Research Topic: The Final 50 Feet of the Urban Goods Delivery System

The Urban Freight Lab coined the term “Final 50 Feet” and defined it as the supply chain segment that begins when a delivery vehicle pulls into a parking space and stops moving — in public load/unload spaces at the curb or in an alley, or a building’s loading dock or internal freight bay. It tracks the delivery process inside buildings and ends where the customer takes receipt of their goods. This research analyzes processes, develops potential solutions, and tests operational improvements in the final segment of the urban goods delivery system.

Presentation

Roadblocks to Sustainable Urban Freight

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URL: https://www.metrans.org/inuf_2022-papers_presentations

Publication: 9th International Urban Freight Conference, Long Beach, May 2022

Publication Date: 2022

Summary:

While several stakeholders in the private and public sectors are taking actions and drafting roadmaps to achieve sustainable urban freight goals, the urban freight ecosystem is a complex network of stakeholders, achieving such sustainability goals requires the collaboration and coordination between multiple agents. Researchers collected and synthesized views from both the private and public sectors on what is needed to sustainably deliver the last mile and identify roadblocks towards this goal.

Authors: Thomas MaxnerDr. Giacomo Dalla ChiaraDr. Anne Goodchild

Recommended Citation:
Thomas Maxner, Giacomo Dalla Chiara, Anne Goodchild (2022). Roadblocks to Sustainable Freight. 9th International Urban Freight Conference (INUF), Long Beach, CA May 2022.

Empirical Analysis of Commercial Vehicle Dwell Times Around Freight-Attracting Urban Buildings in Downtown Seattle

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URL: https://doi.org/10.1016/j.tra.2021.02.019

Publication: Transportation Research Part A: Policy and Practice

Volume: 147

Pages: 320-338

Publication Date: 2021

Summary:

This study aims to identify factors correlated with dwell time for commercial vehicles (the time that delivery workers spend performing out-of-vehicle activities while parked). While restricting vehicle dwell time is widely used to manage commercial vehicle parking behavior, there is insufficient data to help assess the effectiveness of these restrictions, which makes it difficult for policymakers to account for the complexity of commercial vehicle parking behavior.

This is accomplished by using generalized linear models with data collected from five buildings that are known to include commercial vehicle activities in the downtown area of Seattle, Washington, USA. Our models showed that dwell times for buildings with concierge services tended to be shorter. Deliveries of documents also tended to have shorter dwell times than oversized supplies deliveries. Passenger vehicle deliveries had shorter dwell times than deliveries made with vehicles with roll-up doors or swing doors (e.g., vans and trucks). When there were deliveries made to multiple locations within a building, the dwell times were significantly longer than dwell times made to one location in a building. The findings from the presented models demonstrate the potential for improving future parking policies for commercial vehicles by considering data collected from different building types, delivered goods, and vehicle types.

Authors: Haena KimDr. Anne Goodchild, Linda Ng Boyle

Recommended Citation:
Kim, H., Goodchild, A., & Boyle, L. N. (2021). Empirical analysis of commercial vehicle dwell times around freight-attracting urban buildings in downtown Seattle. Transportation Research Part A: Policy and Practice, 147, 320–338. https://doi.org/10.1016/j.tra.2021.02.019

Technical Report

The Final 50 Feet of the Urban Goods Delivery System: Pilot Test of an Innovative Improvement Strategy

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URL: http://hdl.handle.net/1773/44473

Publication: Pacific Northwest Transportation Consortium (PacTrans)

Publication Date: 2019

Summary:

This report presents a pilot test of a common carrier smart locker system — a promising strategy to reduce truck trip and failed first delivery attempts in urban buildings. The Urban Freight Lab tested this system in the 62-story Seattle Municipal Tower skyscraper in downtown Seattle.

The Urban Freight Lab identified two promising strategies for the pilot test: (1) Locker system: smaller- to medium-sized deliveries can be placed into a locker that was temporarily installed during the pilot test; and (2) Grouped-tenant-floor-drop-off-points for medium-sized items if the locker was too small or full (4-6 floor groups set up by Seattle Department of Transportation and Seattle City Light).

Users picked up their goods at the designated drop-off points. Flyers with information on drop-off-points were given to the carriers. UFL researchers evaluated the ability of the standardized second step pilot test to reduce the number of failed first delivery attempts by (1) Collecting original data to document the number of failed first delivery attempts before and after the pilot test; and (2) Comparing them to the pilot test goals.

