Date of Award

6-16-2024

Document Type

Thesis

Publisher

Santa Clara : Santa Clara University, 2024

Department

Computer Science and Engineering

First Advisor

David Anastasiu

Abstract

Driving is one of the most tasks people do day to day to get to places more efficiently, but with many people using the road every day, distracted driving can be a big problem. Grothlaw firm states that in the recent years, at least 9 out of 3287 deaths related to auto accidents per day are caused by distracted driving [1]. Distracted driving refers to things that drivers do that are not related to driving [2] This can include texting, eating, talking to passengers, tuning the radios, etc... that can get the driver’s attention away from the road [2]. Many drivers do not realize the impact and importance of safety when they are multitasking when driving. Therefore, we will be participating in the Naturalistic Driving Action Recognition city track in the AI City Challenge, where we designed a recognition system utilizing Deep learning and computer vision that is used to identify distracted driving and to make drivers aware the impacts of distracted driving.

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