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Technical Report

Development, Deployment, and Assessment of Activity-Based Transportation Courses

 
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Publication: U.S. Federal Highway Administration
Publication Date: 2012
Summary:

This project developed four new activity‐based transportation courses including “Traffic Signal Systems Operations and Design”, “Understanding and Communicating Transportation Data”, “Introduction to Freight Transportation”, and “Rural Highway Design and Safety”. The courses are learner‐centered in which activities completed by students form the basis for their learning. The courses were offered fourteen times to a total of 195 students. Activity books that included 142 activities were developed for the four courses. The books and all supporting materials are available on the project web site. A number of assessments and evaluations were conducted to determine how effective the courses and materials were in meeting project objectives. The active learning style was a challenge for many students, as they were required to be prepared for class and to do “active” work during class. In general, there was an acceptance of the value of the active learning environments and how they positively contributed to student learning.

Authors: Dr. Anne Goodchild, Michael Kyte, Steve Beyerlein, Shane Brown, Chris Monsere, Kelly Pitera, Ming Le
Recommended Citation:
Kyte, Michael, Steve Beyerlein, Shane Brown, Chris Monsere, Anne Goodchild, Kelly Pitera, and Ming Lee. "Development, Deployment, and Assessment of Activity-Based Transportation Courses." (2012).

Optimization of Supply and Transportation Networks in an Epidemic Situation in Collaboration with the Seattle Flu Study

The mission of the Seattle Flu Study (SFS) is to prototype city-scale capabilities for epidemic preparedness and response. One of the aims of this study is to understand methods to implement rapid interventions outside of clinical settings and within 48-72 hours of the onset of symptoms, to enable the immediate diagnosis, treatment, or isolation of flu-positive individuals.

SFS has reached out to the Supply Chain Transportation and Logistics Center at the University of Washington to test various to develop models and perform sensitivity analyses on epidemic response scenarios via simulation and mathematical optimization. Modeling will allow SFS to measure and understand questions like, “when will our supply chain break?”, “how do you prevent it from breaking?” and “how do you get drugs and tests to people if your driver workforce gets sick?”. By modeling these types of scenarios, they will be able to assess the pros and cons of various supply chain strategies and develop multiple levers that can be pulled depending on the epidemic situation including prepositioning of orders, and leveraging in-house and supplementary private transportation alternatives (FedEx, etc.).

Report

Curbing Conflicts: Curb Allocation Change Project Report

 
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Publication Date: 2019
Summary:

Like many congested cities, Seattle is grappling with how best to manage the increasing use of ride-hailing services by Transportation Network Companies (TNCs) like Uber and Lyft. According to a 2018 Seattle Times analysis, TNC ridership in the Seattle region has grown to more than five times the level it was in the beginning of 2015, providing, on average, more than 91,000 rides a day in 2018. And the newspaper reports Uber and Lyft trips are heavily concentrated in the city’s densest neighborhoods, where nearly 40,000 rides a day start in ZIP codes covering downtown, Belltown, Capitol Hill and South Lake Union.

This University of Washington (UW) study focuses on a strategy to manage TNC driver stops when picking up and dropping off passengers to improve traffic flow in the South Lake Union (SLU) area. SLU is the site of the main campus for Amazon, the online retail company. The site is known to generate a large number of TNC trips, and Amazon reports high rates of ride-hailing use for employee commutes. This study also found that vehicle picking-up/dropping-off passengers make up a significant share of total vehicle activity in SLU. The center city neighborhood is characterized by multiple construction sites, slow speed limits (25 mph), and heavy vehicle and pedestrian traffic.

Broad concerns about congestion, safety, and effective curb use led to this study, conducted by researchers at the UW’s Urban Freight Lab and Sustainable Transportation Lab. Amazon specifically was concerned about scarcity of curb space where TNC drivers could legally and readily stop to pick up and drop off passengers. Without dedicated load/unload curb space, TNC vehicles stop and wait at paid parking spots, other unauthorized curb spots, or in the travel lane itself, potentially blocking or slowing traffic. To try to mitigate the impacts of passenger pick-up/drop-off activity on traffic, the city proposed a strategy of increasing passenger loading zone (PLZ) spaces while Uber and Lyft implemented a geofence, which directs their drivers and passengers to designated pick-up and drop-off locations on a block. (Normally, drivers pick up or drop off passengers at any address a rider requests via the ride-hailing app.)

