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Chapter

Are Cities’ Delivery Spaces in the Right Places? Mapping Truck Load/Unload Locations

 
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Publication: City Logistics 2: Modeling and Planning Initiatives (Proceedings of the 2017 International Conference on City Logistics)
Volume: 2
Pages: 351-368
Publication Date: 2018
Summary:

Two converging trends – the rise of e‐commerce and urban population growth – challenge cities facing competing uses for road, curb and alley space. The University of Washington has formed a living Urban Freight Lab to solve city logistics problems that cross private and public sector boundaries. To assess the capacity of the city’s truck load/unload spaces, the lab collected GIS coordinates for private truck loading bays, and combined them with public GIS layers to create a comprehensive map of the city’s truck parking infrastructure. The chapter offers a practical approach to identify useful existent urban GIS data for little or no cost; collect original granular urban truck data for private freight bays and loading docks; and overlay the existing GIS layers and a new layer to study city‐wide truck parking capacity. The Urban Freight Lab’s first research project is addressing the “Final 50 Feet” of the urban delivery system.

Recommended Citation:
Goodchild, Anne, Barb Ivanov, Ed McCormack, Anne Moudon, Jason Scully, José Machado Leon, and Gabriela Giron Valderrama. Are Cities' Delivery Spaces in the Right Places? Mapping Truck Load/Unload Locations: Modeling and Planning Initiatives. City Logistics 2: Modeling and Planning Initiatives (2018): 351-368. 10.1002/9781119425526.ch21

Dr. Anne Goodchild

Dr. Anne Goodchild
Dr. Anne Goodchild
  • Founder, Urban Freight Lab
  • Professor, Civil and Environmental Engineering
annegood@uw.edu  |  206-543-3747  |  Wilson Ceramics Lab 103
  • Urban goods delivery systems and land use
  • Logistics hubs and ports
  • Sustainable freight transportation systems
  • Supply chain management and freight transportation

Dr. Anne Goodchild is interested in the intersection between supply chain management and freight transportation. As an example of this, recent research is evaluating the changing nature of shopping and implications for goods delivery on CO2 emissions, local pollutants, and vehicle miles travelled. Her interest in economic and environmental sustainability is also demonstrated by her work looking at CO2 emissions in strategic routing and schedule planning in urban pick-up and delivery systems. Dr. Goodchild’s work in understanding supply chains, as they relate to the transport system, is demonstrated by her research funded by the SHRP2 freight data and modeling program, NCFRP 20, the FHWA’s Behavioral based National Freight Demand Model, and surveys and analysis funded by both the Washington and Oregon Departments of Transportation.

  • Innovation in Education Award, Institute of Transportation Engineers (ITE) Transportation Education Council (2021)
  • Outstanding Researcher Award, Pacific Northwest Transportation Consortium (PacTrans) (2021)
  • Outstanding Mentor Award, Department of Civil and Environmental Engineering (2020)
  • Person of the Year, Transportation Club of Seattle (2017)
  • Allan and Inger Osberg Endowed Professorship (2012 – 2016)
  • Community of Innovators Junior Faculty Research Award, College of Engineering (2012)
  • 2nd Prize, College-Industry Council on MH Education Outstanding Material Handling and Logistics paper (2008)
  • Dissertation Prize Honorable Mention, INFORMS Transportation Science and Logistics (2006)
  • PRISMS Presentation Competition Finalist, Institute for Operations Research and Management Science (2003)
  • Ph.D., Civil and Environmental Engineering, UC Berkeley (2005)
    (Dissertation: Crane Double Cycling in Container Ports: Algorithms, Evaluation, and Planning)
  • M.S., Civil and Environmental Engineering, UC Berkeley (2003)
  • B.S., Mathematics, UC Davis (1995)

Dr. Anne Goodchild leads the University of Washington’s academic and research efforts in the area of supply chain, logistics, and freight transportation. She is Professor of Civil and Environmental Engineering and Founder of both the Supply Chain Transportation & Logistics online Master’s degree program and the Urban Freight Lab (UFL).

