As e-commerce and urban deliveries spike, there is an increasing demand for curbside loading/unloading space. However, commercial vehicle drivers face numerous challenges while navigating dense urban road networks. Literature on the topic of how commercial vehicle drivers make choices about when and where to park is scarce, and data from those available studies usually come from field studies in which limited situations can be observed, without experimental controls, and there is an absence of known driver characteristics. Therefore, this study used a heavy vehicle driving simulator to examine the behavior of commercial vehicle drivers in various parking and delivery situations. A heavy vehicle driving simulator experiment examined the behaviors of commercial vehicle drivers under various parking and delivery situations. The heavy vehicle experiment was completed by 14 participants. The experiment included 24 scenarios with several independent variables, including number of lanes (two-lane and four-lane roads), with/without a bike lane, available/unavailable passenger vehicle parking space, CVLZs (no CVLZ, occupied CVLZ, and unoccupied CVLZ), and delivery time (3-5 mins and 20-60 mins). By collecting speed, eye-movement, and stress data during the experiment, the project produced results that support the development of more effective curb management strategies that will maintain efficient delivery operations while balancing the needs of all road users.
Publication Type: Technical Report
Interview Results: Carrier Perspectives on Delivery Operations and Zero-Emission Zones in Downtown Portland
In 2023, Portland was awarded a U.S. Department of Transportation SMART grant to pilot a Zero-Emission Delivery Zone (ZEDZ). Funding for this Stage One SMART grant will allow PBOT to trial changing three to five truck loading zones into “Zero-Emission Delivery” loading zones in downtown Portland. The Urban Freight Lab (UFL) was approached by PBOT to assist in their SMART grant implementation by providing subject matter expertise on the topics of urban freight, curb management, and freight decarbonization. The UFL team created a questionnaire and interview guide to inquire about current carrier operations, current and future fleet composition, and loading activities of carriers operating in the City of Portland.
The selected organizations were identified as carriers or organizations that make deliveries into the proposed Zero-Emission Delivery Zone (ZEDZ) in downtown Portland. The UFL reached out to over 20 different organizations spanning different business sectors and company sizes, from large national parcel carriers to regional wholesale distributors to small delivery companies. Ultimately, only four organizations responded to requests for interviews. Between June and August 2024, the UFL conducted these interviews. Table 1 provides an overview of the companies interviewed and their main business activities. Company and organization names are omitted from this report to anonymize the respondents.
The goal of the interviews was to understand the parking behaviors and fleets of individual companies. In particular, the interviewers focused on understanding the current delivery operations in the Portland area, the related parking and routing behaviors of their delivery drivers, fleet composition, and the challenges they face in performing deliveries in the study area.
Each interview was 1-hour long and was guided on a questionnaire reported in the appendix. The questionnaire was developed into three sections:
- Organization – Describe their main business activities, logistics network and fleet composition.
- Routing, parking, and payment behaviors – Description of typical drivers’ operations in the City of Portland and specifically downtown, including routing and parking behaviors, as well as use of paid parking and citations.
- Future scenarios – Companies were asked about zero-emission vehicles and implications of the ZEDZ on operations.
This report contains the main results of the interviews, including a description of the logistics network infrastructure, delivery operations, and curb use behaviors. The final section provides the key lessons learned.
Insights from Driver Parking Decisions in a Truck Simulator to Inform Curb Management Decisions
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.
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.
Using Truck Fleet Management GPS Data to Develop the Foundation for a Performance Measures Program
Global positioning systems (GPS) used for fleet management by trucking companies provide probe data that can support a truck performance-monitoring program. This paper discusses the steps taken to acquire fleet management data and then process those data so they can eventually be used for a network-based truck performance measures program. While other studies have evaluated truck travel by using GPS, they have used a limited number of project-specific and temporary devices that have collected frequent location reads, permitting a fine-grained performance analysis of specific roadway segments. In contrast, this fleet management GPS data project involved infrequent reads but a relatively large number of different trucks with ongoing data collection. The most effective approach to obtaining the fleet management data was to purchase the data directly from GPS vendors. Because a performance measures program ultimately monitors trips generated by trucks as they travel between origins and destinations, an algorithm was developed to extract trip end information from the data. The large volume of data required automated processing without manual intervention. Because performance measures require travel times and speeds, it was also necessary to evaluate whether speed data from a large number of trucks could compensate for infrequent location reads. Spot speeds recorded by the trucks’ GPS devices were compared to speed data from roadway loops. The researchers concluded that spot speed data can indicate free flow conditions, but sufficient quantities of data are probably necessary to measure congested travel.
