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.

Biking for Goods: A Case Study on the Seattle Pedaling Relief Project

1. Introduction
One of the disruptions brought by the COVID-19 pandemic was the reduction of in-store shopping, and the consequent increase in online shopping and home deliveries. However, not everyone had equal access to online shopping and home-delivery services. Customers relying on food banks were forced to shop in-store even during the pandemic. In 2020, the Cascade Bicycle Club started the Pedaling Relief Project (PRP) – a not-for-profit home delivery service run by volunteers using bikes to pick up food at food banks and deliver to food bank customers, among other services.

The Urban Freight Lab collaborates with the Cascade Bicycle Club (CBC) to study and improve PRP operations. For this work, students in Prof. Anne Goodchild’s Transportation Engineering course on Transportation Logistics (CET 587) are undertaking a case study: to analyze the transport and logistics system of the Pedaling Relief Project and provide recommendations for how to improve operations.

2. Background
2.1. Food rescue at a glance
An estimated 94,500 tons of food from Seattle business establishments end up in compost and landfills each year, while many members of our community remain food insecure. The process of food rescuing consists of the gleaning of edible food from business establishments – called donor businesses such as grocery stores, restaurants, and commissary kitchens – that otherwise would enter the waste stream and be re-distributed to local food programs. Hunger relief agencies, also referred to as food banks, are non-profit organizations that collect rescued food, either directly from businesses or through food rescue distributors (such as Food Lifeline or Northeast Harvest) and re-distribute it to the community through meal programs, walk-ins, and pop-up food pantries, student backpack programs, among others.

Read more about the Seattle food rescue system in SCTL’s report (2020) on “Improving Food Rescue in Seattle: What Can Be Learned from a Supply Chain View?”

2.2. Pedaling Relief Project
In 2020 the Cascade Bicycle Club started the Pedaling Relief Project (PRP), a volunteer-based program that collaborates with local food banks to offer three main types of services — (1) grocery delivery, (2) food rescue, (3) little free pantry restocking — coordinating a network of volunteers on bikes.

Grocery delivery (GD) service consists of picking up grocery bags from food banks and performing delivery routes, distributing food to food bank customers that asked for home delivery services.
Food rescue (FR) services support the existing distributors by picking up food at business establishments and carrying rescued food to local food banks.
Little free pantries restocking (LFPR) services consist of picking up food at local food banks and carrying it to neighborhood micro pantries –containers placed on local streets and open to everyone to store food from donors to whoever needs it. Learn more about the Little free pantries project on thelittlefreepantries.org.

Volunteers use their own bikes, with some cargo carry capacity, or can request a bike trailer or cargo bike from the Cascade Bicycle Club.

2.3. Cargo Bikes
Cargo bikes are two/three/four-wheel bikes with some cargo-carrying capacity. They are increasingly used as an alternative mode to trucks and vans to transport goods in urban areas. Cargo bikes are often supported by an electric motor that assists the driver when pedaling. Compared to internal combustion engine vehicles, cargo bikes do not produce tailpipe emissions and they consume less energy than electric vans (Verlinghieri et al., 2021). They also offer several operational advantages: they are more agile in navigating urban road traffic, they can use alternative road infrastructure such as bike lanes and sidewalks to drive and park, they can park closer to their delivery destination, reducing walking distances and parking dwell times (Dalla Chiara et al., 2020).

3. Project instructions

The CBC provided access to anonymous data on the PRP operations for the exclusive use of the 2022 CET 587 course student cohort final projects. Students are asked to individually perform empirical research using the provided data and/or self-collected data on the PRP operations with the following objectives:

Empirically analyze and describe PRP operations.
Provide recommendations on what actions can be taken to improve PRP operations.

Projects will meet the following two requirements:

Use the provided data and/or self-collected and/or publicly sourced data to perform empirical analysis
Provide justified and concrete recommendations on how to improve the PRP.
Complete deliverables 1 and 2 (see below), which consist of 2 presentations, a project proposal, and a final project report.

Project progress timeline and deliverables:

Weeks	Progress & Deliverables
1-2	Become familiar with R language programming; PRP background and data
3	CBC gives a guest lecture about PRP
4-5	Project proposal; 2-minute lightning talk about the project proposal Deliverable 1: 1-page project proposal
6-10	Implement proposed methodology and perform research
11	Each student will give a 15-minute presentation of the main results of the project Deliverable 2: Final report

The following are potential project directions:

Analyze current routes performed by volunteers. How can they be improved? Get the work done more quickly, or with fewer bikes?
Analyze data from little free pantries restocking. Collect additional data on the use of Little Free Pantries by manual observations or by installing sensors in a few of them. Can we model demand and supply for food donations?
Collect and analyze GPS data by signing up and performing some of the PRP routes yourself. What type of infrastructure do cargo bikes need and how does street and curb use behavior differ between cargo bikes and vans? What can the city do to better support this type of activity?
Analyze volunteers’ behaviors data. Is it possible to model the supply of volunteers? Can you simulate different scenarios of volunteer supply?
Develop your own direction with approval.

