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Technical Report

Urban Goods Delivery Toolkit

Publication Date: 2020
Summary:

This Toolkit is designed to help transportation professionals and researchers gather key data needed to make the Final 50 Feet segment function as efficiently as possible, reducing both the time trucks park in load/unload spaces and the number of failed first delivery attempts.

In addition, the toolkit can help transportation planners, traffic engineers, freight system managers, parking and operations strategists, and researchers build a fundamental knowledge base for planning; managing parking operations; managing emergency management and response; updating traffic, land use and building codes; and modeling future scenarios and needs.

In short, the toolkit can be used to help cities meet the ever-increasing demand for trucks and other load/unload activities.

Recommended Citation:
Urban Freight Lab. (2020) Urban Goods Delivery Toolkit. https://depts.washington.edu/toolkit

Shipping Resilience: Strategic Planning for Coastal Community Resilience to Marine Transportation Risk (SIREN)

Many coastal communities across Canada are highly dependent upon maritime transportation systems that are vulnerable in natural disasters. This project aims to improve understanding of how coastal maritime transportation systems would be disrupted in natural hazard events, how such disruption would impact coastal communities, and what strategies could effectively address this risk.

Ports across Canada are vulnerable in natural disasters, and their disruption can pose severe consequences for marine transportation systems and the coastal communities that rely on them. This project aims to improve understanding of how different types of ports may be affected in hazard events, with focus on catastrophic earthquake risk in coastal British Columbia, and consideration of severe hurricane damage to ports in Eastern Canada.

Focusing on the movement of people and goods in the emergency response phase of a disaster, the research team develops new tools, information, and risk assessments to support preparedness planning by local and provincial governments and the transportation sector. Through iterative engagement with stakeholders, the research is also intended to foster dialogue and shared understandings of risk that are necessary for resilience planning.

The research consists of an interrelated set of activities:

  • Organization of workshops for engaging government and transport sector stakeholders.
  • Development of a framework for assessing community resilience to shipping and port disruption.
  • Development of a model and simulation tool for the coastal maritime transportation system and regional multimodal logistics system.
  • Development of a simulation model for port operations and vulnerabilities to natural hazards.
  • Development of an approach for evaluating the effectiveness of the modelling approach.

Research questions:

  1. How would a major disaster likely affect marine transportation routes?
  2. How would this marine transportation disruption affect the movement of people and resources in the emergency response phase?
  3. What strategies (e.g., alternate routes and/or transport modes) would be effective for different types of communities in alleviating the potential consequences?
  4. Will a port be available, and in what state, after a natural hazard event, considering its own vulnerability and the vulnerability of interdependent infrastructure (e.g., road access, electric power)?
  5. Based on expected states, what ports could be used for ingress and egress of populations and resources during the immediate and sustained response phases of a catastrophic disaster?
  6. What strategies would be effective for different types of ports to reduce failure risk or improve functional resilience?
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

Testing Curbside Management Strategies to Mitigate the Impacts of Ridesourcing Services on Traffic

 
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Publication:  Transportation Research Record: Journal of the Transportation Research Board
Publication Date: 2020
Summary:

Increased use of ridehailing leads to increased pick-up and drop-off activity. This may slow traffic or cause delays as vehicles increase curb use, conduct pick-up and drop-off activity directly in the travel lane, or slow to find and connect with passengers. How should cities respond to this change in an effort to keep travel lanes operating smoothly and efficiently? This research evaluates two strategies in Seattle, WA, in an area where large numbers of workers commute using ridesourcing services: (i) a change of curb allocation from paid parking to passenger load zone (PLZ), and (ii) a geofencing approach by transportation network companies (TNCs) which directs their drivers and passengers to designated pick-up and drop-off locations on a block. An array of data on street and curb activity along three study blockfaces was collected, using video and sensor technology as well as in-person observations. Data were collected in three phases: (i) the baseline, (ii) after the new PLZs were added, expanding total PLZ curb length from 20 ft to 274 ft, and (iii) after geofencing was added to the expanded PLZs. The added PLZs were open to any passenger vehicle (not just TNC vehicles), weekdays 7:00–10:00 a.m. and 2:00–7:00 p.m. The results showed that the increased PLZ allocation and geofencing strategy reduced the number of pick-ups/drop-offs in the travel lane, reduced dwell times, increased curb use compliance, and increased TNC passenger satisfaction. The two strategies, however, had no observable effect on travel speeds or traffic safety in the selected study area.

