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Seattle Center City: Alley Infrastructure Inventory and Occupancy Study

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Publication Date: 2018

The Supply Chain and Transportation Logistics (SCTL) Center conducted an alley inventory and truck load/unload occupancy study for the City of Seattle. Researchers collected data identifying the locations and infrastructure characteristics of alleys within Seattle’s One Center City planning area, which includes the downtown, uptown, South Lake Union, Capitol Hill, and First Hill urban centers. The resulting alley database includes GIS coordinates for both ends of each alley, geometric and traffic attributes, and photos. Researchers also observed all truck load/unload activity in selected alleys to determine minutes vacant and minutes occupied by trucks, vans, passenger vehicles, and cargo bikes. The researchers then developed alley management recommendations to promote safe, sustainable, and efficient goods delivery and pick-up.

Key Findings:

The first key finding of this study is that more than 90% of Center City alleys are only one lane wide. This surprising fact creates an upper limit on alley parking capacity, as each alley can functionally hold only one or two vehicles at a time. Because there is no room to pass by, when a truck, van, or car parks it blocks all other vehicles from using the alley. When commercial vehicle drivers see that an alley is blocked they will not enter it, as their only way out would be to back up into street traffic. Seattle Municipal Code prohibits this, as well as backing up into an alley, for safety reasons.

When informed by the second key finding—68% of vehicles in the alley occupancy study parked there for 15 minutes or less—it is clear that moving vehicles through alleys in short time increments is the only reasonable path to increase productivity. As one parked vehicle operationally blocks the entire alley, the goal of new alley policies and strategies should be to reduce the amount of time alleys are blocked to additional users.

The study surfaces four additional key findings:

  1. 87% of all vehicles in the 7 alleys studied parked for 30 minutes or less. Given the imperative to move alley traffic quickly, vehicles that need more parking time must be moved out of the alleys and onto the curb where they don’t block others.
  2. 15% of alleys’ pavement condition is so poor that delivery workers can’t pass through with loaded hand carts.  Although trucks can drive over fairly uneven pavement without difficulty, it is not the case for delivery people walking with fully loaded handcarts.  The alley pavement rating was done with a qualitative visual inspection to identify obvious problems; more detailed measurements would be needed to fully assess conditions.
  3. 73% of Center City area alleys contain entrances to passenger parking facilities. Placing garage entrances in alleys has been a city policy goal for years. But it increases the frequency of cars in alleys and adds demands on alley use. Understanding why cars are queuing for passenger garages located off alleys, and providing incentives and disincentives to reduce that, would help make alleys more productive.
  4. Alleys are vacant about half of the time during the business day. While at first blush this suggests ample capacity, the fact that an alley can only hold one-to-two parked trucks at a time means alleys are limited operationally and therefore are not a viable alternative to replace the use of curb CVLZs on city streets.

These findings indicate that, due to the fixed alley width constraint, load/unload space inside Seattle’s existing Center City area alleys is insufficient to meet additional future demand.

Recommended Citation:
Urban Freight Lab (2018). Seattle Center City: Alley Infrastructure Inventory and Occupancy Study.

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

A Policy-Sensitive Model of Parking Choice for Commercial Vehicles in Urban Areas

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Publication: Transportation Science
Publication Date: 2020

Understanding factors that drive the parking choice of commercial vehicles at delivery stops in cities can enhance logistics operations and the management of freight parking infrastructure, mitigate illegal parking, and ultimately reduce traffic congestion. In this paper, we focus on this decision-making process at large urban freight traffic generators, such as retail malls and transit terminals, that attract a large share of urban commercial vehicle traffic. Existing literature on parking behavior modeling has focused on passenger vehicles. This paper presents a discrete choice model for commercial vehicle parking choice in urban areas. The model parameters were estimated by using detailed, real-world data on commercial vehicle parking choices collected in two commercial urban areas in Singapore. The model analyzes the effect of several variables on the parking behavior of commercial vehicle drivers, including the presence of congestion and queuing, attitudes toward illegal parking, and pricing (parking fees). The model was validated against real data and applied within a discrete-event simulation to test the economic and environmental impacts of several parking measures, including pricing strategies and parking enforcement.