Students will be provided with a base dataset on PRP operations. Students are encouraged to use other datasets self-collected or from public data sources (e.g. check out the SDOT Open Data Portal), to share ideas in class and among each other, to use as much as possible class time, guest lectures and office hours to ask questions and share ideas.

1: 1-page project proposal and 2-minute lightning talk describing motivation, project objective(s) and research question(s), proposed methodology (data to use/collect, methods to implement), and expected results.

2: Final report and 10-minute presentation describing data used, including sample size and sample statistics, how data collection was performed, empirical analysis performed using data and results from the analysis, and conclusions, key findings, and key recommendations.

Paper

Measuring Delivery Route Cost Trade-Offs Between Electric-Assist Cargo Bicycles and Delivery Trucks in Dense Urban Areas

Download PDF (3.79 MB)

Download Slides PDF (0.88 MB)

URL: https://doi.org/10.1186/s12544-019-0349-5

Publication: European Transport Research Review

Volume: 11

Publication Date: 2019

Summary:

Introduction

Completing urban freight deliveries is increasingly a challenge in congested urban areas, particularly when delivery trucks are required to meet time windows. Depending on the route characteristics, Electric Assist (EA) cargo bicycles may serve as an economically viable alternative to delivery trucks. The purpose of this paper is to compare the delivery route cost trade-offs between box delivery trucks and EA cargo bicycles that have the same route and delivery characteristics, and to explore the question, under what conditions do EA cargo bikes perform at a lower cost than typical delivery trucks?

Methods

The independent variables, constant variables, and assumptions used for the cost function comparison model were gathered through data collection and a literature review. A delivery route in Seattle was observed and used as the base case; the same route was then modeled using EA cargo bicycles.

Four separate delivery scenarios were modeled to evaluate how the following independent route characteristics would impact delivery route cost – distance between a distribution center (DC) and a neighborhood, number of stops, distance between each stop, and number of parcels per stop.

Results

The analysis shows that three of the four modeled route characteristics affect the cost trade-offs between delivery trucks and EA cargo bikes. EA cargo bikes are more cost effective than delivery trucks for deliveries in close proximity to the DC (less than 2 miles for the observed delivery route with 50 parcels per stop and less than 6 miles for the hypothetical delivery route with 10 parcels per stop) and at which there is a high density of residential units and low delivery volumes per stop.

Conclusion

Delivery trucks are more cost effective for greater distances from the DC and for large volume deliveries to one stop.

Authors: Polina ButrinaDr. Anne GoodchildManali ShethDr. Ed McCormack

Recommended Citation:
Sheth, Manali, Polina Butrina, Anne Goodchild, and Edward McCormack. "Measuring delivery route cost trade-offs between electric-assist cargo bicycles and delivery trucks in dense urban areas." European Transport Research Review 11, no. 1 (2019): 11.

An Examination of the Impact of Increasing Commercial Parking Utilization on Cyclist Safety in Urban Environments

There is little research on the behavioral interaction between bicycle lanes and commercial vehicle loading zones (CVLZ) in the United States. These interactions are important to understand, to preempt increasing conflicts between truckers and bicyclists. In this study, a bicycling simulator experiment examined bicycle and truck interactions. The experiment was successfully completed by 48 participants. The bicycling simulator collected data regarding a participant’s velocity and lateral position. Three independent variables reflecting common engineering approaches were included in this experiment: pavement marking (L1: white lane markings with no supplemental pavement color, termed white lane markings, L2: white lane markings with solid green pavement applied on the conflict area, termed solid green, and L3: white lane markings with dashed green pavement applied on the conflict area, termed dashed green), signage (L1: No sign and L2: a truck warning sign), and truck maneuver (L1: no truck in CVLZ, L2: truck parked in CVLZ, and L3: truck pulling out of CVLZ).

The results showed that truck presence does have an effect on bicyclist’s performance, and this effect varies based on the engineering and design treatments employed. Of the three independent variables, truck maneuvering had the greatest impact by decreasing mean bicyclist velocity and increasing mean lateral position. It was also observed that when a truck was present in a CVLZ, bicyclists had a lower velocity and lower divergence from right-edge of bike lane on solid green pavement, and a higher divergence from the right-edge of bike lane was observed when a warning sign was present.