By providing ample designated pick-up and drop-off spots along the curb, the thinking goes, TNC drivers would reduce the frequency with which they stop in the travel lane to pick up or drop off passengers and the time they stay stopped there. By these measures, this study’s findings show the approach was successful. But it is important to note that the strategy is not a silver bullet for solving traffic congestion—nor is it designed as such. It is also important to note that any initiative to manage use of curbs and roads (by TNCs or others) is part of a city’s broader transportation policy framework and goals.

For this study, researchers analyzed an array of data on street and curb activity along three block-faces on Boren Ave N in December 2018 and January 2019. At a minimum, data were collected during the morning and afternoon peak travel times (with some collected 24 hours a day). The research team collected data using video and sensor technology as well as in-person observation. Researchers also surveyed TNC passengers for demographic, trip-related and satisfaction data. The five Amazon buildings in the area studied house roughly 8,650 employees. Researchers collected data in three stages. Phase 1, the study baseline, was before PLZs were added and geofencing started. Phase 2 was after the new PLZs were added, expanding total PLZ curb length from 20 feet (easily filled by one to two vehicles) to 274 feet. Phase 3 was after geofencing was added to the expanded PLZs. The added PLZ spaces were open to any passenger vehicle—not just TNC vehicles—weekdays from 7am to 10am and 2pm to 7pm. (Permitted food trucks were authorized from 10am to 2pm.)

Note that while other cities can learn from this analysis, the findings apply to streets with comparable traffic speed, mix of roadway users, and street design.

The study’s main findings include:

  • A significant percentage of vehicles performing a pick-up/drop-off stop in the travel lane. Those in-lane stops appear connected to the lack of available designated curb space: Adding PLZs and geofencing increased driver compliance in stopping at the curb versus stopping in the travel lane to load and unload passengers. But it was not lack of curb space alone that influenced driver activity: Between 7 percent and 10 percent of drivers still stopped in the travel lane even when PLZs were empty. After adding PLZs and geofencing, in-lane stops fell from 20 percent to 14 percent for pick-ups and from 16 percent to 15 percent for drop-offs.
  • Adding PLZs and geofencing reduced the average amount of time drivers stopped to load and unload passengers. For example, 90 percent of drop-offs took less than 1 minute 12 seconds, 42 seconds faster than the average with the added PLZs alone.
  • While curb occupancy increased after adding PLZs and geofencing, occupancy results show the current allocation of PLZ spaces is more than what is needed to meet observed demand: Average PLZ occupancy remained under 20 percent after PLZ expansion, even during peak commute hours.
  • Vehicles picking-up/dropping-off passengers account for a significant share of total traffic volume in the study area: during peak hours the observed average percentage of vehicles performing a pick-up/drop-off with respect to the total traffic volume was 29 percent (in Phase 1), 32 percent (in Phase 2) and 39 percent (in Phase 3).
  • High volumes of pedestrians (400-500 per hour on average) cross the street at points where there was no crosswalk. Passengers picked-up/dropped-off constituted a fraction (five to seven percent) of those pedestrians, but high rates of passengers (30 to 40 percent) cross the street at non-crosswalk locations.
  • Adding PLZs and geofencing did not have a significant impact on traffic safety. Researchers found no significant change in the number of observed conflicts from baseline to the addition of PLZs and geofencing. Conflicts are situations where a vehicle, bike, or pedestrian is interrupted, forced to alter their path, or engaged in a near-miss situation. Conflicts include vehicles passing in the oncoming traffic lane. • Adding PLZs and geofencing also did not produce a significant impact on roadway travel speed.
  • Of the 116 TNC passengers surveyed in the study area:
    • Roughly 40 percent to 50 percent said their trip was work related. More than half said they used ride-hailing service at least once a week and 70 percent or more used TNC alone (versus in combination with other transportation options) to get from their origin to their destination.
    • Most responded positively to the added PLZs and geofence: 79 percent rated their pick-up satisfactory and 100 percent rated their drop-off satisfactory as compared to 72 percent and 89 percent in the baseline.
    • Nearly half said they would have taken transit and one-third would have walked if ride-hailing was not available.
    • 40 percent requested a shared TNC vehicle in Phase 1 and 47 percent in Phase 3.

