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Urban Freight Lab

Research Topic: The Final 50 Feet of the Urban Goods Delivery System

The Urban Freight Lab coined the term “Final 50 Feet” and defined it as the supply chain segment that begins when a delivery vehicle pulls into a parking space and stops moving — in public load/unload spaces at the curb or in an alley, or a building’s loading dock or internal freight bay. It tracks the delivery process inside buildings and ends where the customer takes receipt of their goods. This research analyzes processes, develops potential solutions, and tests operational improvements in the final segment of the urban goods delivery system.

Paper

Commercial Vehicle Driver Behaviors and Decision Making: Lessons Learned from Urban Ridealongs

 
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URL: https://doi.org/10.1177/03611981211003575
Publication:  Transportation Research Record: Journal of the Transportation Research Board
Volume: 2675 (9)
Pages: 608-619
Publication Date: 2021
Summary:

As ecommerce and urban deliveries spike, cities grapple with managing urban freight more actively. To manage urban deliveries effectively, city planners and policy makers need to better understand driver behaviors and the challenges they experience in making deliveries.

In this study, we collected data on commercial vehicle (CV) driver behaviors by performing ridealongs with various logistics carriers. Ridealongs were performed in Seattle, Washington, covering a range of vehicles (cars, vans, and trucks), goods (parcels, mail, beverages, and printed materials), and customer types (residential, office, large and small retail). Observers collected qualitative observations and quantitative data on trip and dwell times, while also tracking vehicles with global positioning system devices.

The results showed that, on average, urban CVs spent 80% of their daily operating time parked. The study also found that, unlike the common belief, drivers (especially those operating heavier vehicles) parked in authorized parking locations, with only less than 5% of stops occurring in the travel lane. Dwell times associated with authorized parking locations were significantly longer than those of other parking locations, and mail and heavy goods deliveries generally had longer dwell times.

We also identified three main criteria CV drivers used for choosing a parking location: avoiding unsafe maneuvers, minimizing conflicts with other users of the road, and competition with other commercial drivers.

The results provide estimates for trip times, dwell times, and parking choice types, as well as insights into why those decisions are made and the factors affecting driver choices.

In recent years, cities have changed their approach toward managing urban freight vehicles. Passive regulations, such as limiting delivery vehicles’ road and curb use to given time windows or areas have been replaced by active management through designing policies for deploying more commercial vehicle (CV) load zones, pay-per-use load zone pricing, curb reservations, and parking information systems. The goal is to reduce the negative externalities produced by urban freight vehicles, such as noise and emissions, traffic congestion, and unauthorized parking, while guaranteeing goods flow in dense urban areas. To accomplish this goal, planners need to have an understanding of the fundamental parking decision-making process and behaviors of CV drivers.

Two main difficulties are encountered when CV driver behaviors are analyzed. First, freight movement in urban areas is a very heterogeneous phenomenon. Drivers face numerous challenges and have to adopt different travel and parking behaviors to navigate the complex urban network and perform deliveries and pick-ups. Therefore, researchers and policy makers find it harder to identify common behaviors and responses to policy actions for freight vehicles than for passenger vehicles. Second, there is a lack of available data. Most data on CV movements are collected by private carriers, who use them to make business decisions and therefore rarely release them to the public. Lack of data results in a lack of fundamental knowledge of the urban freight system, inhibiting policy makers’ ability to make data-driven decisions.

