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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

 
Download PDF  (0.40 MB)
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.
Student Thesis and Dissertations

Optimization Modeling Approaches to Evacuations of Isolated Communities

Publication Date: 2022
Summary:

Isolated communities are particularly vulnerable to disasters caused by natural hazards. In many cases, evacuation is the only option to ensure the population’s safety. Isolated communities are becoming increasingly aware of this threat and demand solutions to this problem. However, the large body of existing research on evacuation modeling usually considers environments where populations can evacuate via private vehicles and by using an existing road infrastructure. These models are often not applicable to remote valleys and islands, where road connections can be disrupted or do not exist at all. The use of external resources is therefore essential to evacuate the population. How to systematically evacuate an isolated community through a coordinated fleet of resources has not yet been researched. This dissertation thesis addresses this knowledge gap by designing a new routing problem called the Isolated Community Evacuation Problem (ICEP) that optimally routes recovery resources between evacuation pick-up points and shelter locations to minimize the total evacuation time. The research presents derivations of the initial model for (a) emergency planning and (b) response purposes to give emergency planners and researchers tools to prepare for and react to an evacuation of an isolated community. For (a), a scenario-based two-stage stochastic program with recourse considers different emergency scenarios to select the optimal set of recovery resources to hold available for any evacuation emergency. Furthermore, the dissertation explores efficient structure-based heuristics to solve the problem quickly. For (b), the assumption of certainty over the size of the affected population at the time of evacuation is relaxed. Approaches from robust and rolling-horizon optimization are presented to solve this problem. Moreover, meta-heuristics are explored to solve the problem to optimality while overcoming the complexity of the problem formulation. Finally, an in-depth, real-world case study that was conducted in collaboration with first responders and emergency authorities on Bowen Island in Canada is presented to test and evaluate the applicability of the proposed models. This case study further informed the official evacuation plan of the island. This collaboration demonstrates the potential of full integration of the research approach with local emergency expertise from the affected area and highlights the data requirements that need to be met to maximize the use of the model.

Authors: Fiete Krutein
Paper

The Isolated Community Evacuation Problem with Mixed Integer Programming

 
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Publication: Transportation Research Part E: Logistics and Transportation Review
Volume: 161
Pages: 102710
Publication Date: 2022
Summary:

As awareness of the vulnerability of isolated regions to natural disasters grows, the demand for efficient evacuation plans is increasing. However, isolated areas, such as islands, often have characteristics that make conventional methods, such as evacuation by private vehicle, impractical to infeasible. Mathematical models are conventional tools for evacuation planning. Most previous models have focused on densely populated areas, and are inapplicable to isolated communities that are dependent on marine vessels or aircraft to evacuate. This paper introduces the Isolated Community Evacuation Problem (ICEP) and a corresponding mixed integer programming formulation that aims to minimize the evacuation time of an isolated community through optimally routing a coordinated fleet of heterogeneous recovery resources. ICEP differs from previous models on resource-based evacuation in that it is highly asymmetric and incorporates compatibility issues between resources and access points. The formulation is expanded to a two-stage stochastic problem that allows scenario-based optimal resource planning while also ensuring minimal evacuation time. In addition, objective functions with a varying degree of risk are provided, and the sensitivity of the model to different objective functions and problem sizes is presented through numerical experiments. To increase efficiency, structure-based heuristics to solve the deterministic and stochastic problems are introduced and evaluated through computational experiments. The results give researchers and emergency planners in remote areas a tool to build optimal evacuation plans given the heterogeneous resource fleets available, which is something they have not been previously able to do and to take actions to improve the resilience of their communities accordingly.

Recommended Citation:
Krutein, K. F., & Goodchild, A. (2022). The isolated community evacuation problem with mixed integer programming. In Transportation Research Part E: Logistics and Transportation Review (Vol. 161, p. 102710). Elsevier BV. https://doi.org/10.1016/j.tre.2022.10271
Paper

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

 
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Publication: Proceedings of American Society of Civil Engineers (ASCE) Transportation and Development Conference 2022: Transportation Planning and Workforce Development
Publication Date: 2022
Summary:

(This project is part of the Urban Freight Lab’s Technical Assistance Program, where UFL contributes to the project by providing 1:1 match funds in terms of staff and/or research assistants to complete project tasks.)

Green Loading Zones (GLZs) are curb spaces dedicated to the use of electric or alternative fuel (“green”) delivery vehicles. Some U.S. 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 willingness 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.

Recommended Citation:
Maxner, T., Goulianou, P., Ranjbari, A., and Goodchild, A. (2022). "Studying Urban Delivery Company Needs and Preferences for Green Loading Zones Implementation: A Case Study of NYC", In Proceedings of ASCE Transportation and Development Conference (Forthcoming), Seattle, WA.
Report

NYC Zero-Emissions Urban Freight and Green Loading Zones Market Research

 
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Publication Date: 2022
Summary:

In an effort to reduce emissions from last-mile deliveries and incentivize green vehicle adoption, The New York City Department of Transportation (NYC DOT) is seeking to implement a Green Loading Zone (GLZ) pilot program. A Green Loading Zone is curb space designated for the sole use of “green” vehicles, which could include electric and alternative fuel vehicles as well as other zero-emission delivery modes like electric-assist cargo bikes. To inform decisions about the program’s siting and regulations, this study was conducted by the University of Washington’s Urban Freight Lab (UFL) in collaboration with NYC DOT under the UFL’s Technical Assistance Program.