The study suggests that while vehicles picking-up/dropping-off passengers account for a significant share of traffic volume in SLU, they are not the primary cause of congestion. Myriad factors impact neighborhood congestion, including high vehicle volume overall and bottlenecks moving out of the neighborhood onto regional arterials. As researchers observed in the afternoon peak, these bottlenecks cause spillbacks onto local streets. Amazon garages exit vehicles onto streets that then feed into these clogged arterials.

Regarding traffic safety in SLU, this study was not designed to assess whether TNC driver behavior on average is safer or less safe than that of other vehicles. It is important to understand the safety and speed findings in the context of the SLU traffic environment. Drivers tend to drive at relatively slow speeds, navigating around high pedestrian and jaywalking volumes, and seem relatively comfortable stopping in the middle of the street for short periods of time. Due to the nature of area traffic, this seems to have relatively little impact on other drivers. Drivers appear to anticipate both this behavior and the high volumes of vehicles moving onto/off the curb and into/out of driveways and alleys.

Whether the strategy this study analyzed is recommended depends on a city’s transportation goals and approach. The researchers found the increased PLZ allocation and geofencing strategy worked in that it improved driver compliance, reduced dwell times, and boosted TNC user satisfaction. However, this may encourage commuters to use TNC. The passenger survey clearly shows that TNC service is attracting passengers who would have otherwise walked or used transit. While in the short term the increased PLZs and geofencing had a positive effect on traffic, if this induces TNC demand, there could be larger, more negative long-term consequences. If the end goal is to reduce traffic congestion, measures to reduce—rather than encourage—TNC and passenger car use as the predominant mode of commuting will yield the most substantial benefits.


In the news:

Geekwire: As Uber and Lyft pick-ups and drop-offs clog traffic, new study calls load zones a move in right direction

The Seattle Times: Seattle Uber and Lyft drivers often stop in the street to pick up or drop off riders. Here’s a way to reduce that.

Recommended Citation:
Goodchild, Anne. Giacomo dalla Chiara. Jose Luis Machado. Andisheh Ranjbari. (2019) Curb Allocation Change Project.

Food Rescue Collaborative Research

The Supply Chain Transportation & Logistics Center (SCTL) is conducting collaborative research with Seattle Public Utilities (SPU) to explore and share innovative approaches for moving, storing, and redistributing surplus food.

Food rescue is the process of gleaning edible food that would otherwise go into the waste stream from local businesses and re-distributing it to local food programs. SPU is building partnerships to increase this practice while striving to increase the City’s greater affordability and resilience. Transportation, storage, and logistics have been key operational barriers to increasing rescued food.

SPU commissioned SCTL to create a shared data-driven understanding of the logistics of food rescue in Seattle.

The purpose of this project is to reduce waste and increase access and food quality for customers of food banks and meal programs. Research will be conducted with both businesses that donate food and the organizations that receive it. The first phase of this project will focus on identifying ways to lower transportation, cold storage, and logistics costs of securing food and evaluating these benefits.

Ultimately, research findings could lead to creating solutions that:

  • increase supply chain transportation efficiency,
  • reduce current system redundancy across food rescue operations
  • increase collaboration across independent operations serving Seattle’s food insecure residents, and
  • increase the resiliency of food rescue operations which could ultimately enhance their ability to respond to larger City disasters, disruptions and unexpected risks.
Paper

A Competitive, Charter Air-Service Planning Model for Student Athlete Travel

Publication: Transportation Research Part B: Methodological
Volume: 45 (1)
Pages: 128-149
Publication Date: 2011
Summary:

This paper presents a model for planning an air charter service for pre-scheduled group travel. This model is used to investigate the competitiveness of such an enterprise for student athlete travel in conference sports. The relevant demand subset to be served by a limited charter fleet is identified through a comparison with existing scheduled travel options. Further, the routing and scheduling of the charter aircraft is performed within the same framework. Through this modeling a method for formulating and accommodating continuous time windows and competitive market dynamics in strategic planning for a charter service is developed. Computational improvements to the basic model are also presented and tested. The model is applied to the Big Sky Conference for the 2006–2007 season, quantifying the benefits to the students from such a service and the change in expenditure associated with such a benefit for various assumptions about operations and value of time. The findings indicate the lack of spatial or sport based patterns for maximizing benefit, indicating the absence of simplistic “rules of thumb” for operating such a service, and validating the need for the model.

