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Technical Report

Interview Results: Carrier Perspectives on Delivery Operations and Zero-Emission Zones in Downtown Portland

 
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Publication Date: 2024
Summary:

In 2023, Portland was awarded a U.S. Department of Transportation SMART grant to pilot a Zero-Emission Delivery Zone (ZEDZ). Funding for this Stage One SMART grant will allow PBOT to trial changing three to five truck loading zones into “Zero-Emission Delivery” loading zones in downtown Portland. The Urban Freight Lab (UFL) was approached by PBOT to assist in their SMART grant implementation by providing subject matter expertise on the topics of urban freight, curb management, and freight decarbonization. The UFL team created a questionnaire and interview guide to inquire about current carrier operations, current and future fleet composition, and loading activities of carriers operating in the City of Portland.

The selected organizations were identified as carriers or organizations that make deliveries into the proposed Zero-Emission Delivery Zone (ZEDZ) in downtown Portland. The UFL reached out to over 20 different organizations spanning different business sectors and company sizes, from large national parcel carriers to regional wholesale distributors to small delivery companies. Ultimately, only four organizations responded to requests for interviews. Between June and August 2024, the UFL conducted these interviews. Table 1 provides an overview of the companies interviewed and their main business activities. Company and organization names are omitted from this report to anonymize the respondents.

The goal of the interviews was to understand the parking behaviors and fleets of individual companies. In particular, the interviewers focused on understanding the current delivery operations in the Portland area, the related parking and routing behaviors of their delivery drivers, fleet composition, and the challenges they face in performing deliveries in the study area.

Each interview was 1-hour long and was guided on a questionnaire reported in the appendix. The questionnaire was developed into three sections:

  • Organization – Describe their main business activities, logistics network and fleet composition.
  • Routing, parking, and payment behaviors – Description of typical drivers’ operations in the City of Portland and specifically downtown, including routing and parking behaviors, as well as use of paid parking and citations.
  • Future scenarios – Companies were asked about zero-emission vehicles and implications of the ZEDZ on operations.

This report contains the main results of the interviews, including a description of the logistics network infrastructure, delivery operations, and curb use behaviors. The final section provides the key lessons learned.

Zero-Emission Delivery Zone: City of Portland SMART Grant

The Portland Bureau of Transportation (PBOT) was awarded a nearly $2 million Strengthening Mobility and Revolutionizing Transportation (SMART) Grant by the US Department of Transportation (USDOT) in Fall 2023 to pilot the country’s first regulated Zero-Emission Delivery Zone in downtown Portland and test digital infrastructure tools. This project will test an innovative set of incentives and regulations to better understand what technology and strategies municipalities can use to support and reduce greenhouse gas emissions in the freight sector.

While other cities in the United States have piloted voluntary Zero-Emission Delivery Zones (ZEDZs) to encourage the transition of commercial fleets to zero-emission modes, Portland will be the first U.S. city to pilot a regulated ZEDZ. The regulated ZEDZ will be active during a demonstration period of approximately six months beginning in late summer/early fall of 2024. During this temporary demonstration period, the parking rules for all truck loading zones within the project area will be changed to prioritize access for zero-emission vehicles only (see Figure 1). Loading zones within the ZEDZ will be monitored by parking sensors, both before and after the approximately six-month long demonstration period, so that project staff can better understand the impact of this regulation. These loading zones will be referred to as Zero-Emission Loading Zones.

This pilot project will also test a variety of partnerships and incentives to accelerate the movement of “clean goods,” or goods with fewer negative impacts to health and the environment. This could include diverting existing deliveries into the ZEDZ to local fleets of electric-assist cargo trikes and electric vehicles, vans and trucks, or supporting local delivery companies in transitioning their own fleets to zero-emission modes.

This project is enabled by a nearly $2 million USDOT SMART Stage 1 pilot and prototyping grant. Depending on outcomes from this pilot project, PBOT will have the opportunity to apply for a Stage 2 implementation grant for up to $15 million to refine or scale promising strategies identified in the initial pilot project. The two stages of the SMART grant program are unique in that they allow the City of Portland to test several strategies on a small scale before exploring any larger-scale implementation. All of this work is in service to Portland’s values around climate and transportation justice: a safer, cleaner, and more equitable system for delivering goods and services.

