Research Topic: Bicycle Research: Cargo Bikes and Bike-Truck Interactions

Cargo e-bikes are two-, three-, or four-wheeled vehicles with cargo-carrying capacity. Since they are human-powered and often have an electric pedal assist, they are an alternative mode of delivering goods in dense urban areas. They present several advantages over the traditional modes of urban freight: they are more agile in navigating traffic, they occupy less space, and can potentially park anywhere. However, previous studies and pilots showed mixed results. The Urban Freight Lab has been collecting and analyzing data from cargo bike pilot studies and simulations to address questions on their operational efficiency, sustainability, and safety.

Bike-truck conflicts are interactions between a bicyclist and another road user such that at least one of the parties must change direction or speed to avoid collisions.

Paper

How Cargo Cycle Drivers Use the Urban Transport Infrastructure

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URL: https://doi.org/10.1016/j.tra.2022.103562

Publication: Transportation Research Part A: Policy and Practice

Volume: 167

Publication Date: 2023

Summary:

Electric cargo cycles are often considered a viable alternative mode for delivering goods in an urban area. However, cities in the U.S. are struggling to regulate cargo cycles, with most authorities applying the same rules used for motorized vehicles or traditional bikes. One reason is the lack of understanding of the relationships between existing regulations, transport infrastructure, and cargo cycle parking and driving behaviors.

In this study, we analyzed a cargo cycle pilot test in Seattle and collected detailed data on the types of infrastructure used for driving and parking. GPS data were augmented by installing a video camera on the cargo cycle and recording the types of infrastructure used (distinguishing between the travel lane, bicycle lane, and sidewalk), the time spent on each type, and the activity performed.

The analysis created a first-of-its-kind, detailed profile of the parking and driving behaviors of a cargo cycle driver. We observed a strong preference for parking (80 percent of the time) and driving (37 percent of the time) on the sidewalk. We also observed that cargo cycle parking was generally short (about 4 min), and the driver parked very close to the delivery address (30 m on average) and made only one delivery. Using a random utility model, we identified the infrastructure design parameters that would incentivize drivers to not use the sidewalk and to drive more on travel and bicycle lanes.

The results from this study can be used to better plan for a future in which cargo cycles are used to make deliveries in urban areas.

Authors: Dr. Giacomo Dalla ChiaraGriffin DonnellyŞeyma GüneşDr. Anne Goodchild

Recommended Citation:
Dalla Chiara, G., Donnelly, G., Gunes, S., & Goodchild, A. (2023). How Cargo Cycle Drivers Use the Urban Transport Infrastructure. Transportation Research Part A: Policy and Practice, 167, 103562. https://doi.org/10.1016/j.tra.2022.103562

Student Thesis and Dissertations

Survey on the Bike Commute Environment among Seattle Area Bike Planners and Advocates

URL: http://dx.doi.org/10.13140/RG.2.2.28619.31529

Publication Date: 2020

Summary:

Bike facilities like bike lanes, bike trails, and neighborhood greenways have been the backbone of Seattle’s bike planning policy with the goal of promoting active transportation, reducing car dependence, improving social equity, and eliminating bike accidents. While the equitable implementation of all of these facilities are still a priority for the Seattle’s Office of Planning and Community Development to increase viable commute mobility options, bike planning investments may not reflect the priorities shared by those in the bike community. Other factors in the bike commute environment were not present in Seattle’s Bike Master Plan, such as bike storage and shower facilities. There is also a lack of knowledge on whether there were priorities that people of color might have that are different. To better understand those priorities, this study sent out an online survey to 14 bike facility planning groups and bike community organizations around Seattle on the importance of nineteen different factors in the bike commute environment. For each factor, there were a range of values gauging the degree of importance of a bike commute factor to the bike commute environment, as well as a free response to allow respondents to elaborate on their answers. In total, 71 survey responses were received. The factor that placed the highest importance on the bike commute environment was bike racks and storage, higher than even bike facilities such as bike lanes. There were also not many differences in the priorities expressed by people of color, with the only significant difference being the weighting of sharrows, which had received significantly more support from people of color. Using the results of the survey, we recommend that the City of Seattle develop a bike commute environment index with a weighting scheme that is reflective of the priorities expressed in the survey, in addition to informing the City what are the community priorities in the bike commute environment.

Authors: Dr. Ed McCormack, Theodore Cheung, Katie Sheehy, Christine Bae

Recommended Citation:
Cheung, Theodore & Sheehy, Katie & Bae, Christine & McCormack, Edward. (2020). Survey on the Bike Commute Environment among Seattle Area Bike Planners and Advocates. 10.13140/RG.2.2.28619.31529.

Presentation

Exploring the Sustainability Potential of Urban Delivery Microhubs and Cargo Bike Deliveries

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URL: https://metrans.org/inuf_2022-papers_presentations

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

Publication Date: 2022

Summary:

Micro-consolidation implementations and 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.

Authors: Şeyma GüneşDr. Anne Goodchild

Recommended Citation:
Şeyma Güneş and Anne Goodchild (2022). Exploring the Sustainability Potential of Urban Delivery Microhubs and Cargo Bike Deliveries. 9th International Urban Freight Conference (INUF), Long Beach, CA May 2022.

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.

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

The Impact of Commercial Parking Utilization on Cyclist Behavior in Urban Environments

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URL: https://doi.org/10.1016/j.trf.2020.07.014

Publication: Transportation Research Part F: Traffic Psychology and Behaviour

Volume: 74

Pages: 67-80

Publication Date: 2020

Summary:

With growing freight operations within the United States, there continues to be a push for urban streets to accommodate trucks during loading and unloading operations. Currently, many urban locations do not provide loading and unloading zones, which results in trucks parking in places that can obstruct roadway infrastructure designated to vulnerable road users (e.g., pedestrians and cyclists). In an effort to understand the implications of these truck operations, a bicycle simulation experiment was designed to evaluate the impact of commercial vehicle loading and unloading activities on safe and efficient bicycle operations in a shared urban roadway environment. A counter-balanced, factorial design was chosen to explore three independent variables: commercial vehicle loading zone (CVLZ) sizes with three levels (no CVLZ, Min CVLZ, and Max CVLZ), courier position with also three levels (No courier, behind the truck, beside the truck), and loading accessories (Acc) with two levels (no Acc, and with Acc). Cyclist’s velocity and lateral position were used as performance measures. Data were obtained from 48 participants (24 women) resulting in 864 observations in 18 experimental scenarios. Linear Mixed-Effects Models (LMM) were developed to examine the effect of each independent variable level on bicyclist performance.

Results from LMM model suggest that loading zone size had the greatest effect on cyclist’s divergence. Additionally, when the courier was walking beside the truck, cyclist’s velocity significantly dropped to almost one m/sec in compared when the courier located behind the truck. The presence of accessories had the lowest influence on both velocity and lateral positions of cyclists. In the no CVLZ scenarios, the delivery vehicle was parked at the bike lane, therefore; cyclists had to choose between using the travel lane or the sidewalk. About one-third of participants decided to use the sidewalk. These findings could support better roadway and CVLZ design guidelines, which will allow our urban street system to operate more efficiently, safely, and reliably for all users.

Authors: Dr. Anne GoodchildManali ShethDr. Ed McCormack, Hisham Jashami, Douglas Cobb, David S. Hurtwitz

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.