Authors: Dr. Anne Goodchild, Gautam Gupta, and Mark Hansen
Recommended Citation:
Gautam Gupta, Anne Goodchild, and Mark Hansen (2011). A Competitive, Charter Air-Service Planning Model for Student Athlete Travel. Transportation Research Part B, 45, 128-149.

The Route Machine: An Optimization Framework (Phase 1)

The University of Washington Department of Laboratory Medicine runs 12 routes per day moving lab specimens and conducting departmental business. These routes have been developed over time in an ad hoc fashion.

The Urban Freight Lab will primarily focus on the following objectives for optimization:

  1. Minimize expected lead time (from the time the specimens are ready for pick up to the time they are delivered to the lab for testing)
  2. Minimize the extent to which couriers work outside of their maximum shift durations

The decisions the ‘route machine’ optimization framework ideally should inform:

  1. Day-to-day (operational) decision-making: Given all of the current capacities (i.e., number of vehicles) can routes be improved through changing order of routes or destinations serviced in route?
  2. Tactical decision-making: What modifications to the current capacities (i.e., increasing the number of vehicles) will produce the greatest benefit? How will the optimal routes change if there are modifications to customer requirements?
  3. Strategic decision-making: If UW Medicine Department of Laboratory Medicine expands its operations how will routes and capacities need to change to accommodate the new situation? What should the workforce balance between full-time workers and contractors look like?

This analysis includes:

  • Phase 1: Evaluate the existing routes on a qualitative basis to judge whether there is sufficient opportunity for improvement, and strategies that show greatest opportunity for improvement
  • Phase 1: Conduct an inventory of off the shelf tools and determine their suitability for the application
  • Phase 2: Build the Route Machine tool, either using off-the shelf software tools, building the tool from scratch, or some combination of the two.

Dynamically Managed Curb Space Pilot

Transportation Network Company (TNC) usage in Seattle has been increasing every quarter since 2015 when the City of Seattle Department of Transportation (SDOT) began collecting data. TNC trips exceeded 20 million in 2017, a 46% increase from total reported trips in 2016. This has led to concerns about congestion and pedestrian safety as cars and people take risks to connect at the curb and in the right-of-way. By providing additional curb capacity through increased passenger loading zones and directing customers via in-app messaging, the City may be able to reduce congestion and unsafe vehicle/people movements during peak traffic and late-night hours.

Other cities have attempted to study the impacts of increased usage of passenger loading zones (e.g., San Francisco, Washington D.C.), with varying success, but no standard methodology exists for cities to assess the potential for reallocated curb space and the subsequent impacts of those changes. SDOT is taking a data-driven approach to curb reallocation and traffic network impacts, modeling the work SDOT has done to quantify demand in paid parking areas and set rates accordingly. The main goals of this pilot are three-fold: increase pedestrian safety, minimize congestion impacts on the larger transportation network, and build a scalable methodology for assessment and implementation of curb allocation to accommodate this new mobility service.

The Supply Chain Transportation & Logistics Center and SDOT will work in collaboration with employers, transit operators, and TNCs to test a variety of strategies to mitigate the traffic impacts of TNC pick-ups on the greater transportation network and improve safety for passengers and drivers. Strategies include increasing the number of passenger loading zones in high-traffic pick-up areas and geofenced pick-up or black-out areas. Curb and street use data will be collected under each alternative and compared to baseline data.

Paper

A Meta-Heuristic Solution Approach to Isolated Evacuation Problems

 
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Publication: IEEE (Institute of Electrical and Electronics Engineers)
Volume: 2022 Winter Simulation Conference (WSC) INFORMS
Publication Date: 2022
Summary:

This paper provides an approximation method for the optimization of isolated evacuation operations, modeled through the recently introduced Isolated Community Evacuation Problem (ICEP). This routing model optimizes the planning for evacuations of isolated areas, such as islands, mountain valleys, or locations cut off through hostile military action or other hazards that are not accessible by road and require evacuation by a coordinated set of special equipment. Due to its routing structure, the ICEP is NP-complete and does not scale well. The urgent need for decisions during emergencies requires evacuation models to be solved quickly. Therefore, this paper investigates solving this problem using a Biased Random-Key Genetic Algorithm. The paper presents a new decoder specific to the ICEP, that allows to translate in between an instance of the S-ICEP and the BRKGA. This method approximates the global optimum and is suitable for parallel processing. The method is validated through computational experiments.