Recommended Citation:
Ranjbari, Andisheh, Jose Luis Machado-León, Giacomo Dalla Chiara, Don MacKenzie, and Anne Goodchild. “Testing Curbside Management Strategies to Mitigate the Impacts of Ridesourcing Services on Traffic.” Transportation Research Record, (October 2020). https://doi.org/10.1177/0361198120957314.
Paper

An Empirical Analysis of Passenger Vehicle Dwell Time and Curb Management Strategies for Ride-Hailing Pick-Up/Drop-Off Operations

Publication: Transportation
Publication Date: 2023
Summary:

With the dramatic and recent growth in demand for curbside pick-up and drop-off by ride-hailing services, as well as online shopping and associated deliveries, balancing the needs of roadway users is increasingly critical. Local governments lack tools to evaluate the impacts of curb management strategies that prioritize different users’ needs. The dwell time of passenger vehicles picking up/dropping off (PUDO) passengers, including ride-hailing vehicles, taxis, and other cars, is a vital metric for curb management, but little is understood about the key factors that affect it. This research used a hazard-based duration modeling approach to describe the PUDO dwell times of over 6,000 passenger vehicles conducted in Seattle, Wash. Additionally, a before-after study approach was used to assess the effects of two curb management strategies: adding PUDO zones and geofencing. Results showed that the number of passenger maneuvers, location and time of day, and traffic and operation management factors significantly affected PUDO dwell times. PUDO operations took longer with more passengers, pick-ups (as opposed to drop-offs), vehicle´s trunk access, curbside stops, and in the afternoon. More vehicles at the curb and in adjacent travel lanes were found to be related to shorter PUDO dwell times but with a less practical significance. Ride-hailing vehicles tended to spend less time conducting PUDOs than other passenger vehicles and taxis. Adding PUDO zones, together with geofencing, was found to be related to faster PUDO operations at the curb. Suggestions are made for the future design of curb management strategies to accommodate ride-hailing operations.

Authors: José Luis Machado LeónDr. Anne Goodchild, Don MacKenzie (University of Washington College of Engineering)
Recommended Citation:
Machado-León, J.L., MacKenzie, D. & Goodchild, A. An Empirical Analysis of Passenger Vehicle Dwell Time and Curb Management Strategies for Ride-Hailing Pick-Up/Drop-Off Operations. Transportation (2023). https://doi.org/10.1007/s11116-023-10380-6
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.
Paper

Do Commercial Vehicles Cruise for Parking? Empirical Evidence from Seattle

 
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Publication: Transport Policy
Volume: 97
Pages: 26-36
Publication Date: 2020
Summary:

Parking cruising is a well-known phenomenon in passenger transportation, and a significant source of congestion and pollution in urban areas. While urban commercial vehicles are known to travel longer distances and to stop more frequently than passenger vehicles, little is known about their parking cruising behavior, nor how parking infrastructure affect such behavior.

In this study we propose a simple method to quantitatively explore the parking cruising behavior of commercial vehicle drivers in urban areas using widely available GPS data, and how urban transport infrastructure impacts parking cruising times.

We apply the method to a sample of 2900 trips performed by a fleet of commercial vehicles, delivering and picking up parcels in Seattle downtown. We obtain an average estimated parking cruising time of 2.3 minutes per trip, contributing on average for 28 percent of total trip time. We also found that cruising for parking decreased as more curb-space was allocated to commercial vehicles load zones and paid parking and as more off-street parking areas were available at trip destinations, whereas it increased as more curb space was allocated to bus zone.

