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Paper

Intersections and Non-Intersections: A Protocol for Identifying Pedestrian Crash Risk Locations in GIS

 
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Publication: International Journal of Environmental Research and Public Health
Volume: 16 (19)
Pages: 3565
Publication Date: 2019
Summary:

Intersection and non-intersection locations are commonly used as spatial units of analysis for modeling pedestrian crashes. While both location types have been previously studied, comparing results is difficult given the different data and methods used to identify crash-risk locations. In this study, a systematic and replicable protocol was developed in GIS (Geographic Information System) to create a consistent spatial unit of analysis for use in pedestrian crash modeling. Four publicly accessible datasets were used to identify unique intersection and non-intersection locations: Roadway intersection points, roadway lanes, legal speed limits, and pedestrian crash records. Two algorithms were developed and tested using five search radii (ranging from 20 to 100 m) to assess the protocol reliability. The algorithms, which were designed to identify crash-risk locations at intersection and non-intersection areas detected 87.2% of the pedestrian crash locations (r: 20 m). Agreement rates between algorithm results and the crash data were 94.1% for intersection and 98.0% for non-intersection locations, respectively. The buffer size of 20 m generally showed the highest performance in the analyses. The present protocol offered an efficient and reliable method to create spatial analysis units for pedestrian crash modeling. It provided researchers a cost-effective method to identify unique intersection and non-intersection locations. Additional search radii should be tested in future studies to refine the capture of crash-risk locations.

Authors: Haena Kim, Mingyu Kang, Anne Moudon, Linda Ng Boyle,
Recommended Citation:
Kang, Mingyu, Anne Vernez Moudon, Haena Kim, and Linda Ng Boyle. 2019. Intersections and Non-Intersections: A Protocol for Identifying Pedestrian Crash Risk Locations in GIS. International Journal of Environmental Research and Public Health 16, no. 19: 3565. https://doi.org/10.3390/ijerph16193565

Freight and Bus Lane (FAB) Data Collection and Evaluation Plan (Route 40)

The Urban Freight Lab (UFL) was approached by the Seattle Department of Transportation (SDOT) to complete a review of proposed evaluation criteria and propose a data collection plan in preparation for the implementation of a Freight and Bus Lane (FAB) Lane in Fall 2024 for King County Metro’s Bus Route 40.

This project would effectively produce the follow-on scope of work for the UFL to complete during the actual implementation (pre/post/post phase). UFL will build on the findings from the Urban Freight Lab’s Freight and Transit Lane Case Study completed in 2019. With the completion of the Route 40 TPMC project in Fall 2024, FAB lanes will be tested as a pilot in select locations and evaluated before permanent installation.

Objectives

  • Refresh literature review on freight and transit lane studies
  • Meet with key stakeholders from SDOT and Metro to understand data collection tools and methodologies
  • Propose a technical evaluation plan for this pilot that includes data collection and metrics and communication strategies

Revenue-Related Strategies for New Mobility Options

The Urban Freight Lab (UFL) is partnering with ECONorthwest and Cityfi to develop a research product for the National Cooperative Highway Research Program (NCHRP) on the topic of revenue strategies for new mobility options. The team will analyze the public sector’s potential role in using revenue-related strategies to encourage or discourage new mobility options in personal mobility and goods delivery.

Transportation services often operate in publicly owned and publicly managed spaces, make use of public rights-of-way, and produce mobility benefits for a broad array of users. The public sector is responsible for managing and pricing those rights-of-way and delivering services in an equitable way. Recovering the public costs of management and provisioning from private transportation services and their users is essential for maintaining public benefit. And sometimes the public sector needs to help private services to thrive.

The research methodology for this project is designed to be iterative: activities and research will build on previous research and activities. We will begin with the development of a revenue framework informed by a broad review of the literature, a policy scan, and workshop sessions with transportation and other public agency representatives that regulate and collect revenue from new mobility services. The framework will include revenue-related strategies based on:

    • (a) identifiable need
    • (b) nexus to cost responsibility
    • (c) policy outcome
    • (d) other factors such as access to technology and ease of administration.

