Project Budget: $180,000 (UW amount: $80,000)
- University of Washington, Urban Freight Lab (UFL)
This study will use a driving simulator to design a simulation experiment to test the behavior of commercial vehicle drivers under various parking and delivery situations and to analyze their reactions. The ability to modify the simulator’s environment will allow the researchers to relatively easily test a range of scenarios that correspond to different delivery and parking situations.
The simulation experience will be designed in a quarter-cab truck simulator at Oregon State University’s Driving and Bicycling Simulator Laboratory. Various simulation environments will be defined by changing road characteristics (such as land use, number of travel lanes, nearby signals, traffic in adjacent lanes), curb allocations (such as paid parking, commercial vehicle loading zones, and passenger load zones, as well as the size of the loading zones and their availability at the time of the vehicle arrival at the blockface), and other road users (passenger cars, ridehailing vehicles, bikes). Drivers from various categories of age, gender, experience level (less experiences vs. seasoned) and goods type (documents, packages, or heavy goods) will be invited to operate the simulator and make a parking decision in a few simulated environments. The simulator can also monitor distraction (through eye tracking) and the stress level of drivers (through galvanic skin response) when making these decisions and interacting with other road users.
Analyzing parking decisions and driver stress levels based on roadway and driver characteristics will provide insights on travel behaviors and the parking decision-making process of commercial vehicle drivers, and will help city planners improve street designs and curb management policies to accommodate safe and efficient operations in a shared urban roadway environment.
The unique needs of delivery trucks and commercial vehicles are not acknowledged in current design practices. This study is intended to fill these gaps and serve as a valuable resource for policy makers, transportation engineers and urban planners.
Project Budget: $2.9M (UW amount: $500k)
- Pacific Northwest National Lab (PNNL)
- Urban Freight Lab (UFL), University of Washington
- Lawrence Berkeley National Laboratory (LBNL)
- Lacuna Technologies, Inc. (Lacuna)
- National Renewable Energy Laboratory (NREL)
Curbs are a critical interfacing layer between movement and arrival in urban areas—the layer at which people and goods transition from travel to arrival—representing a primary point of resistance when joining and leaving the transportation network. Traditionally, curb spaces are statically supplied, priced, and zoned for specific usage (e.g., paid parking, commercial/passenger loading, or bus stops). In response to the growing demand for curb space, some cities are starting to be more intentional about defining curb usage. Examples of curb demand include not only traditional parking and delivery needs, but today include things like curb access requirements generated by micro delivery services, active transportation modes, and transportation network companies. And now due to the pandemic, increased demand comes from food/grocery pick-up/drop-off activities, as well as outdoor business use of curb space (e.g., outdoor restaurant seating).
Heightened demand and changing expectations for finite curb resources necessitates the implementation of new and dynamic curb management capabilities so that local decision-makers have the tools needed to improve occupancy and throughput while reducing the types of traffic disruptions that result from parking search and space maneuvering activities.
However, municipalities and cities currently lack tools that allow them to simulate the effectiveness of potential dynamic curb management policies to understand how the available control variables (e.g. price or curb space supply) can be modified to influence curb usage outcomes. On the other hand, transportation authorities and fleet managers lack the needed signage or communication platforms to effectively communicate the availability of curb space for a specified use, price, and time at scales beyond centralized lots and garages.
This project aims to develop a city-scale dynamic curb use simulation tool and an open-source curb management platform. The envisioned simulation and management capabilities will include dynamically and concurrently controlling price, number of spaces, allowed parking duration, time of use or reservation, and curb space use type (e.g., dynamic curb space rezoning based on supply and demand).
Project objectives include the following:
- Objective 1: The team will develop a microscale curb simulation tool to model behavior of individual vehicles with different purposes at the curb along a blockface over time of day, accounting for price, supply, function, and maximum parking time.
- Objective 2: The team will integrate the microscale simulation tool with the LBNL’s mesoscale (city-scale) traffic simulation tool, BEAM, for simulating traffic impacts of alternative curb management strategies and their effects on citywide and regional traffic, in terms of (1) travel time, (2) throughput (people and goods) into and out of urban centers, (3) reduced energy use and emissions (from parking search and congestion), and (4) curb space utilization.
- Objective 3: The team will develop a dynamic curbspace allocation controller for various curb users, either municipal or commercial, for the purpose of a demonstration and pilot.
- Objective 4: The team will design, implement and test a curbside resource usage platform for fleet vehicles communications at commercial vehicle load zones (CVLZs), passenger load zones (PLZs), and transit stops.
- Objective 5: The team will perform demonstrations with stakeholder agencies and provide pathways to practice for promising curb allocation policies.