The study consists of three sources of information, focusing primarily on input from potential GLZ users, i.e., delivery companies. An online survey of these stakeholders was conducted, garnering 13 responses from 8 types of companies. Interviews were conducted with a parcel carrier and an electric vehicle manufacturer. Additionally, similar programs from around the world were researched to help identify current practices. The major findings are summarized below, followed by recommendations for siting, usage restriction and pricing of GLZs. It is important to note that these recommendations are based on the survey and interview findings and thus on benefits to delivery companies. However, other important factors such as environmental justice, land use patterns, and budgetary constraints should be considered when implementing GLZs.

Literature Review Findings

Green Loading Zones are a relatively novel approach to incentivizing electric vehicle (EV) adoption. Two relevant pilot programs exist in the United States, one in Santa Monica, CA and the other one in Los Angeles, CA. Both are “zero-emission” delivery programs, meaning alternative fuel vehicles that reduce emissions (compared to fossil fuel vehicles) are not included in the pilot’s parking benefits (dedicated spaces and free parking). Other cities including Washington, DC and Vancouver, Canada are also creating truck-only zones and dedicating parking to EVs in their efforts to reduce emissions. Bremen, Germany also has a similar program called an Environmental Loading Point.

Many cities in Europe are implementing low- or zero-emission zones. These are different than GLZs in that entire cities or sections of cities are restricted to vehicles that meet certain emissions criteria. London, Paris, and 13 Dutch municipalities are all implementing low-emission zones. These zones have achieved some success in reducing greenhouse gas emissions: in London, CO2 from vehicles has been reduced by 13 percent. Companies operating in those cities have opted to purchase cleaner vehicles or to replace trucks with alternative modes like cargo bikes. In addition to demonstrating similar goals as NYC DOT, these programs provide insights to the siting and structure of GLZs. Loading zones have been selected based on equity concerns, delivery demand, and commercial density. Every city in the literature review has installed specific signage for the programs to clearly convey the regulations involved.

Survey and interview Findings

A range of company types replied to the survey: parcel carriers (large shippers), small shippers, e-commerce and retail companies, freight distributors, a truck dealer, a liquid fuel delivery company, and a logistics NYC  association (answering on behalf of members). The majority of these companies will be increasing their fleet sizes over the next ten years, and most plan to increase the share of EVs in their fleets while doing so. A smaller share (4 of 13) also plans to increase their share of alternative fuel vehicles. The most cited reasons for increasing fleet size and green vehicle share are: 1) internal sustainability goals, 2) social responsibility, and 3) new vehicles/models coming to the market.

Green vehicle adoption is not without its challenges. For EV adoption specifically, companies identified three major barriers: 1) competition in the EV market, 2) electric grid requirements upstream of company-owned facilities, and 3) lack of adequate government-supported purchasing subsidies. To overcome these barriers, respondents would like larger or more government purchasing incentives and reduced toll or parking rates for EVs. However, the majority of companies also expressed a willingness to pay for GLZs at similar rates to other commercial loading zones.

As for area coverage, all respondents deliver to Manhattan, Queens, and Brooklyn. 11 of 13 deliver to Staten Island and the Bronx as well. All EV and cargo bike operators deliver to Manhattan, whereas only one EV operator and one cargo bike operator deliver to all five boroughs of NYC. Respondents deliver at all times of day, but the busiest times are between 9:00AM and 4:00PM (stated by 8 of 13 respondents). Peak periods are busiest for four companies in the morning (6:00AM-9:00AM) and six companies in the evening (4:00PM-9:00PM).

The interviews supported findings from the survey. Both interviewed companies have a vested interest in reducing their environmental footprint and plan to use or produce exclusively zero-emission vehicles by 2050 (carrier) or 2035 (manufacturer). However, they noted challenges to electrifying entire fleets for cities. Charging infrastructure needs to be expanded, but incentives are also needed (parking benefits, subsidies, expedited permitting) to make the market viable for many delivery companies.

Recommendations

The preceding findings informed four key recommendations:

  • GLZs should be made available to multiple modes: green vehicles and cargo bikes. Adequate curb space might be needed to accommodate multiple step-side vans plus a small vehicle and cargo bikes, but this should be balanced against curb utilization rates and anticipated dwell times to maximize curb use.
  • Explore piloting GLZs in Lower Manhattan and commercial areas of Midtown Manhattan; they could be the most beneficial locations for the pilot according to survey respondents.
  • The preferred layout for GLZs is several spaces distributed across multiple blocks.
  • DOT can charge for the GLZ use. It is recommended that rates not exceed current parking prices in the selected neighborhood, but some companies are willing to pay a modest increase over that rate to avoid parking tickets.

 

Recommended Citation:
Urban Freight Lab (2022). NYC Zero-Emissions Urban Freight and Green Loading Zones Market Research.