We will then take a deeper dive into each personal mobility mode and goods delivery market segment to apply the framework. We will also provide examples to illustrate the opportunities and challenges of a variety of revenue strategies. We will also conduct additional workshops with public agency representatives, industry representatives, and other transportation stakeholders. Finally, we will create a spreadsheet-based Revenue Calculator that allows interested individuals to estimate how much revenue could be generated using different assumptions and strategies. The work will culminate with the development of a Toolkit that will be submitted to NCHRP and made available for wider distribution.

Objectives

The objective of this research is to develop a toolkit for transportation agencies that addresses how revenue-related strategies (e.g., taxes, fees, and subsidies) support policy objectives and shape the deployment of new mobility options. The toolkit will assist agencies to develop, evaluate, implement, and administer revenue-related strategies for new mobility options that transport people and goods.

The research will include:

  1. New and evolving transportation options for people and goods that interact with the existing built environment and travel throughout an area
  2. Incentives and disincentives that result from revenue-related strategies
  3. Policy implications of revenue-related strategies for new mobility options including revenue potential, mobility, travel demand, safety, equity, environment, economic development, infrastructure design, operations, and maintenance
  4. Mechanisms for revenue collection and distribution for different mobility options in different scenarios
  5. The ease and difficulty of implementing and enforcing different revenue-related strategies for new mobility options
  6. Potential roles and responsibilities of governmental organizations and private entities

Managing Increasing Demand for Curb Space in the City of the Future

This research aims to develop innovative methods for managing curb lane function and curb access. The rapid rise of autonomous vehicles (AV), on-demand transportation, and e-commerce goods deliveries, as well as increased cycling rates and transit use, is increasing demand for curb space resulting in competition between modes, failed goods deliveries, roadway and curbside congestion, and illegal parking.

The research findings will improve mobility by increasing the understanding of existing curb usage and provide new solutions to city officials, planners, and engineers responsible for managing this scarce resource in the future.

The research team will work closely with several cities in the PacTrans region to ensure the study’s relevance to their needs, and that the results will be broadly applicable for other cities.

This research will allow for the development of innovative curb space designs and ensure that our urban street system may operate more efficiently, safely, and reliably for both goods and people.

Technical Report

Analyzing the Long-Term Impacts of COVID-19 Disruption on Travel Patterns

 
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Publication Date: 2020
Summary:

The rapid spread of COVID-19 pandemic in the U.S. spurred many state governments to take extensive actions for social distancing and issue stay-at-home orders to reduce the spread of the virus. Washington State and all other States in the PacTrans region have issued stay-at-home orders that include school closures, telecommuting, bars/restaurants closures, and group gathering bans, among others. These actions create significant changes to daily life and while some travel patterns will gradually restore by the end of outbreak, some may remain changed for a much longer period.

Behaviors that may see a lasting response include commuting, grocery shopping, business meetings, and even social interactions. Working from home for 2-3 months may change people’s attitudes toward telecommuting, and some may continue to do so a few days a week once the stay-at-home orders are lifted. Some employers may also shift their telecommute policies and provide/encourage working from home. In recent years, with the growth of e-commerce, many grocery stores had started to offer home deliveries; however, online grocery shopping experienced a fast and sudden boom during the pandemic. This has resulted in quick service adoption, and therefore some people may continue to do online grocery shopping once things go back to normal. Moreover, as people shift to online grocery shopping, they may proactively make a list and place orders less frequently compared to them going to store, resulting in fewer shopping trips. Some business meetings and even personal gatherings may also move online as people learn about and try alternate ways of communicating during the outbreak. Some may also consider enrolling in distant learning programs instead of attending in-person educational programs. There may also be significant changes in modes of travel. Some transit commuters may choose other modes of transportation for a while, and people may choose to drive or bike instead of taking a ride-hailing trip.

The goal of this research is to understand how COVID-19 disruption has affected people’s activity and travel patterns during the pandemic, and how these changes may persist in a post-pandemic era.