McCormack, E. D., Zhao, W., & Tabat, D. (2011). GPS truck data performance measures program in Washington State. Washington State Department of Transportation, Office of Research.
Development of a Freight Benefit/Cost Methodology for Project Planning
Casavant, Ken, Anne Goodchild, Ed McCormack, Zun Wang, B. Starr McMullen, and Daniel Holder. "Development of a Freight Benefit/Cost Methodology for Project Planning."
Field Test of Unmanned Aircraft Systems (UAS) to Support Avalanche Monitoring
The Norwegian Public Roads Administration, the Norwegian Geotechnical Institute, and SINTEF conducted a field test with a unmanned aerial system (UAS) with various instruments at the research station Fonnbu in Stryn. The purpose of the test was to evaluate the use of instrumented drones for monitoring and assessing avalanche danger. The instruments tested included optical and thermal imaging, laser scanning and ground-penetrating radar. Resulting datasets included 3D models (point clouds and height maps), multispectral and radiometric, thermal images and radargrams.
Technology and Safety on Urban Roadways: The Role of ITS in WSDOT
This report examines the relationship between Intelligent Transportation Systems (ITS) and safety from an urban perspective.
Existing urban ITS systems are either system-level or site-level applications. System-level ITS, such as freeway management systems or traffic signal networks, address safety concerns only indirectly. These systems are designed to improve traffic flows and thus indirectly reduce collisions caused by congestion. Other system-level ITS used to increase the efficiency of transit, commercial vehicle, and emergency service operations also benefit safety indirectly. Site-level ITS applications, such as railroad/highway crossing warnings or work zone systems, are installed to directly address safety concerns. However, these applications are limited to specific locations identified as hazardous.
Most urban crashes in Washington involve multiple vehicle collisions caused by driver error at locations that have not been identified as hazardous. Future ITS systems known collision avoidance systems (CAS) hold considerable promise for urban roadway safety because these in-vehicle devices will inform drivers of judgment errors and can do so at many locations along an urban roadway system.
A handful of ITS applications are so well tested that they can be aggressively pursued by WSDOT as tools to reduce urban crashes. Most of these applications include the various systems, such a ramp meters and incident detection, used for freeway management. Other ITS safety applications, while promising, still need to be fully documented and are best used as demonstration applications. Most of these applications involve sensor technology used to warn drivers about road and roadside hazards at specific sites. The greatest safety benefit from ITS may come from in-vehicle collision warning systems. These applications should evolve from a number of large federal research projects and private industry initiatives that are under way. Given their potential impact on safety, WSDOT should monitor applications of these projects.
McCormack, E., Legg, B. (2000). Technology and Safety on Urban Roadways: The Role of ITS in WSDOT. Research Report, Washington State Transportation Center (TRAC). Washington State Transportation Center, U.S. Department of Transportation.
Development and Analysis of a GIS-Based Statewide Freight Data Flow Network
harm the state’s economy, the Washington State Department of Transportation
(WSDOT), in partnership with Transportation Northwest (TransNow) commissioned
researchers at the University of Washington and Washington State University to
undertake freight resiliency research to:
- Understand how disruptions of the state’s freight corridors change the way
trucking companies and various freight-dependent industries route goods, - Plan to protect freight-dependent sectors that are at high risk from these disruptive
events, and - Prioritize future transportation investments based on the risk of economic loss to
the state
this research developed the first statewide multimodal freight model for Washington
State. The model is a GIS-based portrayal of the state’s freight highway, arterial, rail,
waterway and intermodal network and can help the state prioritize strategies that protect industries most vulnerable to disruptions.
- Predict how shipments will be re-routed during disruptions, and
- Analyze the level of resiliency in various industry sectors in Washington State
sectors and its dependence on the I-90 corridor, while showing how the state’s diesel
delivery system is highly resilient and isn’t linked to I-90.
WSDOT will be able to evaluate the impact of freight system disruptions on each of
them. This will improve WSDOT’s ability to develop optimal strategies for highway
closures, and prioritize improvements to the system based on the relative impact of the
disruption.
organization building a state freight model. First, the researchers had to decide on the
level of spatial and temporal detail to include in the statewide GIS freight model. This
decision has significant consequences for data resolution requirements and results.
