Research Projects
Searching for:
- "Curb allocation"
Demand for curb space is increasing with the rise of TNCs, micro-delivery services, electric vehicle infrastructure, micromobility, and complete streets. Municipalities are addressing these challenges with new curb allocation policies that improve flow and reduce traffic disruption.
Start Date: May 2024
Funding: U.S. Department of Transportation SMART grant
Project Budget: $100,000
Principal Investigator(s): Dr. Anne Goodchild
Summary:
The Open Mobility Foundation’s SMART Curb Collaborative is a group of cities united in tackling challenges in curb management, reducing congestion, enhancing livability, and improving safety and equity on city streets. Each of these public agencies is a recipient of USDOT’s Strengthening Mobility and Revolutionizing Transportation (SMART) grant program, which provides funding to build data and technology capacity across the US. In close coordination with the Open Mobility Foundation (OMF) Collaborative Program Manager, the UFL will support the nine cities...
The Open Mobility Foundation’s SMART Curb Collaborative is a group of cities united in tackling challenges in curb management, reducing congestion, enhancing livability, and improving safety and equity on city streets. Each of these public agencies is a recipient of USDOT’s Strengthening Mobility and Revolutionizing Transportation (SMART) grant program, which provides funding to build data and technology capacity across the US. In close coordination with the Open Mobility Foundation (OMF) Collaborative Program Manager, the UFL will support the nine cities...
Start Date: January 2021
Funding: PacTrans (Region 10 University Transportation Center)
Project Budget: $180,000
Other PI(s): David Hurwitz (Oregon State University)
Summary:
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, such as changing road characteristics (land use, number of travel lanes, nearby signals, traffic in adjacent lanes), curb allocations (paid parking, commercial vehicle loading zones, passenger load zones), and other road users (passenger cars, ridehailing vehicles, bikes). In addition to monitoring behavior and decision-making, 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. This study is intended to fill knowledge gaps and serve as a valuable resource for policy makers, transportation engineers, and urban planners.
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, such as changing road characteristics (land use, number of travel lanes, nearby signals, traffic in adjacent lanes), curb allocations (paid parking, commercial vehicle loading zones, passenger load zones), and other road users (passenger cars, ridehailing vehicles, bikes). In addition to monitoring behavior and decision-making, 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. This study is intended to fill knowledge gaps and serve as a valuable resource for policy makers, transportation engineers, and urban planners.
Start Date: January 2020
Funding: U.S. Department of Energy, Vehicle Technologies Office (VTO)
Project Budget: $500,000
Summary:
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). Researchers 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, and perform demonstrations with stakeholder agencies and provide pathways to practice for promising curb allocation policies.
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). Researchers 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, and perform demonstrations with stakeholder agencies and provide pathways to practice for promising curb allocation policies.