Authors: Haena KimBarbara IvanovDr. Anne Goodchild

Recommended Citation:
Goodchild, A., Kim, H., & Ivanov, B. Final 50 Feet of the Urban Goods Delivery System: Pilot Test of an Innovative Improvement Strategy. (2019)

Analysis of Parking Utilization Using Curb Parking Sensors (Task Order 10)

In a Department of Energy-funded project led by the Urban Freight Lab, a network of parking occupancy sensors was installed in a 10-block study area in the Belltown neighborhood of Seattle, Washington. The study aimed at improving commercial vehicle delivery efficiency generating and providing real-time and future parking information to delivery drivers and carriers. This project will build upon the existing sensor network and the knowledge developed to explore how historical parking occupancy data can be used by urban planners and policymakers to better allocate curb space to commercial vehicles. The proposed project will use data from the existing sensor network and explore the relationship between the built environment (location and characteristics of establishments and urban form) and the resulting occupancy patterns of commercial vehicle load zones and passenger load zones in the study area.

Task 1 – Gather public data sources

Using public data sources (e.g. SDOT open data portal and Google Maps Places) the research team will obtain data on buildings and business establishments located in the Belltown study area (1st to 3rd Ave and Battery to Stewart Street). Data will include the location of business establishments, building height, land use, and estimates of the number of residents per building.

Task 2 – Analyze sensor data and estimate parking events

The research team will retrieve and process 1-year historical sensor data from the sensor network deployed in the study area. Sensor data is not directly usable as sensors are placed every 10 feet and a vehicle parking in a curb space might activate more than one sensor. Therefore, the research team will develop an algorithm that takes as input raw sensor data and gives as output estimate individual parking events, each consisting of a start time, curb space, and parking dwell time. The algorithm will be validated and algorithm performance will be reported.

Task 3 – Estimate parking utilization for each curb parking space

Using the estimated parking events obtained from task 2, the research team will analyze parking patterns and estimate total parking utilization for each curb parking space over time.

Task 4 – Design and perform an establishment survey

The research team will design an establishments survey to gather data on opening times, number of employees, type of business, and number of trips generated by business establishments in the study area. The survey will then be deployed and data will be collected for the business establishments in the study area. Descriptive statistics will be obtained characterizing the demand of freight trips generated by business type in the study area.

Task 5 – Analysis of parking utilization

The research team will perform statistical modeling to understand factors affecting curb space utilization in relationship with the location and characteristics of individual buildings and business establishments. The output of this effort is twofold: first, the analysis will obtain the factors that best explain the observed variability in curb parking demand, second, the analysis will obtain a model that can be used to predict future curb space demand.

Task 6 – Dissemination of findings and recommendations

A final report containing the result from the collection, processing, and analysis of the sensors data and establishment survey data will be drafted and published.

Expected outcomes

Descriptive time and spatial analysis of commercial vehicle load zone and passenger load zone utilization
Understand the impact of different establishments’ location and characteristics on commercial vehicle load zone and passenger load zone utilization
Discussion of policy implications for commercial vehicle load zones and passenger load zones allocation and time restrictions

Presentation

Growth of Ecommerce and Ride-Hailing Services is Reshaping Cities: The Urban Freight Lab’s Innovative Solutions

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URL: https://catc.ca.gov/-/media/ctc-media/documents/tab-10-3-a11y.pdf

Publication: California Transportation Commission (August 15, 2018)

Publication Date: 2018

Summary:

A 20% e-commerce compound annual growth rate (CAGR) would more than double goods deliveries in 5 years. If nothing changes, this could double delivery trips in cities; thereby doubling the demand for load/unload spaces.

Innovation is needed to manage scarce curbs, alleys, and private loading bay space in the new world of on-demand transportation, 1-hour e-commerce deliveries, and coming autonomous vehicle technologies.

The Urban Freight Lab at the University of Washington (UW), in partnership with the City of Seattle Department of Transportation (SDOT), is using a systems engineering approach to solve delivery problems that overlap cities’ and businesses’ spheres of control.

The Urban Freight Lab is a living laboratory where potential solutions are generated, evaluated, and pilot-tested inside urban towers and on city streets.

Authors: Dr. Anne Goodchild

Recommended Citation:
Goodchild, Anne. Growth of Ecommerce and Ride-Hailing Services is Reshaping Cities: The Urban Freight Lab’s Innovative Solutions. California Transportation Commission (August 15, 2018)

Presentation

Improving Delivery Efficiency and Understanding User Behavior through Common Carrier Parcel Lockers

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URL: https://metrans.org/inuf_2022-papers_presentations

Publication: 9th International Urban Freight Conference, Long Beach, May 2022

Publication Date: 2022

Summary:

Common-carrier parcel lockers have emerged as a secure, automated, self-service means of delivery consolidation in congested urban areas, which are believed to mitigate last-mile delivery challenges by reducing out-of-vehicle delivery times and consequently vehicle dwell times at the curb. However, little research exists to empirically demonstrate the environmental and efficiency gains from this technology.