The urban freight literature discusses research that has employed various data collection techniques to study CV driver behaviors. Cherrett et al. reviewed 30 UK surveys on urban delivery activity and performed empirical analyses on delivery rates, time-of-day choice, types of vehicles used to perform deliveries, and dwell time distribution, among others. The surveys reviewed were mostly establishment-based, capturing driver behaviors at specific locations and times of the day. Allen et al. performed a more comprehensive investigation, reviewing different survey techniques used to study urban freight activities, including driver surveys, field observations, vehicle trip diaries, and global positioning system (GPS) traces. Driver surveys collect data on driver activities and are usually performed through in-person interviews with drivers outside their working hours or at roadside at specific locations. In-person interviews provide valuable insights into driver choices and decisions but are often limited by the locations at which the interviews occur or might not reflect actual choices because they are done outside the driver work context. Vehicle trip diaries involve drivers recording their daily activities while field observations entail observing driver activities at specific locations and establishments; neither collects insights into the challenges that drivers face during their trips and how they make certain decisions. The same limitations hold true for data collected through GPS traces. Allen et al. mentioned the collection of travel diaries by surveyors traveling in vehicles with drivers performing deliveries and pick-ups as another data collection technique that could provide useful insights into how deliveries/pick-ups are performed. However, they acknowledged that collecting this type of data is cumbersome because of the difficulty of obtaining permission from carriers and the large effort needed to coordinate data collection.

This study aims to fill that gap by collecting data on driver decision-making behaviors through observations made while riding along with CV drivers. A systematic approach was taken to observe and collect data on last-mile deliveries, combining both qualitative observations and quantitative data from GPS traces. The ridealongs were performed with various delivery companies in Seattle, Washington, covering a range of vehicle types (cars, vans, and trucks), goods types (parcels, mail, beverages, and printed materials), and customer types (residential, office, large and small retail).

The data collected will not only add to the existing literature by providing estimates of trip times, parking choice types, time and distance spent cruising for parking, and parking dwell times but will also provide insights into why those decisions are made and the factors affecting driver choices.

The objectives of this study are to provide a better understanding of CV driver behaviors and to identify common and unique challenges they experience in performing the last mile. These findings will help city planners, policy makers, and delivery companies work together better to address those challenges and improve urban delivery efficiency.

The next section of this paper describes the relevant literature on empirical urban freight behavior studies. The following section then introduces the ridealongs performed and the data collection methods employed. Next, analysis of the data and qualitative observations from the ridealongs are described, and the results are discussed in five overarching categories: the time spent in and out of the vehicle, parking location choice, the reasons behind those choices, parking cruising time, and factors affecting dwell time.

Authors: Dr. Giacomo Dalla ChiaraFiete KruteinDr. Andisheh RanjbariDr. Anne Goodchild
Recommended Citation:
Chiara, Giacomo Dalla, Krutein, Klaas Fiete, Ranjbari, Andisheh, & Goodchild, Anne. (2021). Understanding Urban Commercial Vehicle Driver Behaviors and Decision Making. Transportation Research Record, 2675(9), 608-619. https://doi.org/10.1177/03611981211003575
Report

Cargo E-Bike Delivery Pilot Test in Seattle

 
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Publication Date: 2020
Summary:

This study performed an empirical analysis to evaluate the implementation of a cargo e-bike delivery system pilot tested by the United Parcel Service, Inc. (UPS) in Seattle, Washington. During the pilot, a cargo e-bike with a removable cargo container was used to perform last-mile deliveries in downtown Seattle. Cargo containers were pre-loaded daily at the UPS Seattle depot and loaded onto a trailer, which was then carried to a parking lot in downtown.

Data were obtained for two study phases. In the “before-pilot” phase, data were obtained from truck routes that operated in the same areas where the cargo e-bike was proposed to operate. In the “pilot” phase, data were obtained from the cargo e-bike route and from the truck routes that simultaneously delivered in the same neighborhoods. Data were subsequently analyzed to assess the performance of the cargo e-bike system versus the traditional truck-only delivery system.

The study first analyzed data from the before-pilot phase to characterize truck delivery activity. Analysis focused on three metrics: time spent cruising for parking, delivery distance, and dwell time. The following findings were reported:

  • On average, a truck driver spent about 2 minutes cruising for parking for each delivery trip, which represented 28 percent of total trip time. On average, a driver spent about 50 minutes a day cruising for parking.
  • Most of the deliveries performed were about 30 meters (98 feet) from the vehicle stop location, which is less than the length of an average blockface in downtown Seattle (100 meters, 328 feet). Only 10 percent of deliveries were more 100 meters away from the vehicle stop location.
  • Most truck dwell times were around 5 minutes. However, the dwell time distribution was right-skewed, with a median dwell time of 17.5 minutes.

