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Report

The Final 50 Feet of the Urban Goods Delivery System (Final Report)

 
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Publication Date: 2018
Summary:

Urban Freight Lab’s foundational report is the first assessment in any American city of the privately-owned and operated elements of the Final 50 Feet of goods delivery supply chains (the end of the supply chain, where delivery drivers must locate both parking and end customers). These include curb parking spaces, private truck freight bays and loading docks, street design, traffic control, and delivery policies and operations within buildings.

Goods delivery is an essential but little-noticed activity in urban areas. For the last 40 years, deliveries have been mostly performed by a private sector shipping industry that operates within general city traffic conditions. However, in recent years e-commerce has created a rapid increase in deliveries, which implies an explosion of activity in the future.

Meeting current and future demand is creating unprecedented challenges for shippers to meet both increased volumes and increasing customer expectations for efficient and timely delivery. Anecdotal evidence suggests that increasing demand is overwhelming goods delivery infrastructure and operations. Delivery vehicles parked in travel lanes, unloading taking place on crowded sidewalks, and commercial truck noise during late night and early morning hours are familiar stories in urban areas.

These conditions are noticeable throughout the City of Seattle as our population and employment rapidly increase. However, goods delivery issues are particularly problematic in Seattle’s high-density areas of Downtown, Belltown, South Lake Union, Pioneer Square, First Hill, Capitol Hill and Queen Anne, described as Seattle’s “Center City”. Urban goods transportation makes our economy and quality of life possible.

As the Seattle Department of Transportation (SDOT) responds to the many travel challenges of a complex urban environment, we recognize that goods delivery needs to be better understood and supported to retain the vitality and livability of our busiest neighborhoods.

U.S. cities do not have much information about the urban goods delivery system. While public agencies have data on city streets, public transportation and designated curbside parking, the “final 50 feet” in goods delivery also utilizes private vehicles, private loading facilities, and privately-owned and operated buildings outside the traditional realm of urban planning.

Bridging the information gap between the public and private sectors requires a new way of thinking about urban systems. Specifically, it requires trusted data sharing between public and private partners, and a data-driven approach to asking and answering the right questions, to successfully meet modern urban goods delivery needs.

The Urban Freight Lab (UFL) provides a standing forum to solve a range of short-term as well as long-term strategic urban goods problem solving, that provides evidence of effectiveness before strategies are widely implemented in the City.

Recommended Citation:
Supply Chain Transportation & Logistics Center. (2018) The Final 50 Feet of the Urban Goods Delivery System.
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.

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.
Paper

Delivery Process for an Office Building in the Seattle Central Business District

 
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Publication: Transportation Research Record: Journal of the Transportation Research Board
Volume: Transportation Research Board 97th Annual Meeting
Publication Date: 2018
Summary:

Movement of goods within a central business district (CBD) can be very constraining with high levels of congestion and insufficient curb spaces. Pick-up and delivery activities encompass a significant portion of urban goods movement and inefficient operations can negatively impact the already highly congested areas and truck dwell times. Identifying and quantifying the delivery processes within the building is often difficult.

This paper introduces a systematic approach to examine freight movement, using a process flow map with quantitative delivery times measured during the final segment of the delivery process. This paper focuses on vertical movements such as unloading/loading activities, taking freight elevators, and performing pick-up/delivery operations. This approach allows us to visualize the components of the delivery process and identify the processes that consume the most time and greatest variability. Using this method, the authors observed the delivery process flows of an office building in downtown Seattle, grouped into three major steps: 1. Entering, 2. Delivering, 3. Exiting. This visualization tool provides researchers and planners with a better understanding of the current practices in the urban freight system and helps identify the non-value-added activities and time that can unnecessarily increase the overall delivery time.

Authors: Haena KimDr. Anne Goodchild, Linda Ng Boyle
Recommended Citation:
Kim, Haena, Linda Ng Boyle, and Anne Goodchild. "Delivery Process for an Office Building in the Seattle Central Business District." Transportation Research Record 2672, no. 9 (2018): 173-183. 
Report

The Final 50 Feet of the Urban Goods Delivery System (Executive Summary)

 
Download PDF  (1.91 MB)
Publication Date: 2018
Summary:

Urban Freight Lab’s foundational report is the first assessment in any American city of the privately-owned and operated elements of the Final 50 Feet of goods delivery supply chains (the end of the supply chain, where delivery drivers must locate both parking and end customers). These include curb parking spaces, private truck freight bays and loading docks, street design, traffic control, and delivery policies and operations within buildings.

Two key goals have been identified early for the Final 50 Feet program:

  • Reducing truck time in a load/unload space in the city (“dwell time”)
  • Minimizing failed first package deliveries. About 8-10% of first delivery attempts in urban areas are unsuccessful, creating more return trips
Recommended Citation:
Supply Chain Transportation & Logistics Center. (2018) The Final 50 Feet of the Urban Goods Delivery System: Executive Summary.

UPS E-Bike Delivery Pilot Test in Seattle: Analysis of Public Benefits and Costs (Task Order 6)

The City of Seattle granted a permit to United Parcel Service, Inc. (UPS) in fall 2018 to pilot test a new e-bike parcel delivery system in the Pioneer Square/Belltown area for one year. The Seattle Department of Transportation (SDOT) commissioned the Urban Freight Lab (UFL) to quantify and document the public impacts of this multimodal delivery system change in the final 50 feet of supply chains, to provide data and evidence for development of future urban freight policies.