In this study, we designed a nonequivalent group pretest/post-test experiment to estimate the causal effects of a common-carrier locker in a residential building in downtown Seattle, WA. The causal effects are measured in terms of vehicle dwell time and the time delivery drivers spend inside the building, through the difference-in-difference method and using a similar residential building as a control.

The results showed a statistically significant decrease in time spent inside the building and a small yet insignificant reduction in vehicle dwell times.

Authors: Dr. Andisheh RanjbariCaleb DiehlDr. Giacomo Dalla ChiaraDr. Anne Goodchild

Recommended Citation:
Andisheh Ranjbari, Caleb Diehl, Giacomo Dalla Chiara, and Anne Goodchild (2022). Improving Delivery Efficiency and Understanding User Behavior through Common Carrier Parcel Lockers. 9th International Urban Freight Conference (INUF), Long Beach, CA May 2022.

Student Thesis and Dissertations

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

URL: http://hdl.handle.net/1773/42251

Publication Date: 2018

Summary:

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.

Authors: José Luis Machado León

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

Paper

Understanding the Use of the Curb Space and Alley for Unloading and Loading Operations: A Seattle Case Study

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Publication: VREF: Current Issues Influencing Urban Freight Research

Publication Date: 2018

Summary:

Purpose: The increasing growth of e-commerce has been putting pressure on local governments to rethink how they manage street curb parking and alley operations for trucks and other delivery vehicles. Many studies state that the competition for space among road users and the lack of adequate infrastructure force delivery drivers to either search for vacant spaces or park in unsuitable areas; which negatively impacts road capacity and causes inconvenience to other users of the road (Butrina et al. (2017); Dablanc & Beziat (2015); Aiura & Taniguchi (2005)).

However, local governments often lack data about the current usage of the parking infrastructure, which is necessary to make well-informed decisions regarding freight planning, especially in dense, constrained urban areas.

For these reasons, the purpose of this research is to address the lack of information regarding the usage of the infrastructure at the public right of way used for freight and parcel load and unload operations.

Research Approach: The approach of this research is quantitative. The SCTL research team developed two independent data collection replicable methods to quantify the usage of (i) curb spaces and (ii) alleys in selected areas of Seattle’s One Center City.

Findings and Originality: This research presents two case studies for selected areas in Seattle’s One Center City area. The first one documents and analyzes the duration and types of curb spaces used by delivery vehicles in the surrounding area of five prototype buildings. We also considered all vehicles occupying on-street commercial vehicle load zones located in the study area. The second case study conducts an alley occupancy survey, looking into all parking activities (including trucks, vans, garbage collection vehicles, and passenger vehicles) in seven alleys. A total of twelve survey locations were monitored during 2-3 weekdays and 4-8 hours per day.

Research Impact: This research provides practical step-by-step methods to conduct occupancy studies of public parking for loading and loading operations, which helps to understand the current usage of a key piece of the infrastructure network. The results provide critical information to make well informed decisions regarding urban freight planning especially in dense, constrained urban areas.

Practical Impact :This research describes the steps required to develop an efficient and systematic data collection method to build a database that will provide evidence-based learning to Seattle local officials. By applying these quantitative methods, we provided decision support to pilot-test and potentially adopt solutions to improve the freight parking infrastructure performance.

Authors: Dr. Anne GoodchildJosé Luis Machado LeónGabriela Girón-Valderrama

Recommended Citation:
Giron-Valderrama, G., Machado-León, J. L., & Goodchild, A. Understanding the use of the curb space and alley for unloading and loading operations: A Seattle Case Study. VREF: Current Issues Influencing Urban Freight Research, 37.

Urban Freight in 2030

There are many questions to answer about the future of urban delivery. How changes and developments in the industry will ultimately play out cannot really be predicted, but the Urban Freight Lab, a group of experienced professionals with deep and up-to-date knowledge of their subject, representing a broad range of urban freight stakeholders is best suited to envision the future. The Urban Freight in 2030 project will explore emerging urban freight trends, their impacts on local and global sustainable development, and propose Urban Freight Lab’s future course of action.

Objective: This project proposes to use the expertise of the Urban Freight Lab members and partners, supported by up-to-date research and subject specialists, to create a shared vision of the future of urban delivery in 2030. The work will produce vision documents to be shared publicly, outlining and detailing the Urban Freight Lab’s vision of the future of urban freight.

Summary of Project Tasks:

Task 1: Generate a candidate list of influential variables.

Task 2: UFL members provide feedback and democratically select four variables for future discussion.

Task 3: Schedule one category of variables discussion at each Urban Freight Lab quarterly meeting.

Task 4: Based on the discussions described in Task 3, UFL staff draft a number of public-facing documents that lay out our shared vision for Urban Freight 2030. The format of these products will be discussed during the course of the project.

Task 5: UFL members will review and revise the vision documents. When all members agree, it will be distributed publicly as a joint publication of the UFL research team and membership.

Presentation