Authors: Dr. Giacomo Dalla Chiara, Lynette Cheah, Carlos Lima Azevedo, Moshe E. Ben-Akiya
Recommended Citation:
Dalla Chiara, Giacomo and Cheah, Lynette and Azevedo, Carlos Lima and Ben-Akiva, Moshe E. (2020). A Policy-Sensitive Model of Parking Choice for Commercial Vehicles in Urban Areas. Transportation Science, 54(3), 606–630. 

The Final 50 Feet of the Urban Goods Delivery System: Tracking Curb Use in Seattle

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Publication Date: 2019

Vehicles of all kinds compete for parking space along the curb in Seattle’s Greater Downtown area. The Seattle Department of Transportation (SDOT) manages use of the curb through several types of curb designations that regulate who can park in a space and for how long. To gain an evidence-based understanding of the current use and operational capacity of the curb for commercial vehicles (CVs), SDOT commissioned the Urban Freight Lab (UFL) at the University of Washington Supply Chain Transportation & Logistics Center to study and document curb parking in five selected Greater Downtown areas.

This study documents vehicle parking behavior in a three-by-three city block grid around each of five prototype Greater Downtown buildings: a hotel, a high-rise office building, an historical building, a retail center, and a residential tower. These buildings were part of the UFL’s earlier SDOT-sponsored research tracking how goods move vertically within a building in the final 50 feet.

The areas around these five prototype buildings were intentionally chosen for this curb study to deepen the city’s understanding of the Greater Downtown area.

Significantly, this study captures the parking behavior of commercial vehicles everywhere along the curb as well as the parking activities of all vehicles (including passenger vehicles) in commercial vehicle loading zones (CVLZs). The research team documented: (1) which types of vehicles parked in CVLZs and for how long, and; (2) how long commercial vehicles (CVs) parked in CVLZs, in metered parking, and in passenger load zones (PLZ) and other unauthorized spaces.

Four key findings, shown below, emerged from the research team’s work:

  1. Commercial and passenger vehicle drivers use CVLZs and PLZs fluidly: commercial vehicles are parking in PLZs, and passenger vehicles are parking in CVLZs. Passenger vehicles made up more than half of all vehicles observed parking in CVLZs (52%). More than one-quarter of commercial vehicle drivers parked in PLZs (26 %.) This fact supports more integrated planning for all curb space, versus developing standalone strategies for passenger vehicle and for commercial vehicle parking.
  2. Most commercial vehicle (CV) demand is for short-term parking: 15 or 30 minutes. Across the five locations, more than half (54%) of all CVs parked for 15 minutes or less in all types of curb spaces. Nearly three-quarters of all CVs (72%) parked for 30 minutes or less. When considering just the delivery CVs, an even higher percentage, 60%, parked for 15 minutes or less. Eighty-one percent of the delivery CVs parked for 30 minutes or less.
  3. Thirty-six percent of the total CVs parked along the curb were service CVs, showing the importance of factoring their behavior and future demand into urban parking schemes. In contrast to delivery CVs that predominately parked for 30 minutes or less, service CVs’ parking behavior was bifurcated. While 56% of them parked for 30 minutes or less, 44% parked for more than 30 minutes. And more than one quarter (27%) of the service CVs parked for an hour or more. Because service vehicles make up such a big share of total CVs at the curb, this may have an outsize impact on parking space turn rates at the curb.
  4. Forty-one percent of commercial vehicles parked in unauthorized locations. But a much higher percentage parked in unauthorized areas near the two retail centers (55% – 65%) when compared to the predominately office and residential areas (27% – 30%). The research team found that curb parking behavior is associated with granular, building-level urban land use. This occurred even as other factors such as the total number, length and ratio of CVLZs versus PLZs varied widely across the five study areas.

