Morgan State University

Samira Ahangari

Mansoureh Jeihani

Zohreh Rashidi Moghaddam

Arsalan Hassan Pour

Abdollah Dehzangi

Systems and methods are disclosed for detecting both the occurrence and type of driver distraction experienced by a driver, determined through evaluation of sensed vehicle conditions or activities, such as steering, braking, lane changing, etc. as detected by one or more sensors on or associated with the vehicle. That detection of the occurrence and type of driver distraction may then be used to initiate another action, including initiating an audible or visual alert to the driver, taking measures to interfere with or stop operation of the device that is causing the distraction, log the occurrence and type of distraction that occurred, and report the occurrence and type of distraction to an outside monitoring computer (such as one associated with a guardian of the driver, an insurer of the vehicle, a law enforcement authority, or the like). To allow such detection, the system and method set forth herein employ machine learning methods to first train a classifier to classify certain driver behaviors (as evidenced by sensed vehicle movements and conditions) as a distraction or non-distraction event, and if a distraction event is detected then to further classify a type of such distraction event, and then to apply the trained classifier to classify the driver's ongoing driving activity.

System and method for driver distraction detection and classification

Disclosed is a system and method for generating a vehicle speed alert in a driving simulation system that communicates with a remote driving simulator engine and a remote speed optimization engine. The remote speed optimization engine receives data from the vehicle speed alert system after the vehicle speed alert system has received data from the remote driving simulator engine, including the vehicle's simulated distance to a signalized intersection, the time remaining for the simulated traffic light to change, and the current simulated light status (green, yellow, red) of the traffic light. The vehicle speed alert system then receives from the remote speed optimization engine a recommended speed profile for that given instant, and if the driver's current speed does not fall within some maximum difference with the current recommended speed profile, calculates and transmits an alert to an output device to alert the driver of action necessary to achieve the recommended speed profile.

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Baltimore, MD, United States of America

Samira Ahangari