Under Goodchild’s leadership, the UFL coined the increasingly used term “Final 50 Feet” and defined it as the last leg of the supply chain for urban deliveries—including finding parking, moving items from a delivery vehicle, navigating traffic, sidewalks, intersections, bike lanes, and building security, and ending with the recipient. In addition to being key to customer satisfaction, this final segment is both the most expensive (where an estimated 25-50% of total supply chain costs are incurred) and most time-consuming part of the delivery process—and ripe for improvement. One of the hurdles in the final 50 feet is that many different parties are involved—city departments of transportation, delivery carriers, property owners, residents, and consumers—making a collaborative effort between sectors essential for developing mutually beneficial solutions. Using a systems engineering approach, the UFL has completed innovative research projects that provide foundational data and proven strategies, such as:

Dr. Goodchild’s contributions to transportation engineering in the U.S. and abroad have been significant. She is an expert in international border and port operations and has been instrumental in bringing supply chain concepts to freight model architectures. She has worked at the forefront of GPS data applications, identifying observable transportation characteristics that statistically predict transportation behavior.

She is the author or co-author of more than 100 research publications, and serves as associate editor for the peer-reviewed scientific journal Transportation Letters. From 2016 to 2018 she chaired the National Academies of Science, Engineering, and Medicine’s Transportation Research Board (TRB) Freight and Marine Chairs group, the top national research organization in her field. She teaches logistics and analysis, global trade, transportation & logistics management, and advises graduate students in transportation engineering, and has won several teaching and research awards.

Dr. Goodchild is the recipient of numerous research grants, including recent awards from the U.S. Department of Transportation, PacTrans (Regional University Transportation Center for Federal Region 10), Seattle Department of Transportation, Federal Highway Administration’s Strategic Highway Research Program (SHRP2), TRB’s National Cooperative Freight Research Program, and the Washington and Oregon State Departments of Transportation.

Dr. Goodchild holds both a doctorate (2005) and a master’s degree (2003) in civil and environmental engineering from the University of California, Berkeley, and a bachelor’s degree (with high honors) in mathematics from University of California, Davis. Before earning her Ph.D. she worked for PricewaterhouseCoopers LLP and Applied Decision Analysis Inc. in Europe and North America designing efficient airline schedules and optimizing research portfolios. She joined the Department of Civil and Environmental Engineering faculty at the University of Washington in 2005. In addition, she holds a Visiting Professorship at the University of Gothenburg in Sweden and a Research Affiliateship at Urban@UW (an initiative of the Office of Research and CoMotion at the University of Washington).

  • Adjunct Professor, Industrial & Systems Engineering, University of Washington
  • Visiting Professor, School of Business, Economics and Law, University of Gothenburg (Sweden)
  • Affiliate, Urban @ UW, University of Washington
  • Co-Chair, Aurora Urban Freight Consortium
  • Member, NECTAR (The Network on European Communications and Transport Activity Research) Cluster 3 Organizing Committee, Logistics and Freight
  • Member, Washington State Freight Advisory Committee (Chair, 2011-2013)
  • Organizing Committee, International Urban Freight Conference (I-NUF), Long Beach, CA (2017, 2019, 2021)
  • Associate Editor, Transportation Research Record (TRR) (2019-2020)
  • Member, National Academies of Sciences, Engineering, and Medicine, Transportation Research Board (TRB), Taskforce on Development of Freight Fluidity Performance Measures (2016-2019)
  • Group Chair, National Academies of Sciences, Engineering, and Medicine, Transportation Research Board (TRB), Freight Group (2016-2019)
  • Chair, National Academies of Sciences, Engineering, and Medicine, Transportation Research Board (TRB), Freight and Marine Chairs Group (2016-2018)
  • Chair, National Academies of Sciences, Engineering, and Medicine, Transportation Research Board (TRB) Standing Committee on Intermodal Freight Transportation (AT045) (2013-2016)
  • Member, National Academy of Sciences, Committee for Study of Freight Rail Transportation and Regulation (2014-2015)
  • Editor, International Journal of Logistics and Transportation Research (2013-2014)
  • Member, Puget Sound Regional Council Freight Advisory Panel (2008-2011)
Report

The Final 50 Feet of the Urban Goods Delivery System: Completing Seattle’s Greater Downtown Inventory of Private Loading & Unloading Infrastructure (Phase 2)

 
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Publication Date: 2020
Summary:

This report describes the Urban Freight Lab (UFL) work to map the locations of all private loading docks, loading bays, and loading areas for commercial vehicles in Seattle’s First Hill and Capitol Hill neighborhoods and document their key design and capacity features, as part of our Final 50 Feet Research Program.