Paper

Factors Impacting Bicyclist Lateral Position and Velocity in Proximity to Commercial Vehicle Loading Zones: Application of a Bicycling Simulator

Download PDF (7.70 MB)

URL: https://doi.org/10.1016/j.aap.2019.01.024

Publication: Accident Analysis & Prevention

Volume: 125

Pages: 29-39

Publication Date: 2019

Summary:

Authors: Manali ShethDr. Anne GoodchildDr. Ed McCormack, Masoud Ghodrat Abadia, David S. Hurwitz

Recommended Citation:
Abadi, Masoud Ghodrat, David S. Hurwitz, Manali Sheth, Edward McCormack, and Anne Goodchild. (2019) Factors Impacting Bicyclist Lateral Position and Velocity in Proximity to Commercial Vehicle Loading Zones: Application of a Bicycling Simulator. Accident Analysis and Prevention, 125, 29–39. https://doi.org/10.1016/j.aap.2019.01.024

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:

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?
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?
How does the e-bike system affect UPS’ failed first delivery (FFD) attempt rate along the route?
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?
How do e-bike delivery operations impact pedestrian, other bike, and motor traffic?

Technical Report

Multimodal Intersections: Resolving Conflicts between Trains, Motor Vehicles, Bicyclists and Pedestrians

Download PDF (9.16 MB)

URL: https://rosap.ntl.bts.gov/view/dot/35068

Publication: Oregon State Department of Transportation

Publication Date: 2017

Summary:

This research report investigates the relationship between pedestrians and bicyclists on paths parallel to railroad tracks and with a road perpendicular to the path. The possible conflicts at intersections within these design parameters are of concern to ODOT, and therefore, has been recognized as an opportunity to conduct research that improves this type of intersection. The goal of this research project is to create a Guidebook that suggests appropriate path or road treatments for crossings, while also acknowledging and complimenting the unique site conditions present at the intersection. The report contains an extensive literature review, including existing railroad treatment options, and a description of the conducted field surveys and pedestrian, bicycle, vehicle, and train counts from the video. The report could help future work, such as developing more design solutions for paths parallel to tracks and the road perpendicular to the path. A preliminary guidebook is exemplified in the conducted case studies. It is intended to be a user friendly tool for city planners and engineers to assess a crossing and identify appropriate treatment options to improve the path and road user environment, and overall safety for all users.

Authors: Anna Bovbjerg AlligoodDr. Ed McCormackDr. Anne GoodchildManali Sheth

Recommended Citation:
Goodchild, Anne V., Edward McCormack, Anna Bovbjerg, and Manali Sheth. Multimodal Intersections: Resolving Conflicts Between Trains, Motor Vehicles, Bicyclists and Pedestrians. No. FHWA-OR-18-04. Oregon. Dept. of Transportation, 2017.

Technical Report

Insights from Driver Parking Decisions in a Truck Simulator to Inform Curb Management Decisions

Download PDF (3.37 MB)

URL: http://hdl.handle.net/1773/49802

Publication Date: 2023

Summary:

Millions of people who live and work in cities purchase goods online. As ecommerce and urban deliveries spike, there is an increasing demand for curbside loading and unloading space. To better manage city curb spaces for urban freight, city planners and decision makers need to understand commercial vehicle driver behaviors and the factors they consider when parking at the curb.

Urban freight transportation is a diverse phenomenon. Commercial vehicle drivers must overcome several obstacles and adapt to various rules and policies to properly navigate the intricate metropolitan network and make deliveries and pick-ups. However, other road users and occasionally municipal planners generally view them as contributing considerably to urban congestio, responsible for unauthorized parking, double parking, and exceeding their legal parking time.

These realities reflect the need for a thorough comprehension of commercial vehicle operators’ core decision-making procedures and parking habits to inform and adjust curb management policies and procedures. However, more robust corroborated literature on the subject is needed. The information used in these studies is typically obtained from empirical field research, which, while valuable, is limited to certain situations and case scenarios. Therefore, to improve the operation of urban transportation networks, it is necessary to study commercial vehicle drivers’ parking behavior in a controlled environment.

This project used a heavy vehicle driving simulator to examine commercial vehicle drivers’ curbside parking behaviors in various environments in shared urban areas. Also observed were the interactions between commercial vehicle drivers and other road users.