Authors: Dr. Andisheh Ranjbari, Parastoo Jabbari, Don MacKenzie
Recommended Citation:
Mackenzie D., Jabbari P., Ranjbari A. Analyzing the Long-Term Impacts of COVID-19 Disruption on Travel Patterns. Pacific Northwest Transportation Consortium (PacTrans). 2020. http://hdl.handle.net/1773/46655.
Paper

The Automated Driver as a New Road User

 
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Publication: Transport Reviews
Pages: 23-Jan
Publication Date: 2020
Summary:

Although road infrastructure has been designed to accommodate human drivers’ physiology and psychology for over a century, human error has always been the main cause of traffic accidents. Consequently, Advanced Driver Assistance Systems (ADAS) have been developed to mitigate human shortcomings. These automated functions are becoming more sophisticated allowing for Automated Driving Systems (ADS) to drive under an increasing number of road conditions. Due to this evolution, a new automated road user has become increasingly relevant for both road owners and the vehicle industry alike. While this automated driver is currently operating on roads designed for human drivers, in the future, infrastructure policies may be designed specifically to accommodate automated drivers. However, the current literature on ADSs does not cover all driving processes. A unified framework for human and automated driver, covering all driving processes, is therefore presented. The unified driving framework, based on theoretical models of human driving and robotics, highlights the importance of sensory input in all driving processes. How human and automated drivers sense their environment is therefore compared to uncover differences between the two road users relevant to adapt road design and maintenance to include the automated driver. The main differences identified between human and automated drivers are that (1) the automated driver has a much greater range of electromagnetic sensitivity and larger field of view, and (2) that the two road users interpret sensory input in different ways. Based on these findings, future research directions for road design and maintenance are suggested.

Authors: Dr. Ed McCormack, Ane Dalsnes Storsaeter, Kelly Pitera
Recommended Citation:
Storsæter, A. D., Pitera, K., & McCormack, E. D. (2020). The automated driver as a new road user. Transport Reviews, 1–23. https://doi.org/10.1080/01441647.2020.1861124
Paper

Bringing Alleys to Light: An Urban Freight Infrastructure Viewpoint

 
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Publication: Cities
Volume: 105
Publication Date: 2020
Summary:

There is growing pressure in cities to unlock the potential of every public infrastructure element as density and demand for urban resources increase. Despite their historical role as providing access to land uses for freight and servicing, alleys have not been studied as a resource in modern freight access planning.

The authors developed a replicable data collection method to build and maintain an alley inventory and operations study focused on commercial vehicles. A Seattle Case study showed that 40% of the urban center city blocks have an alley. 90% of those alleys are wide enough to accommodate only a single lane for commercial vehicles. 437 parking operations were recorded in seven alleys during business hours and found that all alleys were vacant 50% of the time.

This confirms that, in its alleys, Seattle has a valuable resource as both space for freight load/unload; and direct access to parking facilities and business entrances for commercial, private, and emergency response vehicles.

However, alley design features and the prevalence of parking facilities accessed through the alley may restrict the freight load/unload space in the alley. Future efforts should investigate how to better manage these infrastructures.

Recommended Citation:
Machado-León, Girón-Valderrama, G. del C., & Goodchild, A. (2020). Bringing Alleys to Light: An Urban Freight Infrastructure Viewpoint. Cities, 105. https://doi.org/10.1016/j.cities.2020.102847 

Freight and Transit Lane Study (Task Order 7)

The City of Seattle Department of Transportation (SDOT) engaged the Urban Freight Lab to conduct research on the impacts of a Freight and Transit-Only (FAT) Lane in place in January 2019. The research findings will be used to understand the FAT Lane’s performance towards achieving city goals and to guide the development of future FAT Lane projects.

