with most authorities applying the same rules used for motorized vehicles or traditional bikes. One reason is the lack of understanding of the relationships between existing regulations, transport infrastructure, and cargo cycle parking and driving behaviors.

In this study, we analyzed a cargo cycle pilot test in Seattle and collected detailed data on the types of infrastructure used for driving and parking. GPS data were augmented by installing a video camera on the cargo cycle and recording the types of infrastructure used (distinguishing between the travel lane, bicycle lane, and sidewalk), the time spent on each type, and the activity performed.

The analysis created a first-of-its-kind, detailed profile of the parking and driving behaviors of a cargo cycle driver. We observed a strong preference for parking (80 percent of the time) and driving (37 percent of the time) on the sidewalk. We also observed that cargo cycle parking was generally short (about 4 min), and the driver parked very close to the delivery address (30 m on average) and made only one delivery. Using a random utility model, we identified the infrastructure design parameters that would incentivize drivers to not use the sidewalk and to drive more on travel and bicycle lanes.

The results from this study can be used to better plan for a future in which cargo cycles are used to make deliveries in urban areas.

Recommended Citation:
Dalla Chiara, G., Donnelly, G., Gunes, S., & Goodchild, A. (2023). How Cargo Cycle Drivers Use the Urban Transport Infrastructure. Transportation Research Part A: Policy and Practice, 167, 103562.