Taken together with the UFL’s earlier private freight infrastructure inventory in Downtown Seattle, Uptown, and South Lake Union, this report finalizes the creation of a comprehensive Greater Downtown inventory of private loading/unloading infrastructure. The Seattle Department of Transportation (SDOT) commissioned this work as part of its broader effort with UFL to GIS map the entire Greater Downtown commercial load/unload network, which includes alleys, curbs and private infrastructure.

The research team could find no published information on any major U.S. or European city that maintains a database with the location and features of private loading/unloading infrastructure (meaning, out of the public right of way): Seattle is the first city to do so.

By supporting and investing in this work, SDOT demonstrates that it is taking a high-level conceptual view of the entire load/unload network. The city will now have a solid baseline of information to move forward on myriad policy decisions. This commitment to creating a private load/unload infrastructure inventory is significant because infrastructure is often identified as an essential element in making urban freight delivery more efficient. But because these facilities are privately owned and managed, policymakers and stakeholders lack information about them—information critical to urban planning. By and large, this private infrastructure has been a missing piece of the urban freight management puzzle. The work represented in this section fills a critical knowledge gap that can help advance efforts to make urban freight delivery more efficient in increasingly dense, constrained cities, like Seattle.

Without having accurate, up-to-date information on the full load/unload network infrastructure—including the private infrastructure addressed here—cities face challenges in devising effective strategies to minimize issues that hamper urban freight delivery efficiency, such as illegal parking and congestion. Research has shown that these issues are directly related to infrastructure (specifically, a lack thereof). (4) A consultant report for the New York Department of Transportation found that the limited data on private parking facilities for freight precluded development of solutions that reduce double parking, congestion and other pertinent last-mile freight challenges. (5) The report also found that the city’s off-street loading zone policy remained virtually unchanged for 65 years (despite major changes like the advent and boom of e-commerce.)

Local authorities often rely heavily on outside consultants to address urban freight transport issues because these authorities generally lack in-house capacity on urban freight. (6) Cities can use the replicable data-collection method developed here to build (and maintain) their own database of private loading/unloading infrastructure, thereby bolstering their in-house knowledge and planning capacity. Appendix C includes a Step-by-Step Toolkit for a Private Load/Unload Space Inventory that cities, researchers, and other parties can freely use.

The method in that toolkit builds—and improves—on the prior data-collection method UFL used to inventory private infrastructure in the dense urban neighborhoods of Downtown Seattle, Uptown and South Lake Union in early 2017 (Phase 1). The innovative, low-cost method ensures standardized, ground-truthed, high-quality data and is practical to carry out as it does not require prior permission and lengthy approval times to complete.

This inventory report’s two key findings are:

  1. Data collectors in this study identified, examined, and collected key data on 92 private loading docks, bays and areas across 421 city blocks in the neighborhoods of Capitol Hill, First Hill, and a small segment of the International District east of I-5. By contrast, the early 2017 inventory in Downtown Seattle, Uptown, and South Lake Union identified 246 private docks, bays and areas over 523 blocks—proportionally more than twice the density of private infrastructure of Capitol Hill and First Hill. This finding is not surprising. While all the inventoried neighborhoods are in the broad Greater Downtown, they are fundamentally different neighborhoods with different built environments, land use, and density. Variable demand for private infrastructure—and the resulting supply—stems from those differences.
  2. A trust relationship with the private sector is essential to reduce uncertainty in this type of work. UFL members added immense value by ground-truthing this work and playing an active role in improving inventory results. When data collectors in the field found potential freight loading bays with closed doors (preventing them from assessing whether the locations were, in fact, used for freight deliveries), UPS had their local drivers review the closed-door locations as part of their work in the Urban Freight Lab. The UPS review allowed the researchers to rule out 186 of the closed-door locations across this and the earlier 2017 data collection, reducing uncertainty in the total inventory from 33% to less than 1%.

