Abstract
Demand for parking is increasing from a growing number of diverse stakeholders, however the supply of curbspace is limited. A Smart Curbspace system is envisioned to improve parking by rigorously optimizing vehicle arrivals based on environmental, economic, and social objectives. This project expands our previous research of Smart Curbspace parking optimization for delivery vehicle to address the broader concerns of the community of curbspace customers.
Description
Competition for urban curbspace is increasing due to limited parking space shared among passenger vehicles, transportation network companies, delivery services, bikes and scooters, and even outdoor dining for restaurants. As part of a Department of Energy research grant, we recently explored how a Smart Curbspace system, an optimized reservation system similar to Airbnb for commercial vehicle parking, can impact the surrounding environment and improve parking. Present day uncoordinated competition for commercial parking spaces can result in a lack of available parking and subsequent double parking in traffic lanes. Double parked delivery vehicles can increase traffic congestion and associated passenger vehicle delay, increase energy use and emissions, and decrease in safety for nearby pedestrians. Our initial research findings show that a Smart Curbspace system can substantially reduce the total time that delivery vehicles double-park by optimally scheduling vehicle arrival times.
Our University Transportation Center (UTC) proposal aims to leverage this prior work to develop new Smart City Technologies that benefits all stakeholders. Specifically, we hope to incorporate new delivery vehicle behaviors, including “cruising” in search of parking when spaces are not available, and delivery vehicle routing to optimally coordinate a set of deliveries with timing of parking availability. We also intend to incorporate other users of Smart Curbspace systems, such as Uber, Lyft and passenger vehicles, combining advanced parking reservations with on-demand reservations. Furthermore, we aim to assess impacts of Smart Curbspace including congestion externalities, energy use, private costs, and equity of curbspace use for all users of the system. We intend to garner user perspectives through partnerships with the City of Pittsburgh Department of Mobility and Infrastructure (DOMI) and Office of Equity.
The proposed project will leverage a Python/Gurobi Mixed Integer Linear Program (MILP) optimization framework that we developed in prior work. Our methodology currently uses delivery vehicle parking input data from smart loading zones in Aspen, CO and may include data from downtown Pittsburgh in the future. Outputs from our algorithm inform time periods of double-parked delivery vehicles, which are used as inputs into a traffic flow queuing model. When delivery vehicle parking is not optimally coordinated, double parking results in vehicle delays for the surrounding traffic, causing congestion delays and additional energy consumption and emissions.
Finally, we aim for our research to better inform city decision-makers on reservation-based parking systems and when and how to implement a Smart Curbspace system. We will identify conditions under which Smart Curbspace is a more cost-effective solution than building additional parking infrastructure or revamping roadway infrastructure. To support Smart Curbspace implementation, after submitting our research for peer review, we plan to engage with the Swartz Center for Entrepreneurship to identify potential deployment partners. With several companies, Coord and Automotus, already exploring smart loading zones, full scale Smart Curbspace systems may be fast approaching. As a result, our proposed research intends to provide a community leading assessment of Smart Curbspace and shape the technology to best fulfill diverse stakeholder needs.
Timeline
July – August 2022: Deep dive into literature review and discussions with City of Pittsburgh Department of Mobility and Infrastructure (DOMI)
September – December 2022: Data collection, optimization model development and refinement
January – March 2023: Collect final study results from optimization model
April – June 2023: Submit research paper, write policy brief, and engage policymakers
Strategic Description / RD&T
Deployment Plan
We plan to interact with and share our findings with the City of Pittsburgh Office of Equity and Department of Mobility and Infrastructure (DOMI) to inform and support planning and future strategy. We also plan to engage the Swartz Center for Entrepreneurship to identify potential for deploying the technology.
Expected Outcomes/Impacts
- Identification of metrics of interest from the City of Pittsburgh Office of Equity, Department of Mobility and Infrastructure and literature review
- Completion and verification of optimization algorithm
- Published peer review paper with accompanying dataset necessary for study replication
- Identification of potential deployment partners from the Swartz Center for Entrepreneurship
Expected Outputs
TRID
Individuals Involved
| Email |
Name |
Affiliation |
Role |
Position |
| aaronbur@andrew.cmu.edu |
Burns, Aaron |
Carnegie Mellon University |
Other |
Student - PhD |
| aharder@andrew.cmu.edu |
Harder, Annie |
CMU |
Other |
Staff - Business Manager |
| jmichalek@cmu.edu |
Michalek, Jeremy |
Carnegie Mellon University |
PI |
Faculty - Tenured |
Budget
Amount of UTC Funds Awarded
$100000.00
Total Project Budget (from all funding sources)
$200000.00
Documents
| Type |
Name |
Uploaded |
| Data Management Plan |
Data_Management_Plan_IlLAbcv.docx |
Nov. 18, 2021, 7:14 p.m. |
| Project Brief |
Smart_Curbspace.pptx |
March 2, 2022, 10:39 a.m. |
| Progress Report |
397_Progress_Report_2022-09-30 |
Sept. 30, 2022, 8:03 a.m. |
| Presentation |
Smart Curbspace: Estimating the potential for optimized delivery vehicle parking assignment to reduce double parking, congestion and energy consumption |
March 29, 2023, 6:42 a.m. |
| Progress Report |
397_Progress_Report_2023-03-30 |
March 29, 2023, 9:27 a.m. |
| Publication |
Generalized Costs of Travel by Solo and Pooled Ridesourcing vs. Privately Owned Vehicles, and Policy Implications |
March 30, 2023, 5:25 a.m. |
| Publication |
Sharing Mobility Data for Planning and Policy Research |
March 30, 2023, 5:26 a.m. |
| Publication |
Are We There Yet?: The Myths and Realities of Autonomous Vehicles |
March 30, 2023, 5:27 a.m. |
| Publication |
Carbon Neutrality Study 1: Driving California’s Transportation Emissions to Zero |
March 30, 2023, 5:28 a.m. |
| Publication |
Travel time costs in the near-(circa 2020) and long-term (2030–2035) for automated, electrified, and shared mobility in the United States |
March 30, 2023, 5:29 a.m. |
| Publication |
Smart Charging of Electric Vehicles Will Reduce Emissions and Costs in a 100% Renewable Energy Future in California |
March 30, 2023, 5:29 a.m. |
| Final Report |
Final_Report_-_397.pdf |
Sept. 15, 2023, 9:40 a.m. |
Match Sources
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Partners
| Name |
Type |
| City of Pittsburgh Department of Mobility and Infrastructure |
Deployment Partner Deployment Partner |
| Street Sense, Inc. |
Deployment Partner Deployment Partner |