Including every road in Washington would have created a cumbersome model with a
large number of links that weren’t used. However, in order to analyze routing during a
disruption all possible connections must exist between origin and destination points in the model. While the team initially included only the core freight network in the model,
ultimately all road links were added to create complete network connectivity.
collection for the two case studies was resource intensive. Supply chain data is held by
various stakeholders and typically not listed on public websites, and it isn’t organized by
those stakeholders for use in a freight model. In most cases it’s difficult to assure data
quality. The team learned that the most difficult data to obtain is data on spatially or
temporally variable attributes, such as truck location and volume. So they developed a
method to estimate the importance of transportation links without commodity flow data.
origin and destination (O/D) pair in the state, and the shortest travel-time re-route for
each O/D pair after a disruption. The routing logic in the model is based on accepted
algorithms used by Google Maps and MapQuest. Phase III of the state’s freight
resiliency research was funded by WSDOT and will result in improved truck freight
routing logic for the model in 2011.
and that some supply chains have built flexibility into their operations and are resilient
while others are not, which leads to very different economic consequences. The results
of these case studies significantly contributed to WSDOT’s understanding of goods
movement and vulnerability to disruptions.
implement the research findings and complete the state freight model. In 2009, the
National Cooperative Freight Research Program (NCFRP) funded development of new
methodology to collect and analyze sub-national commodity flow information. This
NCFRP project, funded at $500,000, will be completed in 2010 and provide a mechanism for states to accurately account for corridor-level commodity flows. If funds are available to implement the new methodology in Washington State, the state’s freight
model will use the information to map these existing origin destination commodity flows
onto the freight network, evaluate the number of re-routed commercial vehicles, and their increased reroute distance from any disruption. This will allow WSDOT to develop
prioritized plans for supply chain disruptions, and recommend improvements to the
system based on the economic impact of the disruption.
Goodchild, Anne V., Eric L. Jessup, Edward D. McCormack, Derik Andreoli, S Rose, Chilan Ta and Kelly Pitera. “Development and Analysis of a GIS-Based Statewide Freight Data Flow Network.” (2009).
Analyzing the Long-Term Impacts of COVID-19 Disruption on Travel Patterns
The rapid spread of COVID-19 pandemic in the U.S. spurred many state governments to take extensive actions for social distancing and issue stay-at-home orders to reduce the spread of the virus. Washington State and all other States in the PacTrans region have issued stay-at-home orders that include school closures, telecommuting, bars/restaurants closures, and group gathering bans, among others. These actions create significant changes to daily life and while some travel patterns will gradually restore by the end of outbreak, some may remain changed for a much longer period.
Behaviors that may see a lasting response include commuting, grocery shopping, business meetings, and even social interactions. Working from home for 2-3 months may change people’s attitudes toward telecommuting, and some may continue to do so a few days a week once the stay-at-home orders are lifted. Some employers may also shift their telecommute policies and provide/encourage working from home. In recent years, with the growth of e-commerce, many grocery stores had started to offer home deliveries; however, online grocery shopping experienced a fast and sudden boom during the pandemic. This has resulted in quick service adoption, and therefore some people may continue to do online grocery shopping once things go back to normal. Moreover, as people shift to online grocery shopping, they may proactively make a list and place orders less frequently compared to them going to store, resulting in fewer shopping trips. Some business meetings and even personal gatherings may also move online as people learn about and try alternate ways of communicating during the outbreak. Some may also consider enrolling in distant learning programs instead of attending in-person educational programs. There may also be significant changes in modes of travel. Some transit commuters may choose other modes of transportation for a while, and people may choose to drive or bike instead of taking a ride-hailing trip.
The goal of this research is to understand how COVID-19 disruption has affected people’s activity and travel patterns during the pandemic, and how these changes may persist in a post-pandemic era.
Mackenzie D., Jabbari P., Ranjbari A. Analyzing the Long-Term Impacts of COVID-19 Disruption on Travel Patterns. Pacific Northwest Transportation Consortium (PacTrans). 2020. http://hdl.handle.net/1773/46655.
Freight Data from Intelligent Transportation System Devices
Hallenbeck, M. E., McCormack, E., Nee, J., & Wright, D. (2003). Freight Data from Intelligent Transportation System Devices (No. WA-RD 566.1,). The Center.