Authors: Dr. Anne GoodchildFiete Krutein, Linda Ng Boyle (University of Washington Dept. of Industrial & Systems Engineering)
Recommended Citation:
K. F. Krutein, L. N. Boyle and A. Goodchild, "A Meta-Heuristic Solution Approach to Isolated Evacuation Problems," 2022 Winter Simulation Conference (WSC), Singapore, 2022, pp. 2002-2012, doi: 10.1109/WSC57314.2022.10015470.
Presentation

Ecommerce and Environmental Justice in Metro Seattle U.S.

 
Publication: Laboratoire Ville Mobilite Transport (City Transportation Mobility Laboratory), Paris
Publication Date: 2022
Summary:

The central research question for this project explores the distributional impacts of ecommerce and its implications for equity and justice.

The research aims to investigate how commercial land use affects people and communities. In 2018, U.S. warehouses surpassed office buildings as the primary form of commercial and industrial land use, now accounting for 18 billion square feet of floor space. Warehouses have experienced significant growth in both number and square footage, becoming the predominant land use in the U.S. Warehouse expansion has strategically sprawled from port areas to suburbs in order to get closer to populations and transportation access.

The research findings reveal a correlation between warehouse locations and lower-income communities, resulting in increased exposure to air pollution and triple the traffic associated with ecommerce. Conversely, higher-income populations experience the least exposure, despite making more than half of their purchases online compared to their lower-income counterparts.

Factors such as race and proximity to highways and warehouse locations emerge as stronger predictors of the volume of freight activity through ecommerce than individuals’ income levels or the number of orders placed. Going forward, there is an opportunity for retailers and distributors to take into account the health implications of warehouse placement, and governments can provide best practices to facilitate municipal coordination, particularly where local authorities may be unaware of the impacts.

Authors: Travis Fried
Report

Analysis of Online Shopping and Shopping Travel Behaviors in West Seattle

 
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Publication Date: 2023
Summary:

The purpose of this research is to explore consumers’ online shopping and in-person shopping travel behaviors and the factors affecting these behaviors within the geographical context of the study area of West Seattle.

West Seattle is a peninsula located southwest of downtown Seattle, Washington State. In March 2020, the West Seattle High Bridge, the main bridge connecting the peninsula to the rest of the city, was closed to traffic due to its increased rate of structural deterioration. The closure resulted in most of the traffic being re-distributed across other bridges, forcing many travelers to re-route their trips in and out of the peninsula. At about the same time, the COVID-19 pandemic caused business-shuttering lockdowns. Both events fundamentally changed the nature of shopping and the urban logistics system of the study area.

The Seattle Department of Transportation (SDOT) engaged the Urban Freight Lab (UFL) at the University of Washington to conduct research to understand current freight movements and goods demands in West Seattle and identify challenges related to the bridge closure to inform data-driven mitigation strategies. The study took place in two phases: the first phase documented the challenges experienced by local businesses and carriers through a series of interviews and quantified the freight trip generated by land use in the case study area1 ; the second phase, described in the current report, performed an online survey to understand online shopping and in-person shopping travel behaviors for West Seattle residents.

The main objectives of the current study are twofold:

  • Describe online shopping and shopping travel consumer behaviors for West Seattle residents.
  • Understand what factors influence consumer shopping behaviors, from accessibility to local stores, to the characteristics of goods purchased, to socio-economic factors.

Methods

To address these objectives, the research team designed an online questionnaire that was advertised through a West Seattle Bridge Closure-related SDOT newsletter and other local online media outlets during the spring and summer of 2022. The questionnaire asked respondents about their socioeconomic conditions (age, income, education, etc.), where they live and their access to transportation (vehicle ownership and types of vehicles), their online shopping behavior, the impact of the West Seattle High Bridge closure on their shopping habits, and about their most recent purchase for a given category of goods among clothing items, groceries, restaurant food, and household supplies. The questionnaire was collected anonymously, and no personally identifiable information was collected. A total of 1,262 responses were collected, and after data processing, the final sample data consisted of 919 responses, corresponding approximately to 1 percent of the study area population.

