Christopher Flores | Searcharxiv

arXiv2017

Parking Sensing and Information System: Sensors, Deployment, and Evaluation

This paper describes a smart parking sensing and information system that disseminates the parking availability information for public users in a cost-effective and efficient manner. The hardware framework of the system is built on advanced wireless sensor networks and cloud service over the Internet, and the system is highly scalable. The parking information provided to the users is set in the form of occupancy rates and expected cruising time. Both are obtained from our analytical algorithm processing both historical and real-time data, and are thereafter visualized in a color theme. The entire parking system is deployed and extensively evaluated at Stanford University Parking Structure-1.

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arXiv2016

Traffic Predictive Control from Low-Rank Structure

The operation of most signalized intersections is governed by predefined timing plans that are applied during specified times of the day. These plans are designed to accommodate average conditions and are unable to respond to large deviations in traffic flow. We propose a control approach that adjusts time-of-day signaling plans based on a prediction of future traffic flow. The prediction algorithm identifies correlated, low rank structure in historical measurement data and predicts future traffic flow from real-time measurements by determining which structural trends are prominent in the measurements. From this prediction, the controller then determines the optimal time of day to apply new timing plans. We demonstrate the potential benefits of this approach using eight months of high resolution data collected at an intersection in Beaufort, South Carolina.

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