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 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. (7) One of the pilot’s goals is to add more parking capacity by using private infrastructure more efficiently, such as by inviting building managers in the test area to offer off-peak load/unload space to outside users. The U.S. Department of Energy’s Office of Energy Efficiency and Renewable Energy under the Vehicles Technologies Office is funding the project.

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.

Recommended Citation:
Urban Freight Lab (2020). The Final 50 Feet of the Urban Goods Delivery System: Phase 2, Completing Seattle’s Greater Downtown Inventory of Private Loading/Unloading Infrastructure.
Technical Report

Changing Retail Business Models and the Impact on CO2 Emissions from Transport: E-commerce Deliveries in Urban and Rural Areas

 
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Publication: Pacific Northwest Transportation Consortium (PacTrans)
Volume: 2013-S-UW-0023
Publication Date: 2014
Summary:

While researchers have found relationships between passenger vehicle travel and smart growth development patterns, similar relationships have not been extensively studied between urban form and goods movement trip-making patterns. In rural areas, where shopping choice is more limited, goods movement delivery has the potential to be relatively more important than in more urban areas. As such, this work examines the relationships between certain development pattern characteristics including density and distance from warehousing. This work models the amount of carbon dioxide (CO2), nitrogen oxides (NOx), and Particle Matter (PM10) generated by personal travel and delivery vehicles in several different scenarios, including various warehouse locations. Linear models were estimated via regression modeling for each dependent variable for each goods movement strategy. Parsimonious models maintained nearly all of the explanatory power of more complex models and relied on one or two variables – a measure of road density and a measure of distance to the warehouse. Increasing road density or decreasing the distance to the warehouse reduces the impacts as measured in the dependent variables (vehicle miles traveled (VMT), CO2, NOx, and PM10). The authors find that delivery services offer relatively more CO2 reduction benefit in rural areas when compared to CO2 urban areas, and that in all cases delivery services offer significant VMT reductions. Delivery services in both urban and rural areas, however, increase NOX and PM10 emissions.

Authors: Dr. Anne Goodchild, Erica Wygonik
Recommended Citation:
Goodchild, Anne, and Erica Wygonik. Changing retail business models and the impact on CO2 emissions from transport: e-commerce deliveries in urban and rural areas. No. 2013-S-UW-0023. Pacific Northwest Transportation Consortium, 2014.

Biking the Goods: How North American Cities Can Prepare for and Promote Large-Scale Adoption

With the rise in demand for home deliveries and the boom of the e-bike market in the U.S., cargo cycles are becoming the alternative mode of transporting goods in urban areas. However, many U.S. cities are struggling to decide how to safely integrate this new mode of transportation into the pre-existing urban environment.

In response, the Urban Freight Lab is developing a white paper on how cities can prepare for and promote large-scale adoption of cargo cycle transportation. Sponsors include freight logistics providers, bicycle industry leaders, and agencies Bosch eBike Systems, Fleet Cycles, Gazelle USA, Michelin North America, Inc., Net Zero Logistics, the Seattle Department of Transportation, and Urban Arrow.

The Urban Freight Lab is internationally recognized as a leader in urban freight research, housing a unique and innovative workgroup of private and public stakeholders and academic researchers working together to study and solve urban freight challenges. The Urban Freight Lab has previously worked on evaluating, studying, and deploying cargo cycles in Asia and the U.S, and is recognized as an expert leader in North America on cargo cycle research.

Objectives
The objectives of the white paper are the following:

  1. Define and understand what types of cargo bikes exist in North America, their main features, how they are operated, and the infrastructure they need.
  2. Identify opportunities for and challenges to large-scale adoption of cargo cycles in North American cities.
  3. Learn from case studies of U.S. cities’ approaches to regulating and promoting cargo cycles.
  4. Provide recommendations for how cities can safely recognize, enable and encourage large-scale adoption of cargo bikes, including infrastructure, policy, and regulatory approaches.
Paper