The occupancy study documents that each building and the built environment surrounding it has unique features that impact parking operations. As cities seek to more actively manage curb space, the study’s findings illuminate the need to plan a flexible network with capacity for distinct types (time and space requirements) of CV parking demand.

This study also drives home that the curb does not function in isolation, but instead forms one element of the Greater Downtown’s broader, interconnected load/unload network, which includes alleys, the curb, and private loading bays and docks. (1,2,3) SDOT commissioned this work as part of its broader effort with the UFL to map—and better understand—the entire Greater Downtown area’s commercial vehicle load/unload space network. Cities and other parties interested in the details of how to conduct a commercial vehicle occupancy study can see a step-by-step guide in Appendix C.

In this study, researchers deployed six data collectors to observe each curb study area for three days over roughly six weeks in October and December 2017. To make the data produced in this project as useful as possible, the research team designed a detailed vehicle typology to track specific vehicle categories consistently and accurately. The typology covers 10 separate vehicle categories, from various types of trucks and vans to passenger vehicles to cargo bikes. Passenger vehicles in this study were not treated as commercial vehicles, due to challenges in systematically identifying whether passenger vehicles were making deliveries or otherwise carrying a commercial permit.

The five prototype Seattle buildings studied are Seattle Municipal Tower (also the site of a common carrier parcel locker pilot), Dexter Horton, Westlake Center, and Insignia Towers. (4) The study shows how different building and land uses interact with the broader load/unload network. By collecting curb occupancy data in the same locations as their earlier work, the research team added a new layer of information to help the city evaluate—and manage—the Greater Downtown area load/unload network more comprehensively.

This report is part of a broader suite of UFL research to date that equips Seattle with an evidence-based foundation to actively and effectively manage Greater Downtown load/unload space as a coordinated network. The UFL has mapped the location and features of the legal landing spots for trucks across the Greater Downtown, enabling the city to model myriad urban freight scenarios on a block-by-block level. To the research team’s knowledge, no other city in the U.S. or the E.U. has this data trove. The findings in this report, together with all the UFL research conducted and GIS maps and databases produced to date, give Seattle a technical baseline to actively manage the Greater Downtown’s load/unload spaces as a coordinated network to improve the goods delivery system and mitigate gridlock.

The UFL will pilot such active management on select Greater Downtown streets in Seattle and Bellevue, Washington, to help goods delivery drivers find a place to park without circling the block in crowded cities for hours, wasting time and fuel and adding to congestion. The U.S. Department of Energy’s Office of Energy Efficiency and Renewable Energy under the Vehicles Technologies Office is funding the project. (5) The project partners will integrate sensor technologies, develop data platforms to process large data streams, and publish a prototype app to let delivery firms 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. This is the nation’s first systematic research pilot to test proof of concept of a functioning system that offers commercial vehicle drivers and dispatchers real-time occupancy data on load/unload spaces–and test what impact that data has on commercial driver behavior. This pilot can help inform other cities interested in taking steps to actively manage their load/unload network.

Actively managing the load/unload network is more imperative as the city grows denser, the e-commerce boom continues, and drivers of all vehicle types—freight, service, passenger, ride-sharing and taxis—jockey for finite (and increasingly valuable) load/unload space. Already, Seattle ranks as the sixth most-congested city in the country.

The UFL is a living laboratory made up of retailers, truck freight carriers and parcel companies, technology companies supporting transportation and logistics, multifamily residential and retail/commercial building developers and operators, and SDOT. Current members are Boeing HorizonX, Building Owners and Managers Association (BOMA) – Seattle King County, curbFlow, Expeditors International of Washington, Ford Motor Company, General Motors, Kroger, Michelin, Nordstrom, PepsiCo, Terreno, USPack, UPS, and the United States Postal Service (USPS).