Recommended Citation:
Dalla Chiara, Giacomo, & Goodchild, Anne. (2020) Do Commercial Vehicles Cruise for Parking? Empirical Evidence from Seattle. Transport Policy, 97, 26-36. https://doi.org/10.1016/j.tranpol.2020.06.013
Paper

Estimating Intermodal Transfer Barriers to Light Rail using Smartcard Data in Seattle, WA

 
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Publication:  Transportation Research Record: Journal of the Transportation Research Board
Publication Date: 2022
Summary:

Transit transfers are a necessary inconvenience to riders. They support strong hierarchical networks by connecting various local, regional, and express lines through a variety of modes. This is true in Seattle, where many lines were redrawn to feed into the Link Light Rail network. Previous transfer studies, using surveys, found that perceived safety, distance, and personal health were significant predictors of transfers. This study aims to use smartcard data and generalized linear modeling to estimate which elements of transfers are commonly overcome—and which are not—among riders boarding the Link Light Rail in Seattle and its suburbs. The aims of this research are twofold: (1) critical analysis of attributes of transfer barriers so that the future station area could serve improved riders’ accessibility; (2) equity of transfer barriers among the users by analyzing the user breakdown of the origin lines and the destination. We use Seattle’s One Regional Card for All smartcard data among the Link Light Rail riders in the Seattle metropolitan area in 2019, and applied a negative binomial generalized linear model. The model suggests that walking distance and walking grade have significant effects on transfers. For the users’ equity analysis, the disabled population tends to transfer less, while the low-income and youth riders populations tend to transfer more often. Future research could incorporate a more mixed-methods approach to confirm some of these findings or include station amenities, such as live schedule updates for common transfer lines.

Authors: Dr. Ed McCormack, James Eager (University of Washington Department of Urban Design and Planning), Chang-Hee Christine Bae (University of Washington Department of Urban Design and Planning)
Recommended Citation:
Eager, J., Bae, C.-H. C., & McCormack, E. D. (2022). Estimating Intermodal Transfer Barriers to Light Rail using Smartcard Data in Seattle, WA. Transportation Research Record. https://doi.org/10.1177/03611981221119190.
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.
Technical Report

Freight and Transit Lane Case Study

 
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Publication Date: 2020
Summary:

The Seattle Department of Transportation (SDOT) engaged the Urban Freight Lab at the Supply Chain Transportation and Logistics Center at the University of Washington to conduct research on the impacts of a freight and transit (FAT) lane that was implemented in January 2019 in Seattle. To improve freight mobility in the City of Seattle and realize the objectives included in the city’s Freight Master Plan (FMP), the FAT lane was opened upon the closing of the Alaskan Way Viaduct.

The objective of this study was therefore to evaluate the performance and utilization of the FAT lane. Street camera video recordings from two separate intersection locations were used for this research.

Vehicles were categorized into ten different groups, including drayage with container and drayage without container, to capture their different behavior. Drayage vehicles are vehicles transporting cargo to a warehouse or to another port. Human data reducers used street camera videos to count vehicles in those ten designated groups.

The results of the traffic volume analysis showed that transit vehicles chose the FAT lane over the general purpose lane at ratios of higher than 90 percent. By the time of day, transit vehicle volumes in the FAT lane followed a different pattern than freight vehicles. Transit vehicle volumes peaked around afternoon rush hours, but freight activity decreased during that same time. Some freight vehicles used the FAT lane, but their ratio in the FAT lane decreased when bus volumes increased. The ratio of unauthorized vehicles in the FAT lane increased during congestion.

Further analysis described in this report included a multinomial logistic regression model to estimate the factors influencing the choice of FAT lane over the regular lane. The results showed that lane choice was dependent on the day of week, time of day, vehicle type, and location features. Density, as a measure of congestion, was found to be statistically insignificant for the model.

Recommended Citation:
Urban Freight Lab (2020). Freight and Transit Lane Case Study.