Three other metrics were evaluated for both the before-pilot and the pilot study phases: delivery area, number of delivery locations, and number of packages delivered and failed first delivery rate. The following results were obtained:

  • A comparison of the delivery areas of the trucks and the cargo e-bike before and after the pilot showed that the trucks and cargo e-bike delivered approximately in the same geographic areas, with no significant changes in the trucks’ delivery areas before and during the pilot.
  • The number of establishments the cargo e-bike delivered to in a single tour during the pilot phase was found to be 31 percent of the number of delivery locations visited, on average, by a truck in a single tour during the before-pilot phase, and 28 percent during the pilot phase.
  • During the pilot, the cargo e-bike delivered on average to five establishments per hour, representing 30 percent of the establishments visited per hour by a truck in the before-pilot phase and 25 percent during the pilot.
  • During the pilot, the number of establishments the cargo e-bike delivered to increased over time, suggesting a potential for improvement in the efficiency of the cargo e-bike.
  • The cargo e-bike delivered 24 percent of the number of packages delivered by a truck during a single tour, on average, before the pilot and 20 percent during the pilot.
  • Both before and during the pilot the delivery failed rate (percentage of packages that were not delivered throughout the day) was approximately 0.8 percent. The cargo e-bike experienced a statistically significantly lower failed rate of 0.5 percent with respect to the truck fail rate, with most tours experiencing no failed first deliveries.

The above reported empirical results should be interpreted only in the light of the data obtained. Moreover, some of the results are affected by the fact that the pilot coincided with the holiday season, in which above average demand was experienced. Moreover, because the pilot lasted only one month, not enough time was given for the system to run at “full-speed.”

Authors: Urban Freight Lab
Recommended Citation:
Urban Freight Lab (2020). Cargo E-Bike Delivery Pilot Test in Seattle.
Report

Seattle Center City: Alley Infrastructure Inventory and Occupancy Study

 
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Publication Date: 2018
Summary:

The Supply Chain and Transportation Logistics (SCTL) Center conducted an alley inventory and truck load/unload occupancy study for the City of Seattle. Researchers collected data identifying the locations and infrastructure characteristics of alleys within Seattle’s One Center City planning area, which includes the downtown, uptown, South Lake Union, Capitol Hill, and First Hill urban centers. The resulting alley database includes GIS coordinates for both ends of each alley, geometric and traffic attributes, and photos. Researchers also observed all truck load/unload activity in selected alleys to determine minutes vacant and minutes occupied by trucks, vans, passenger vehicles, and cargo bikes. The researchers then developed alley management recommendations to promote safe, sustainable, and efficient goods delivery and pick-up.

Key Findings:

The first key finding of this study is that more than 90% of Center City alleys are only one lane wide. This surprising fact creates an upper limit on alley parking capacity, as each alley can functionally hold only one or two vehicles at a time. Because there is no room to pass by, when a truck, van, or car parks it blocks all other vehicles from using the alley. When commercial vehicle drivers see that an alley is blocked they will not enter it, as their only way out would be to back up into street traffic. Seattle Municipal Code prohibits this, as well as backing up into an alley, for safety reasons.

When informed by the second key finding—68% of vehicles in the alley occupancy study parked there for 15 minutes or less—it is clear that moving vehicles through alleys in short time increments is the only reasonable path to increase productivity. As one parked vehicle operationally blocks the entire alley, the goal of new alley policies and strategies should be to reduce the amount of time alleys are blocked to additional users.