The experiment was successfully completed by 12 participants. Five independent variables were included in this experiment: number of lanes (two-lane and four-lane roads), bike lane existence, passenger vehicle parking space availability, commercial vehicle loading zones (CVLZs) (no CVLZ, occupied CVLZs, and unoccupied CVLZs), and parking time (short-term parking: 3 to 5 minutes and long-term parking: 20 to 60 minutes). The heavy vehicle driving simulator also collected data regarding participants’ driving speed, eye movement, and stress level.

Results from the heavy vehicle driving simulator experiment indicated that the presence of a bike lane had significant effects on commercial vehicle drivers’ parking decisions., but only a slight effect on fixation duration times. The average fixation duration time, representing how long participants looked at a particular object, on the road with a bike lane was 4.81 seconds, whereas it was 5.25 seconds on roads without a bike lane. Results also showed that the frequency of illegal parking (not parking in the CVLZs) was greater during short-term parking activities, occurring 60 times (45 percent of parking maneuvers). Delivery times also had a slight effect on commercial vehicles’ speed while searching for parking (short-term parking was 17.7 mph; long term parking was 17.2 mph) and on drivers’ level of stress (short-term parking was 8.16 peaks/mins; long-term parking was 8.36 peaks/mins). Seven percent of participants chose to park in the travel lane, which suggested that commercial vehicle operators prioritize minimizing their walking distance to the destination over the violation of parking regulations.

The limited sample size demonstrated the value of our experimental approach but limited the strength of the recommendations that can be applied to practice. With that limitation acknowledged, our preliminary recommendations for city planners include infrastructure installation (i.e., convex mirrors installed at the curbside and CVLZ signs) to help drivers more easily identify legal parking spaces, and pavement markings (i.e., CVLZs, buffered bike lanes) to improve safety when parking. Parking time limits and buffers for bike lanes could improve efficient operation and safety for cyclists and other road users.

For future work, larger sample sizes should be collected. Additional factors could be considered, such as increased traffic flow, pedestrian traffic, conflicts among multiple delivery vehicles simultaneously, various curb use type allocations, and different curb policies and enforcement. Including a larger variety of commercial vehicle sizes and loading, zone sizes would also be of value. A combination of field observations and a driving simulator study could also help validate this investigation’s outcomes.

Authors: Dr. Andisheh RanjbariDr. Anne GoodchildDr. Ed McCormackRishi Verma, David S. Hurwitz (Oregon State University), Yujun Liu (Oregon State University), Hisham Jashami (Oregon State University)

Recommended Citation:
Goodchild, A., McCormack, E., Hurwitz, D., Ranjbari, A., Verma, R., Liu, Y., & Jashami, H. (2023). Insights from Driver Parking Decisions in a Truck Simulator to Inform Curb Management Decisions. PacTrans.

Paper

A Description of Fatal Bicycle Truck Accidents in the United States: 2000 to 2010

URL: https://trid.trb.org/view/1394216

Publication: Transportation Research Board 95th Annual Meeting

Volume: 16-5911

Publication Date: 2016

Summary:

Bicycling is being encouraged across the US and the world as a low-impact, environmentally friendly mode of transportation. In the US, many states and cities, especially cities facing congestion issues, are encouraging cycling as an alternative to automobiles. However, as cities grow and consumption increases, freight traffic in cities will increase as well, leading to higher amounts of interactions between cyclists and trucks. This paper will describe where and how accidents between cyclists and trucks occur. From 2000 to 2010, 807 bicyclists were killed the United States in accidents involving trucks. In 2009, trucks accounted for 9.5% of fatal bicycle accidents, despite trucks only accounting for 4.5% of registered vehicles. The typical fatal bike-truck accident happens in an urban area on an arterial street with a speed limit of 35 or 45 mph. It is about equally likely to occur mid-block or at an intersection. Most accidents involved trucks going straight (56%), and right-turning trucks were involved in a much larger number of accidents (24%) than left turning trucks (7%). Methods such as providing bicycle lanes, or even physically separated bicycle tracks, will not be sufficient to address bicycle-truck collisions, as a significant number of accidents (49%) occur in intersections or are intersection related. Cities with a higher mode-share of bicycling had a lower rate of bicycle-truck fatality accidents.

Authors: Dr. Anne Goodchild, Jerome Drescher

Recommended Citation:
Drescher, Jerome and Anne Goodchild. (2016), "A Description of Fatal Bicycle Truck Accidents in the United States: 2000 to 2010," Accepted for presentation at the 95th Transportation Research Board Annual Meeting, Washington DC, January 10-14. [Paper # 16-5911]

Paper

How Cargo Cycle Drivers Use the Urban Transport Infrastructure

Download PDF (10.47 MB)

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.