The UFL will conduct analyses into the following research questions:

  1. What are the total changes in VMT and emissions (PM and GHG) to all three affected cargo van routes due to the e-bike pilot test in the Pike Place Market and neighboring areas?
  2. What is the change in the delivery van’s dwell time, e.g. the amount of time the van is parked, before and after introducing the e-bike?
  3. How does the e-bike system affect UPS’ failed first delivery (FFD) attempt rate along the route?
  4. If UPS begins to stage drop boxes along the route for the e-bike (instead of having to replenish from the parked trailer) what are the impacts to total VMT and emissions?
  5. How do e-bike delivery operations impact pedestrian, other bike, and motor traffic?
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

Do Parcel Lockers Reduce Delivery Times? Evidence from the Field

 
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Publication: Transportation Research Part E: Logistics and Transportation Review
Volume: 172 (2023)
Publication Date: 2023
Summary:

Common carrier parcel lockers have emerged as a secure, automated, self-service means of delivery consolidation in congested urban areas, which are believed to mitigate last-mile delivery challenges by reducing out-of-vehicle delivery times and consequently vehicle dwell times at the curb. However, little research exists to empirically demonstrate the environmental and efficiency gains from this technology. In this study, we designed a nonequivalent group pre-test/post-test control experiment to estimate the causal effects of a parcel locker on delivery times in a residential building in downtown Seattle. The causal effects are measured in terms of vehicle dwell time and the time delivery couriers spend inside the building, through the difference-in-difference method and using a similar nearby residential building as a control. The results showed a statistically significant decrease in time spent inside the building and a small yet insignificant reduction in delivery vehicle dwell time at the curb. The locker was also well received by the building managers and residents.

Recommended Citation:
Ranjbari, A., Diehl, C., Dalla Chiara, G., & Goodchild, A. (2023). Do Commercial Vehicles Cruise for Parking? Empirical Evidence from Seattle. Transportation Research Part E: Logistics and Transportation Review, 172, 103070. https://doi.org/10.1016/j.tre.2023.103070 
Paper

Toward Predicting Stay Time for Private Car Users: A RNN-NALU Approach

 
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Publication: IEEE Transactions on Vehicular Technology
Volume: 71 (6)
Pages: 6007 - 6018
Publication Date: 2022
Summary:

Predicting the stay time of private cars has various applications in location-based services and traffic management. Due to the associated randomness and uncertainty, achieving the promising performance of stay time prediction is a challenge. We propose an RNN-based encoder model to solve this problem, which consists of three components, i.e., an encoder module, an exception module, and an MLP dropout. First, we encode the stay behaviour into hidden vectors at a specific time to avoid the effect of time sparsity. The encoder module utilizes a multilayer perceptron (MLP) to learn spatiotemporal features from the historical trajectory data, such as the inherent relationship between the stop points and corresponding stay time. We proved a linear relationship problem that cannot be ignored in the stay time prediction problem. In particular, we have added basic arithmetic logic units to the network framework to find linear relationships. By reconstructing the basic arithmetic and logical relations of the network, we have improved the ability of the neural network to handle linear relations and the extrapolation ability of the neural network. Our method can remember the number patterns seen in the training set very well and infer this representation reasonably. Moreover, we utilize the dropout technique to prevent the prediction model from overfitting. We perform extensive experiments based on a large-scale real-world private car trajectory dataset. The experimental results demonstrate that our method achieves an RMSE of 0.1429 and a MAPE of 55.8533%. Furthermore, the results verify the effectiveness and advantages of the proposed model when compared with the benchmarks.

Authors: Amelia Regan, Qibo Zhang; Fanzi Zeng; Zhu Xiao; Hongbo Jiang; Kehua Yang; Yongdong Zhu
Recommended Citation:
Q. Zhang et al., "Toward Predicting Stay Time for Private Car Users: A RNN-NALU Approach," in IEEE Transactions on Vehicular Technology, vol. 71, no. 6, pp. 6007-6018, June 2022, doi: 10.1109/TVT.2022.3164978.
Presentation

Improving Delivery Efficiency and Understanding User Behavior through Common Carrier Parcel Lockers

 
Publication: 9th International Urban Freight Conference, Long Beach, May 2022
Publication Date: 2022
Summary:

Common-carrier parcel lockers have emerged as a secure, automated, self-service means of delivery consolidation in congested urban areas, which are believed to mitigate last-mile delivery challenges by reducing out-of-vehicle delivery times and consequently vehicle dwell times at the curb. However, little research exists to empirically demonstrate the environmental and efficiency gains from this technology.

In this study, we designed a nonequivalent group pretest/post-test experiment to estimate the causal effects of a common-carrier locker in a residential building in downtown Seattle, WA. The causal effects are measured in terms of vehicle dwell time and the time delivery drivers spend inside the building, through the difference-in-difference method and using a similar residential building as a control.

The results showed a statistically significant decrease in time spent inside the building and a small yet insignificant reduction in vehicle dwell times.

Recommended Citation:
Andisheh Ranjbari, Caleb Diehl, Giacomo Dalla Chiara, and Anne Goodchild (2022). Improving Delivery Efficiency and Understanding User Behavior through Common Carrier Parcel Lockers. 9th International Urban Freight Conference (INUF), Long Beach, CA May 2022.
Paper

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

 
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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.

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