The study surfaces four additional key findings:

  1. 87% of all vehicles in the 7 alleys studied parked for 30 minutes or less. Given the imperative to move alley traffic quickly, vehicles that need more parking time must be moved out of the alleys and onto the curb where they don’t block others.
  2. 15% of alleys’ pavement condition is so poor that delivery workers can’t pass through with loaded hand carts.  Although trucks can drive over fairly uneven pavement without difficulty, it is not the case for delivery people walking with fully loaded handcarts.  The alley pavement rating was done with a qualitative visual inspection to identify obvious problems; more detailed measurements would be needed to fully assess conditions.
  3. 73% of Center City area alleys contain entrances to passenger parking facilities. Placing garage entrances in alleys has been a city policy goal for years. But it increases the frequency of cars in alleys and adds demands on alley use. Understanding why cars are queuing for passenger garages located off alleys, and providing incentives and disincentives to reduce that, would help make alleys more productive.
  4. Alleys are vacant about half of the time during the business day. While at first blush this suggests ample capacity, the fact that an alley can only hold one-to-two parked trucks at a time means alleys are limited operationally and therefore are not a viable alternative to replace the use of curb CVLZs on city streets.

These findings indicate that, due to the fixed alley width constraint, load/unload space inside Seattle’s existing Center City area alleys is insufficient to meet additional future demand.

Authors: Urban Freight Lab
Recommended Citation:
Urban Freight Lab (2018). Seattle Center City: Alley Infrastructure Inventory and Occupancy Study.

The Final 50 Feet of the Urban Goods Delivery System: Pilot Test of an Innovative Improvement Strategy

Background

We are living at the convergence of the rise of e-commerce and fast growing cities. Surging growth in U.S. online sales has averaged more than 15% year-over-year since 2010. Total e-commerce sales for 2016 were estimated at $394.9 billion, an increase of 15.1 percent from 2015. This is a huge gain when compared to total retail sales in 2016, which only increased 2.9 percent from 2015. E-commerce sales in 2016 accounted for 8.1 percent of total sales, while accounting for 7.3 percent of total sales in 2015.

This is causing tremendous pressure on local governments to rethink the way they manage street curb parking and alley operations for trucks and other delivery vehicles, and on building operators to plan for the influx of online goods. City managers and policy makers are grappling with high demand for scarce road, curb and sidewalk space, and multiple competing uses. But rapidly growing cities lack data-based evidence for the strategies they are considering to support e-commerce and business vitality, while managing limited parking in street space that is also needed for transit, pedestrians, cars, bikes and trucks.

The Final 50 Feet is the project’s shorthand designation for the last leg of the delivery process, which:

  • Begins when a truck stops at a city-owned Commercial Vehicle Load Zone or alley, or in a privately-owned freight bay or loading dock in a building;
  • May extend along sidewalks or through traffic lanes; and
  • Ends where the end customer takes receipt of delivery.

Research Project

The purpose of the research project is to pilot test a promising strategy to reduce the number of failed first delivery attempts in urban buildings. The test will take place in the Seattle Municipal Tower. It will serve as a case study for transportation and urban planning professionals seeking to reduce truck trips to urban buildings. Urban Freight Lab identified two promising strategies for the pilot test:

  • Locker system: smaller to medium sized deliveries can be placed into a locker which will be temporarily installed during our pilot test
  • Grouped-tenant-floor-drop-off-points for medium sized items if locker is too small or full (4-6 floor groups to be set up by SDOT and Seattle City Light)
  • People will come and pick up the goods at the designated drop off points
  • Flyers with information of drop-off-points will be given to the carriers

UFL will evaluate the ability of the standardized second step pilot test to reduce the number of failed first delivery attempts by:

  • Collecting original data to document the number of failed first delivery attempts before and after the pilot test; and
  • Comparing them to the pilot test goals.
Student Thesis and Dissertations

Micro-Consolidation Practices in Urban Delivery Systems: Comparative Evaluation of Last Mile Deliveries Using e-Cargo Bikes and Microhubs

 
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URL: https://www.proquest.com/docview/2595035025
Publication Date: 2021
Summary:

The demand for home deliveries has seen a drastic increase, especially in cities, putting urban freight systems under pressure. As more people move to urban areas and change consumer behaviors to shop online, busy delivery operations cause externalities such as congestion and air pollution.

