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According to an Audi Urban Future Initiative study, the average person spends 106 days over their life-time searching for parking spaces. Whether it is on the side of a busy city street or a shopping center car park, the issue of parking private vehicles poses a substantial logistical challenge that scales in complexity along with population density. As modern populations trend towards urbanization it becomes imperative to develop more efficient parking structures. With the inevitable shift towards driverless vehicles, there exists a need to establish a control system to mitigate these complications. One embodiment of such a solution is a distributed sensor network feeding real-time data to a central management system which delegates navigational directives to individual vehicles based on algorithms designed to maximize spatial and temporal efficiency. This method would rely on wireless radio communication between the host and client nodes with a static sensor providing state feedback information enabling a non-causal autonomous parking process. The project strives to streamline the process of finding a vacant parking space while ensuring client safety through the direction of localized traffic by means of an optimized control scheme determined by the central server leveraging data collected from the sensor network. Such a mechanism would not only improve safety and efficiency by reducing collisions and time spent searching for open spaces, but also obviate the need for driverless vehicles to have prior knowledge of the destination layout by having the information available locally and on demand.

Publication Date



electrical and computer engineering, automobile


Electrical and Computer Engineering | Engineering

Faculty Advisor/Mentor

Yue Zhao

VCU Capstone Design Expo Posters


© The Author(s)

Date of Submission

August 2015

Non-Causal Autonomous Parking System for Driverless Vehicles [View Image]


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