Truck Trip Generation by Grocery Stores

 
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Publication: Washington State Transportation Innovations Unit and Washington State Transportation Commission
Publication Date: 2010
Summary:
Quantifying the relationship between the number and types of truck trips generated by different land uses provides information useful for traffic demand analyses, forecasting models, and a general understanding of the factors that affect truck mobility. This project evaluated data collection methodologies for determining truck trip generation rates by studying a specific kind of establishment. This effort focused on grocery stores and collected both interview and manual count data from eight supermarkets in the Puget Sound region.
We selected grocery stores for this project because they constitute a common land use that is present in almost every type of neighborhood in the metropolitan region. Grocery stores generate truck trips that have the potential to affect all levels of the transportation roadway network, from local roads in neighborhoods to highways. The eight stores in the Puget Sound region identified for this study were diverse and included both national and local chains. The stores ranged in size from 23,000 to 53,500 square feet and included a variety of urban and suburban locations.
Methodologies for gathering trip generation information were identified in the literature. Telephone interviews and manual counts, which are frequently used data collection methodologies, were explored in this project. The project started with telephone interviews of four distribution centers. This step helped to refine the interview approach and helped to determined that data from larger warehouses could not be easily used to develop information on the number of trips traveling to individual stores. A second round of interviews, lasting between 10 and 15 minutes, was then conducted with the managers or receivers of the nine grocery stores. In addition to the number of truck trips that the store generated, the interviews explored a range of topics related to the busiest days and their delivery windows. This information was used to set up manual, on-site truck counts at each of the grocery stores.
We concluded that a combination of telephone interviews and manual counts is a reasonable way to collect accurate truck trip generation rates. Telephone interviews were an important first step. They established contact with grocery stores, which then provided permission for on-site manual counts. Information elicited from store interviews also included the days and times when the viii truck deliveries occurred so that the manual counts could be scheduled to reflect optimal times. In addition, the interview conversations provided sometimes unanticipated but valuable information that was relevant to understanding truck trip-generation rates. Because it is cost prohibitive and inefficient to send manual counting teams to observe facilities for long shifts, information from store managers regarding their delivery windows and hours made the counts more feasible.
The Puget Sound grocery stores in the study (all of which were conventional supermarkets) generated an average of 18 truck trips per day on typical weekdays. These daily counts were probably low, as some of the stores accepted a few late deliveries outside of the receiving windows. Most of these truck arrivals occurred before noon, and the average delivery time was 27 minutes. Although peak days of the week varied across the sample set, all reported higher volumes during holidays.
The manual counts (15 site observations) provided more accurate truck trip generation rates than did telephone interviews. The interview responses indicated approximately ten to twelve trucks per day in comparison to the average of 18 trucks per day counted at each store by observers. The telephone interviewees at the grocery stores clearly underestimated the number of trucks and provided only minimal information on truck characteristics. Manual counts also provided more detailed information regarding truck type, delivery location (loading docks or front door), average delivery time, and product mix.
Few grocery store characteristics that could be directly related to truck trip generation rates were identified. The project team reviewed literature discussing both trip generation data collection and grocery store management and could not identify any specific characteristic that could be used to quantify the number of truck trips generated by different stores. While size or employment is often related to truck trips in the ITE Trip Generation Manual, this effort did not find any direct relationship with these variables, with a possible exception related to a store’s size. This finding, that smaller stores generated more trucks trips, suggests that one promising area to explore is the linkage between the level at which stores are served by regional warehouses or direct service delivery (DSD) and the number and type of truck trips. The manual counts indicated variability in the nature and size of the delivery trucks, which in turn related to ix whether the deliveries were at the front door (often small trucks and DSD) or loading dock (larger trucks from warehouses with consolidated loads). Smaller stores often use more DSD, which may result in more truck trips generated. It is also possible that smaller stores had smaller stock rooms, requiring more frequent deliveries. Other census-related variables such median household income, residential density and jobs-housing balance, were evaluated, but no significant relationships to truck trip rates were found.

 

Authors: Dr. Ed McCormack, Alon Bassok, Emily Fishkin, Chilan Ta
Recommended Citation:
McCormack, E., Ta, C., Bassok, A., & Fishkin, E. (2010). Truck Trip Generation by Grocery Stores. (No. TNW2010-04).
Paper

NCFRP Report: Smart Growth and Urban Goods Movement

 
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Publication: TR News
Volume: 295
Publication Date: 2014
Summary:

Smart growth design, a strategy for improving the quality of life in urban areas, has typically focused on the areas of passenger travel, land use and nonmotorized transport adoption. The role of goods movement is often ignored in discussions of smart growth. This article reports on National Cooperative Freight Research Program (NCFRP) Report 24, which addresses the importance of the relationship between smart growth and goods movement. A number of principles of smart growth are identified, as are areas where there are research gaps. Urban transportation forecasting models have shown that smart-growth land use offers benefits both for passenger travel and goods movement. Additionally, smart-growth improvements to transit and nonmotorized transportation have been found to offer greater benefits to trucks than do roadway investments.