Micro-consolidation implementations and their possible pairing with soft transportation modes offer practical, economic, environmental, and cultural benefits. Early implementations of micro-consolidation practices were tested but cities need to understand their implications in terms of efficiency and sustainability.

This study includes a research scan and proposes a typology of micro-consolidation practices. It focuses on assessing the performance of microhubs that act as additional transshipment points where the packages are transported by trucks and transferred onto e-bikes to complete the last mile.

The purpose of the study is to assess the performance of delivery operations using a network of microhubs with cargo logistics and identify the conditions under which these solutions can be successfully implemented to improve urban freight efficiencies and reduce emissions. The performance is evaluated in terms of vehicle miles traveled, tailpipe CO2 emissions, and average operating cost per package using simulation tools. Three different delivery scenarios were tested that represents 1) the baseline scenario, where only vans and cars make deliveries; 2) the mixed scenario, where in addition to vans and cars, a portion of packages are delivered by e-bikes; and 3) the e-bike only scenario, where all package demand is satisfied using microhubs and e-bikes.

The results showed that e-bike delivery operations perform the best in service areas with high customer density. At the highest customer demand level, e-bikes traveled 7.7% less to deliver a package and emitted 91% less tailpipe CO2 with no significant cost benefits or losses when compared with the baseline scenario where only traditional delivery vehicles were used. Cargo logistics, when implemented in areas where the demand is densified, can reduce emissions and congestion without significant cost implications.

Authors: Şeyma Güneş
Recommended Citation:
Gunes, S. (2021). Micro-Consolidation Practices in Urban Delivery Systems: Comparative Evaluation of Last Mile Deliveries Using e-Cargo Bikes and Microhubs, University of Washington Master's Thesis.
Paper

Do Commercial Vehicles Cruise for Parking? Empirical Evidence from Seattle

 
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URL: https://doi.org/10.1016/j.tranpol.2020.06.013
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.

Authors: Dr. Anne GoodchildDr. Giacomo Dalla Chiara
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
Report

The Final 50 Feet of the Urban Goods Delivery System: Common Carrier Locker Pilot Test at the Seattle Municipal Tower

 
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Publication Date: 2018
Summary:

This report provides compelling evidence of the effectiveness of a new urban goods delivery system strategy: Common Carrier Locker Systems that create parcel delivery density and provide secure delivery locations in public spaces.

Common carrier locker systems are an innovative strategy because they may be used by any retailer, carrier, and goods purchaser, and placed on public property.  This contrasts with branded lockers such as those operated by Amazon, UPS, and FedEx that are limited to one retailer’s or one carrier’s use. Common carrier lockers use existing smart locker technology to provide security and convenience to users.

The Common Carrier Locker System Pilot Test in the Seattle Municipal Tower was uniquely designed for multiple retailers’ and delivery firms’ use in a public space. In spring 2018, a common carrier locker system was placed in the 62-floor Seattle Municipal Tower for ten days as part of a joint research project of the Urban Freight Lab (UFL) at the University of Washington’s Supply Chain Transportation & Logistics Center and the Seattle Department of Transportation (SDOT), with additional funding from the Pacific Northwest Transportation Consortium (PacTrans).

This report demonstrates common carrier lockers’ potential to reach both public and private goals by reducing dwell time (the time a truck is parked in a load/unload space in the city) and the number of failed first delivery attempts to dense urban areas. This research provides evidence that delivering multiple packages to a single location such as a locker, rather than delivering packages one-by-one to individual tenants in an urban tower increases the productivity of public and private truck load/unload spaces.

