Research Projects

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Research Projects

STATUS: Complete YEAR: 2019 TOPIC AREA: Connected and autonomous systems Vehicles and infrastructure CENTER: PSR

Software and Hardware Systems for Autonomous Smart Parking Accommodating both Traditional and Autonomous Vehicles

Project Summary

Project number: PSR-19-30
Funding source: Caltrans
Contract number: 65A0674, TO-027
Funding amount: $65,000
Performance period: 1/1/2020 to 4/1/2021

Project description

Parking infrastructure is suffering from congestion as the number of vehicles circulating in urban areas is growing and expansion is not a cost-effective solution. In parallel, developments in autonomous vehicle technology mean that driverless vehicles are predicted to be in circulation by the 2020s and makeup 40% of vehicle travel by the 2040s. Expected benefits of autonomous vehicle travel include reduced congestion through vehicle sharing and reduced walking distance for passengers who can be dropped off chauffeur-style by autonomous vehicles. However, empty vehicle cruising, or the case in which autonomous vehicles cannot efficiently locate parking and circle instead, can potentially increase congestion. Given that this new technology has the potential to exacerbate existing congestion issues, it is necessary to develop a solution for parking congestion integrated with autonomous vehicles. Our project addresses this issue by providing a full-stack solution including sensors to monitor occupancy, Fog systems to perform local data pre- processing, and SDR radios to communicate with autonomous vehicles.


Current infrastructure supports parking guidance information and a parking reservation system for traditional vehicles with smartphone-equipped users. DSRC has also been successfully employed in V2V and V2I communications. As such, the research challenge is integrating autonomous vehicles into existing smart parking platform options. This entails not only securing DSRC connections between smart parking systems and autonomous vehicles, but also ensuring that the system provides sufficient information for successful parking services in real time. The challenge of integration is addressed by developing a full stack system that will accomplish the following: monitor a parking garage's occupancy, classify vehicles within the parking garage, aggregate location data for available spaces and associated mapping data, and assign them to the respective vehicles to be routed to it.


Mohammad Al Faruque
Associate Professor of Electrical Engineering & Computer Science
The Henry Samueli School of Engineering
3223 Engineering HallIrvine, CA 92697-2625
United States
[email protected]