Authors: Dr. Anne GoodchildDr. Ed McCormack, Alon Bassok
Recommended Citation:
McCormack, Ed, Anne Goodchild, and Alon Bassok. National Academies of Sciences, Engineering, and Medicine. 2013. Smart Growth and Urban Goods Movement. Washington, DC: The National Academies Press. https://doi.org/10.17226/22522.

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
Technical Report

Technology and Safety on Urban Roadways: The Role of ITS in WSDOT

 
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Publication: Washington State Transportation Center (TRAC)
Publication Date: 2006
Summary:

This report examines the relationship between Intelligent Transportation Systems (ITS) and safety from an urban perspective.

Existing urban ITS systems are either system-level or site-level applications. System-level ITS, such as freeway management systems or traffic signal networks, address safety concerns only indirectly. These systems are designed to improve traffic flows and thus indirectly reduce collisions caused by congestion. Other system-level ITS used to increase the efficiency of transit, commercial vehicle, and emergency service operations also benefit safety indirectly. Site-level ITS applications, such as railroad/highway crossing warnings or work zone systems, are installed to directly address safety concerns. However, these applications are limited to specific locations identified as hazardous.

Most urban crashes in Washington involve multiple vehicle collisions caused by driver error at locations that have not been identified as hazardous. Future ITS systems known collision avoidance systems (CAS) hold considerable promise for urban roadway safety because these in-vehicle devices will inform drivers of judgment errors and can do so at many locations along an urban roadway system.

A handful of ITS applications are so well tested that they can be aggressively pursued by WSDOT as tools to reduce urban crashes. Most of these applications include the various systems, such a ramp meters and incident detection, used for freeway management. Other ITS safety applications, while promising, still need to be fully documented and are best used as demonstration applications. Most of these applications involve sensor technology used to warn drivers about road and roadside hazards at specific sites. The greatest safety benefit from ITS may come from in-vehicle collision warning systems. These applications should evolve from a number of large federal research projects and private industry initiatives that are under way. Given their potential impact on safety, WSDOT should monitor applications of these projects.

Authors: Dr. Ed McCormack, Bill Legg
Recommended Citation:
McCormack, E., Legg, B. (2000). Technology and Safety on Urban Roadways: The Role of ITS in WSDOT. Research Report, Washington State Transportation Center (TRAC). Washington State Transportation Center, U.S. Department of Transportation. 
Paper

Smart Growth and Goods Movement: Emerging Research Agendas

Publication: Journal Urbanism: International Research on Placemaking and Urban Sustainability
Volume: 2-Aug
Pages: 115-132
Publication Date: 2015
Summary:

While recent urban planning efforts have focused on the management of growth into developed areas, the research community has not examined the impacts of these development patterns on urban goods movement. Successful implementation of growth strategies has multiple environmental and social benefits but also raises the demand for intra-urban goods movement, potentially increasing conflicts between modes of travel and worsening air quality. Because urban goods movement is critical for economic vitality, understanding the relation between smart growth and goods movement is necessary in the development of appropriate policies.

This paper reviews the academic literature and summarizes the results of six focus groups to identify gaps in the state of knowledge and suggest important future research topics in five sub-areas of smart growth related to goods movement: (1) access, parking, and loading zones; (2) road channelization and bicycle and pedestrian facilities; (3) land use; (4) logistics; and (5) network system management.

Authors: Dr. Anne GoodchildDr. Ed McCormack, Erica Wygonik, Alon Bassok, Daniel Carlson
Recommended Citation:
Wygonik, Erica, Alon Bassok, Anne Goodchild, Edward McCormack, and Daniel Carlson. "Smart Growth and Goods Movement: Emerging Research Agendas." Journal of Urbanism: International Research on Placemaking and Urban Sustainability 8, no. 2 (2015): 115-132.