The concept for this empirical pilot test draws on prior UFL-conducted research on the Final 50 Feet of the urban goods delivery system. The Final 50 Feet is the term for the last segment of the supply chain. It begins when a truck parks in a load/unload space, continues as drivers maneuver goods along sidewalks and into urban towers to make the final delivery, and ends where the customer takes receipt of the goods.

The UFL’s 2017 research documented that of the 20 total minutes delivery drivers spent on average in the Seattle Municipal Tower, 12.2 of those minutes were spent going floor-to-floor in freight elevators and door-to-door to tenants on multiple floors.  The UFL recognized that cutting those two steps from the delivery process could slash delivery time in the Tower by more than half—which translates into a substantial reduction in truck dwell time.

Authors: Haena KimDr. Ed McCormackDr. Anne GoodchildBarbara Ivanov
Recommended Citation:
Urban Freight Lab (2018). The Final 50 Feet of the Urban Goods Delivery System: Common Carrier Locker Pilot Test at the Seattle Municipal Tower.

Seattle Center City Alley Infrastructure Inventory and Occupancy Study 2018 (Task Order 4)

The Urban Freight Lab conducted an alley inventory and truck load/unload occupancy study for the City of Seattle. Researchers collected data identifying the locations and infrastructure characteristics of alleys within Seattle’s One Center City planning area, which includes the downtown, uptown, South Lake Union, Capitol Hill, and First Hill urban centers. The resulting alley database includes GIS coordinates for both ends of each alley, geometric and traffic attributes, and photos. Researchers also observed all truck load/unload activity in selected alleys to determine minutes vacant and minutes occupied by trucks, vans, passenger vehicles, and cargo bikes. The researchers then developed alley management recommendations to promote safe, sustainable, and efficient goods delivery and pick-up.

Key Findings

The first key finding of this study is that more than 90% of Center City alleys are only one-lane wide. This surprising fact creates an upper limit on alley parking capacity, as each alley can functionally hold only one or two vehicles at a time. Because there is no room to pass by, when a truck, van, or car parks it blocks all other vehicles from using the alley. When commercial vehicle drivers see that an alley is blocked they will not enter it, as their only way out would be to back up into street traffic. Seattle Municipal code prohibits this, as well as backing up into an alley, for safety reasons.

When informed by the second key finding‚ 68% of vehicles in the alley occupancy study parked there for 15 minutes or less‚ it is clear that moving vehicles through alleys in short time increments is the only reasonable path to increase productivity. As one parked vehicle operationally blocks the entire alley, the goal of new alley policies and strategies should be to reduce the amount of time alleys are blocked to additional users.

The study surfaces four additional key findings:

  1. 87% of all vehicles in the 7 alleys studied parked for 30 minutes or less. Given the imperative to move alley traffic quickly, vehicles that need more parking time must be moved out of the alleys and onto the curb where they don’t block others.
  2. 15% of alleys’ pavement condition is so poor that delivery workers can’t pass through with loaded hand carts. Although trucks can drive over fairly uneven pavement without difficulty, it is not the case for delivery people walking with fully loaded handcarts. The alley pavement rating was done with a qualitative visual inspection to identify obvious problems; more detailed measurements would be needed to fully assess conditions.
  3. 73% of Center City area alleys contain entrances to passenger parking facilities. Placing garage entrances in alleys has been a city policy goal for years. But it increases the frequency of cars in alleys and adds demands on alley use. Understanding why cars are queuing for passenger garages located off alleys, and providing incentives and disincentives to reduce that, would help make alleys more productive.
  4. Alleys are vacant about half of the time during the business day. While at first blush this suggests ample capacity, the fact that an alley can only hold one-to-two parked trucks at a time means alleys are limited operationally and therefore are not a viable alternative to replace the use of curb CVLZs on city streets.

These findings indicate that, due to the fixed alley width constraint, load/unload space inside Seattle’s existing Center City area alleys is insufficient to meet additional future demand.