Draft map of project area showing proposed zero-emission load zones updated in March 2024. Loading zone site selection will be refined with stakeholder input in late Spring 2024.

Scope of Work

The Urban Freight Lab (UFL) was approached by PBOT to assist in their Phase 1 SMART grant implementation. The UFL will provide subject matter expertise on the topics of urban freight, curb management, and freight decarbonization. They will support PBOT in the form of interviews and/or surveys to summarize current carrier operations, current and future fleet composition, and loading activities.

  • Task 1. Project management and subject matter expertise support
    • Deliverables: Attend meetings and provide subject matter expert consultation as needed.
  • Task 2. Document how some carriers and delivery operators would be impacted by a zero-emission delivery zone (ZEDZ) in Portland, including understanding current and planned fleet composition, interactions with the curb, and barriers and opportunities for the City to support.
    • Deliverables: Interview questionnaire and summaries of answers (we will aggregate and anonymize results). Draft and final technical memo, with one PBOT review of the draft

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

Tasks

  • 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.

Deliverable

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

Dataset

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

Publication: Harvard Dataverse
Publication Date: 2023
Summary:

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. https://doi.org/10.7910/DVN/HVAUT3.
Paper

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

 
Download PDF  (3.49 MB)
Publication: Transportmetrica B: Transport Dynamics
Volume: 11 (1)
Pages: 1384-1405
Publication Date: 2023
Summary:

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.

Objectives

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.

Background

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.

Strategies

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.

Objectives

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.

Chapter

Success Factors for Urban Logistics Pilot Studies

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

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.

A Holistic Data-Driven Framework for Curb Space Use and Policy-Making

The curb space is the portion of the public rights-of-way that demarcates the roadway from the sidewalk, separating pedestrian flow from moving vehicles. It is a scarce public resource that has been traditionally used for storing private passenger vehicles. However, the past decade has seen not only a surge in demand but also the rise of new demands for curb space, driven by new forces of change: the rise in online shopping has driven up the demand for delivery vehicle loading and unloading spaces; the increasing use of ride-hailing vehicles such as Uber and Lyft has exacerbated curb space congestion; the rapid adoption of micromobility modes has increased their parking demand, among others. The pandemic has only exacerbated the issue due to greater demand for home delivery services and novel use cases such as curbside cafes.

The mismatch between the increase in demand and the lack of curb space supply represents a bottleneck in the urban transportation system, increasing the cruising for parking time — the time drivers spend searching for parking — as well as the occurrence of unauthorized parking. Both consequences heavily impact urban traffic congestion, increasing emissions and lowering the quality of life for urban dwellers, as well as can potentially create unsafe conditions. More broadly, the curb is a major linchpin in city operations: beyond congestion, it also affects business district vitality, residential access, and even policy decisions about new constructions.

To address these challenges, cities need greater access to data science and machine learning tools to have better insights into the overall use of and demand for curb space, with the final objective to be able to effectively manage the limited amount of curb space available. This includes the need for tools to aid in optimizing pricing mechanisms and to adaptively learn the most efficient and sustainable allocation of space to the different types of users.

Two research groups at the University of Washington have taken different but complementary approaches to study the curb and build tools to help cities understand different curb demands and better manage the limited curb space available.

The Urban Freight Lab, led by Prof. Anne Goodchild, approaches the study of the curb from the perspective of commercial vehicles, including delivery and ridehailing vehicles. The group has collected data and derived statistical models of curb users’ behaviors for commercial vehicles. Furthermore, the group has piloted on-the-ground technologies and policies to improve curb access. In a recent project, Prof. Goodchild’s group deployed 300 in-ground occupancy sensors at commercial vehicle load zones (CVLZs) and passenger load zones (PLZs) — curb spaces dedicated to commercial and ridehailing vehicles — in a 10-block study area in the Belltown neighborhood of Seattle, WA, collecting more than a year of fine-grained curb-use data.