Recommended Citation:
Urban Freight Lab (2019). The Final 50 Feet of the Urban Goods Delivery System: Tracking Curb Use in Seattle.

Commercial Vehicle Parking in Downtown Seattle: Insights on the Battle for the Curb

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Publication: Transportation Research Record: Journal of the Transportation Research Board
Publication Date: 2019

Rapid urban growth puts pressure on local governments to rethink how they manage street curb parking. Competition for space among road users and lack of adequate infrastructure force delivery drivers either to search for vacant spaces or to park in unsuitable areas, which negatively impacts road capacity and causes inconvenience to other users of the road.

The purpose of this paper is to advance research by providing data-based insight into what is actually happening at the curb. To achieve this objective, the research team developed and implemented a data collection method to quantify the usage of curb space in the densest urban area of Seattle, Center City.

This study captures the parking behavior of commercial vehicles everywhere along the block face as well as the parking activities of all vehicles (including passenger vehicles) in commercial vehicle loading zones. Based on the empirical findings, important characteristics of Seattle’s urban freight parking operations are described, including a detailed classification of vehicle types, dwell time distribution, and choice of curb use for parking (e.g., authorized and unauthorized spaces). The relationship between land use and commercial vehicle parking operations at the curb is discussed. Seattle’s parking management initiatives will benefit from the insights into current behavior gained from this research.

Rapid urban growth, increasing demand, and higher customer expectations have amplified the challenges of urban freight movement. Finding an adequate space to park can be a major challenge in urban areas. For commercial vehicles used for freight transportation and provision of services, the lack of parking spaces and parking policies that recognize those vehicles’ unique needs can have negative impacts that affect all users of the road, particularly the drivers of these commercial vehicles (1–4).

The curb is an important part of the public right-of-way. It provides a space for vehicles to park on-street; for delivery vehicles (i.e., cargo bikes, cargo vans, and trucks), in particular, it also provides a dedicated space for the loading and unloading of goods close to destinations. Hence it is a key asset for urban freight transportation planning which local governments can administer to support delivery and collection of goods.

According to Marcucci et al. (5), the development of sustainable management policies for urban logistics should be based on site-specific data given the heterogeneity and complexity of urban freight systems. Current loading/unloading parking policies include time restrictions, duration, pricing, space management, and enforcement (6, 7). However, as Marcucci et al. pointed out after an extensive review of the literature on freight parking policy, the quantification of commercial vehicle operations on the curb to inform policy decision making is nonexistent (5). Therefore, local governments often lack data about the current usage of the curb and parking infrastructure, which is necessary to evaluate and establish these policies and therefore make well-informed decisions regarding freight planning, especially in dense, constrained urban areas.

Given the importance of the curb as an essential piece of the load/unload infrastructure, this paper investigates what is actually happening at the curb, developing an evidence-based understanding of the current use of this infrastructure. The research team developed and applied a systematic data collection method resulting in empirical findings about the usage of public parking for loading and unloading operations in the Seattle downtown area.

This research documents and analyzes the parking patterns of commercial vehicles (i.e., delivery, service, waste management, and construction vehicles) in the area around five prototype buildings located in the Center City area. The results of this research will help to develop and inform parking management initiatives.

The paper includes four sections in addition to this introduction. The second section discusses previous freight parking studies and the existing freight parking policies in cities, and explores which of these approaches are being used in Seattle. The third section proposes a data collection method to document freight-related parking operations at the curb though direct observations. The fourth section provides empirical findings from data collection in Seattle. The fifth and last section includes a discussion of the findings and concluding remarks.

Recommended Citation:
Girón-Valderrama, Gabriela del Carmen, José Luis Machado-León, and Anne Goodchild. "Commercial Vehicle Parking in Downtown Seattle: Insights on the Battle for the Curb." Transportation Research Record (2019): 0361198119849062.