Comparing the socioeconomic characteristics of the sample with those of the West Seattle study population it should be noted that individuals identifying themselves as white and female and of older age were oversampled, while individuals with lower than a college degree and with annual income less than $50,000 were under-sampled. Therefore, the sample in general is more representative of a more affluent, older population.

Key Findings

The key findings are summarized as follows:

Online shopping is widespread for clothing items and restaurant food.

Respondents receive on average 5 deliveries per week, across all goods categories. 38.7 percent of the respondents reported performing their most recent shopping activity online, considering all goods categories. However, the frequency of online shopping varied across different goods categories. Most of the respondents that purchased groceries or household supplies reported having shopped in person (89 and 75 percent of the respondents respectively), while, in contrast, for those that purchased restaurant food and clothing items, two-thirds of respondents reported buying online in both categories. Online shopping is widespread in the clothing and restaurant food markets, but less in grocery and household supplies markets. Of the consumers that shopped online for restaurant food, 76 percent of them decided to travel to take out (also referred to as curbside pickup), and only 24 percent of them chose to have the meal delivered directly to their home.

Online shopping is more widespread among mobility-impaired individuals

Participants were asked whether they had a disability that limited physical activities such as carrying, walking, lifting, etc. Of the 918 participants, 98 (11%) responded that they did have a disability that fit this description. The share of respondents that shop online was higher among mobility-impaired individuals (30 percent online for delivery and 19 percent online for pick-up) compared to individuals that did not report any mobility impairment (23 percent online for delivery and 12 percent online for pick-up).

Driving is the predominant shopping travel mode

Of the sample of respondents, 96 percent reported having access to a motorized vehicle within their household. Driving is also the most common shopping mode of in-person travel, with 81.3 percent of respondents reporting that they drove to a store to shop. Walking is a distant second preferred shopping travel mode, with 13.1 percent of respondents reporting having walked to a store. Biking and public transit were rarely adopted as a shopping travel mode, together they were observed 5.6 percent of the time. Though included as a travel option, only 1 participant reported using a rideshare vehicle to shop.

Electrification in West Seattle

Of the respondents that have access to a motorized vehicle in their households, 9.8 percent of them reported owning an electric vehicle. Car ownership is much more widespread than bike ownership, with 51.6 percent of the respondents reporting having access to a bike. Among these, 15.5 percent of them said that at least one of their bikes is electric.

The 10-minute city

The average walking time across all types of goods purchased was 10 minutes. The average driving time, for those respondents that reported driving to a store, was also about 10 minutes, except for those who reported purchasing clothing items, which reported on average of 27-minute trip time (both using a private car or using public transit). The longest travel times are seen mostly for respondents that took public transit as a shopping travel mode.

Living in proximity to stores reduces driving and online deliveries

A higher number of stores within a 10-minute walking distance (0.5 miles) is correlated with a higher number of consumers choosing to walk to a store, compared to those that chose to drive to a store or that shopped online. This is true across all goods types, but it is more significantly seen in grocery shopping. Moreover, accessibility to commercial establishments at a walking distance has a stronger impact on reducing the likelihood of driving, and at a lesser magnitude, reduces the propensity of shopping online.

Delivery to the doorstep is the most common destination for online deliveries

For those that chose to buy online, the most common delivery destination was at the respondents’ home doorstep (84 percent of respondents reported receiving online deliveries at home). The second most frequently used delivery destination was parcel lockers (15 percent of respondents), with 12 percent of respondents making use of private lockers, while only 3 percent made use of public lockers. The remaining one percent received deliveries at other destinations (e.g. office or nearby store).

The West Seattle High Bridge closure incentivized local shopping

When asked about the impacts of the West Seattle Bridge closure on individual online and shopping travel behaviors, more respondents reported buying more locally and online, vs. traveling farther for shopping and buying in person.

Recommended Citation:
Goodchild, A., Dalla Chiara, G., Verma, R., Rula, K. (2023) Analysis of Online Shopping and Shopping Travel Behaviors in West Seattle, Urban Freight Lab.