The research group led by Prof. Lilian Ratliff approaches the study of the curb primarily from the perspective of private passenger vehicles, applying innovative machine learning and game theory tools to study curb management policies. In a recent project, Prof. Ratliff’s group developed a new modeling framework to estimate on-street paid parking occupancies — spaces dedicated for private passenger vehicle parking — from parking transaction data and sparse ground truth occupancy data obtained via manual counts and timelapse camera images.

The research in Goodchild’s and Ratliff’s groups has been impactful. Yet, load zone and paid parking curb-uses are highly interdependent given that the zones dedicated to the different use cases are often on the same curb. Hence, a more holistic approach to learning curb use behaviors is needed in order to effectively manage the whole curb.

For this project, the two groups will collaborate to integrate different data streams currently being collected separately and in an uncoordinated way, including data from in-ground curb sensors at CVLZs and PLZs, paid parking transactions at paid parking spaces, and data obtained from timelapse camera recordings. With such a complete dataset, the groups will create a holistic framework to analyze not only the curb behaviors of different users but also how different users interact in the competition for limited curb space.

The proposed collaboration will advance the state of the art in environmental sciences by providing the most complete dataset and creating innovative tools to inform policymaking on curb parking pricing and curb allocation to reduce cruising for parking and unauthorized parking events, therefore tackling the climate crisis by reducing urban vehicle emissions and traffic congestion.

The proposed collaboration will also advance the state of the art in data science by developing a new statistical framework and machine learning algorithms to analyze curb space use behaviors from different curb space users and develop much-needed recommendations for cities on how to better allocate curb space to different competing demands.

The project will have a direct impact on the City of Seattle as both groups are currently collaborating with the Seattle Department of Transportation to create a more data-driven decision-making framework for curb space policies, as well as an impact on the fields of urban transportation and logistics by merging two separate kinds of literature, the more traditional transport theory taking private passenger vehicles as the main actor in urban transportation and the urban logistics field that focuses on commercial vehicles operations in urban areas.

Concrete outcomes of the projects obtained during the year of collaboration will include a joint seminar series of the two groups, presenting their ongoing research projects that focused on the curb, a join effort to collect data in Seattle, and integrating data streams to generate a complete dataset of curb use for the Seattle downtown area. Additionally, the groups will jointly write a scientific paper proposing a holistic framework to analyze the curb from the different users’ perspectives. The proposed collaboration will expand upon the projects Prof. Goodchild’s and Prof. Ratliff’s groups are currently working on, and develop a new set of data and tools that will enable future joint grant proposals by the two groups.

Paper

How to Improve Urban Delivery Routes’ Efficiency Considering Cruising for Parking Delays

 
Download PDF  (2.27 MB)
Publication Date: 2022
Summary:

This paper explores the value of providing parking availability data in urban environments for commercial vehicle deliveries. The research investigated how historic cruising and parking delay data can be leveraged to improve the routes of carriers in urban environments to increase cost efficiency. To do so, the research developed a methodology consisting of a travel time prediction model and a routing model to account for parking delay estimates. The method was applied both to a real-world case study to show its immediate application potential and to a synthetic data set to identify environments and route characteristics that would most benefit from considering this information.

Results from the real-world data set showed a mean total drive time savings of 1.5 percent. The synthetic data set showed a potential mean total drive time savings of 21.6 percent, with routes with fewer stops, a homogeneous spatial distribution, and a higher cruising time standard deviation showing the largest savings potential at up to 62.3 percent. The results demonstrated that higher visibility of curb activity for commercial vehicles can reduce time per vehicle spent in urban environments, which can decrease the impact on congestion and space use in cities.

Authors: Fiete KruteinDr. Giacomo Dalla ChiaraDr. Anne Goodchild, Todor Dimitrov (University of Washington Paul G. Allen School of Computer Science & Engineering)
Recommended Citation:
Krutein, Klaas Fiete and Dalla Chiara, Giacomo and Dimitrov, Todor and Goodchild, Anne, How to Improve Urban Delivery Routes' Efficiency Considering Cruising for Parking Delays. http://dx.doi.org/10.2139/ssrn.4183322