Paper

Providing Curb Availability Information to Delivery Drivers Reduces Cruising for Parking

URL: https://doi.org/10.1038/s41598-022-23987-z

Publication: Scientific Reports

Volume: (2022) 12:19355

Publication Date: 2022

Summary:

Delivery vehicle drivers are experiencing increasing challenges in finding available curb space to park in urban areas, which increases instances of cruising for parking and parking in unauthorized spaces. Policies traditionally used to reduce cruising for parking for passenger vehicles, such as parking fees and congestion pricing, are not effective at changing delivery drivers’ travel and parking behaviors.

Intelligent parking systems that use real-time curb availability information to better route and park vehicles can reduce cruising for parking, but they have never been tested for delivery vehicle drivers.

This study tested whether providing real-time curb availability information to delivery drivers reduces the travel time and distance spent cruising for parking. A curb parking information system deployed in a study area in Seattle, Wash., displayed real-time curb availabilities on a mobile app called OpenPark. A controlled experiment assigned drivers’ deliveries in the study area with and without access to OpenPark.

The data collected showed that when curb availability information was provided to drivers, their cruising for parking time significantly decreased by 27.9 percent, and their cruising distance decreased by 12.4 percent. These results demonstrate the potential for implementing intelligent parking systems to improve the efficiency of urban logistics systems.

Authors: Dr. Giacomo Dalla ChiaraFiete KruteinDr. Andisheh RanjbariDr. Anne Goodchild

Recommended Citation:
Dalla Chiara, G., Krutein, K.F., Ranjbari, A. et al. Providing curb availability information to delivery drivers reduces cruising for parking. Sci Rep 12, 19355 (2022). https://doi.org/10.1038/s41598-022-23987-z

Report

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

Download PDF (4.54 MB)

Publication Date: 2019

Summary:

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:

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.
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.
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.
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).

Authors: Urban Freight Lab

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

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)

URL: https://dx.doi.org/10.2139/ssrn.4183322

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

Paper

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

Download PDF (0.11 MB)

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.

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

Paper

An Empirical Taxonomy of Common Curb Zoning Configurations in Seattle

Download PDF (0.63 MB)

URL: https://doi.org/10.32866/001c.32446

Publication: Findings

Publication Date: 2022

Summary:

We utilize an unsupervised learning algorithm called-modes clustering (Huang 1998), which is similar to the better-known-means method (Hartigan and Wong 1979), but with a dissimilarity measure designed for categorical variables (Cao et al. 2012), originally developed for analyzing sequential categorical data such as gene sequences (Goodall 1966), but also amenable to curb zoning types. For a specified, the-modes algorithm finds the top vectors that minimize a distance to all sample vectors in the training dataset. The resulting top modes are representative of distinct clusters of sample vectors, with cluster membership determined by the closest mode. The parameter is chosen through cross-validation by holding out portions of the available training data and finding the smallest that largely minimizes the within-cluster variation in this hold-out set (also called the “elbow method”). We utilize basic matching dissimilarity, as implemented in (Vos 2015). For two vectors and of length, where each element attains categorical values, matching dissimilarity is defined as, where denotes the indicator vector, with value 1 where the bracketed condition is true and 0 otherwise. We’ve chosen this measure of dissimilarity between two sets of categorical variables for a number of reasons: 1) its simplicity, 2) successful use in categorical data clustering (Goodall 1966), and 3) its sensitivity to the ordering of values when vectors and are ordered, specific to how we have chosen to represent curb zoning data.

Authors: Thomas MaxnerDr. Andisheh Ranjbari, Chase Dowling

Recommended Citation:
Dowling, Chase P., Thomas Maxner, and Andisheh Ranjbari. 2022. “An Empirical Taxonomy of Common Curb Zoning Configurations in Seattle.” Findings, February. https://doi.org/10.32866/001c.32446

Paper

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

Download PDF (5.23 MB)

URL: https://doi.org/10.1177%2F0361198119849062

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

Publication Date: 2019

Summary:

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.

Authors: Gabriela Girón-ValderramaJosé Luis Machado LeónDr. Anne Goodchild

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.

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

Project Budget: $180,000 (UW amount: $80,000)

Lead Institution:

University of Washington, Urban Freight Lab (UFL)

Partner Institutions:

Oregon State University

Summary:

This study will use a driving simulator to design a simulation experiment to test the behavior of commercial vehicle drivers under various parking and delivery situations and to analyze their reactions. The ability to modify the simulator’s environment will allow the researchers to relatively easily test a range of scenarios that correspond to different delivery and parking situations.

The simulation experience will be designed in a quarter-cab truck simulator at Oregon State University’s Driving and Bicycling Simulator Laboratory. Various simulation environments will be defined by changing road characteristics (such as land use, number of travel lanes, nearby signals, traffic in adjacent lanes), curb allocations (such as paid parking, commercial vehicle loading zones, and passenger load zones, as well as the size of the loading zones and their availability at the time of the vehicle arrival at the blockface), and other road users (passenger cars, ridehailing vehicles, bikes). Drivers from various categories of age, gender, experience level (less experiences vs. seasoned) and goods type (documents, packages, or heavy goods) will be invited to operate the simulator and make a parking decision in a few simulated environments. The simulator can also monitor distraction (through eye tracking) and the stress level of drivers (through galvanic skin response) when making these decisions and interacting with other road users.

Analyzing parking decisions and driver stress levels based on roadway and driver characteristics will provide insights on travel behaviors and the parking decision-making process of commercial vehicle drivers, and will help city planners improve street designs and curb management policies to accommodate safe and efficient operations in a shared urban roadway environment.

The unique needs of delivery trucks and commercial vehicles are not acknowledged in current design practices. This study is intended to fill these gaps and serve as a valuable resource for policy makers, transportation engineers and urban planners.

Urban Delivery Companies’ Needs and Preferences for Green Loading Zones’ Implementation: A Case Study of NYC

Download PDF (0.43 MB)

URL: https://doi.org/10.1061/9780784484340

Publication: International Conference on Transportation and Development 2022

Publication Date: 2022

Summary:

Green loading zones (GLZs) are curb spaces dedicated to the use of electric or alternative fuel (“green”) delivery vehicles. Some US cities have begun piloting GLZs to incentivize companies to purchase and operate more green vehicles. However, there are several questions to be answered prior to a GLZ implementation, including siting, potential users, and their willing to pay. We reviewed best practices for GLZs around the world and surveyed goods delivery companies operating in New York City to collect such information for a future GLZ pilot. The findings suggest the best candidate locations are areas where companies are currently subject to the most parking fines and double parking. Companies expressed willingness to pay for GLZs, as long as deploying green vehicles in the city can offset other cost exposures. Respondents also selected several single-space GLZs spread throughout a neighborhood as the preferred layout.

Authors: Thomas MaxnerNota GoulianouDr. Andisheh RanjbariDr. Anne Goodchild