The Seattle Freight Master Plan includes a FAT Lane strategy to reach the city’s economic goals:

  • (2) Economy – Provide a freight network that supports a thriving and diverse economy for Seattle and the region.
  • (2.4) Maintain and improve truck freight mobility and access between and within the city’s MICs and to the regional highway system
  • (2.4.2) Explore and test the use of truck-only lanes to improve freight mobility on city streets with high truck volumes

SDOT’s key research interests in this project are to:

  1. Document whether the FAT Lane’s benefits to truck drivers were strong enough to attract heavy freight vehicles from using other downtown streets. This will be measured by comparing truck volume on the Lane during implementation to volume after it was closed.
  2. Determine whether passenger cars followed the posted FAT Lane restrictions. This will be measured by documenting the number of cars violating the rule.
  3. Document transit use during the implementation period.

Background:

The Alaskan Way Viaduct, a major freight thoroughfare in Seattle, was closed on January 11, 2019 significantly reducing capacity in the already congested road network in Greater Downtown Seattle. To improve freight and transit access to commercial and industrial areas in the city, the City of Seattle Department of Transportation, in partnership with the WSDOT, temporarily installed two blocks of a Freight and Transit Lane on Alaskan Way.

The FAT Lane was in the curb lane only, on southbound Alaskan Way (at street level, not on the Viaduct). The 2-block segment is north of Little H on Alaskan Way, which provides access to Colorado and Alaskan Way. The FAT Lane supported Port of Seattle operations.

Research Tasks:

The following tasks will be completed by the Urban Freight Lab:

Task 1 – Research Scan

Subtasks:

  1. Conduct a short research scan of published reports that provide data-based evidence of the results of FAT Lane projects.
  2. Write a 2-3 page summary of the results of other FAT Lane projects

Task 2 – Analysis of video data

Subtasks:

  1. SDOT will provide video of the FAT Lane segment taken when the Lane was open and after it closed, to the UFL. The UFL will categorize and count vehicles in the lane as follows:
    • Transit/bus
    • Passenger/car
    • Truck/freight:
      1. Drayage with container
      2. Drayage without container
      3. All other trucks/freight vehicles. This category includes: delivery vans/trucks, construction and waste vehicles, and if readily apparent service commercial vehicles.
    • Other vehicles, e.g. those lacking differentiating features to categorize.
  2. UFL will analyze the count data and include key findings in the final report. The analysis will include:
    1. A comparison of truck volume on the Lane during implementation to the volume after it was closed. This may include time of day, day of week, or other factors.
    2. The number of passenger cars in the Lane during implementation. e.g. the number of violators.
    3. The UFL researchers will also explore whether comparing data collected in the Greater Downtown Cordon study to data collected in this study yields valid findings.
Paper

Analyzing the Effect of Autonomous Ridehailing on Transit Ridership: Competitor or Desirable First-/Last-Mile Connection?

 
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Publication: Transportation Research Record
Volume: 2675 (11)
Pages: 1154-1167
Publication Date: 2021
Summary:

Ridehailing services (e.g., Uber or Lyft) may serve as a substitute or a complement—or some combination thereof—to transit. Automation as an emerging technology is expected to further complicate the current complex relationship between transit and ridehailing. This paper aims to explore how US commuters’ stated willingness to ride transit is influenced by the price of ridehailing services and whether the service is provided by an autonomous vehicle. To that end, a stated preference survey was launched around the US to ask 1,500 commuters how they would choose their commute mode from among choices including their current mode and other conventional modes as well as asking them to choose between their current mode and an autonomous mode. Using a joint stated and revealed preference dataset, a mixed logit model was developed and analyzed.

Authors: Dr. Andisheh Ranjbari, Moein Khaloei, Ken Laberteaux, Don MacKenzie
Recommended Citation:
Khaloei, M., Ranjbari, A., Laberteaux, K., & MacKenzie, D. (2021). Analyzing the Effect of Autonomous Ridehailing on Transit Ridership: Competitor or Desirable First-/Last-Mile Connection? Transportation Research Record, 2675(11), 1154–1167. https://doi.org/10.1177/03611981211025278

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

 
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Publication: Transportation Research Part A: Policy and Practice
Volume: 147
Pages: 320-338
Publication Date: 2021
Summary:

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

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

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