Presenter(s)

Kunal Agrawal

Comments

Presentation: 9:40-10:00 a.m., Jessie Hathcock Hall 180

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Description

Motorcycles are one of the most popular modes of transportation, particularly in developing countries such as India, and Vietnam. Due to lesser protection compared to cars and other standard vehicles, motorcycle riders are exposed to a greater risk of crashes. Therefore, wearing helmets for motorcycle riders is mandatory as per traffic rules and automatic detection of motorcyclists without helmets is one of the critical tasks to enforce strict regulatory traffic safety measures. Due to the increase in the number of vehicles on roads, the number of injuries or accidents has also increased. According to a study, approximately 21.5% of motorcycle riders had been wearing helmets at the time of the accident. This has also made a huge impact on city development planning. Due to not wearing a helmet, there’s an exponential increase in the fatality rate during an accident. It has been observed that these fatality rates are higher during the daytime and the dark. To decrease the risk of fatal injuries, we are developing a model that will detect whether a motorcyclist wears a helmet or not. We will be using the traffic data from Vietnam from daytime and nighttime. The trained model using this data will be used further for the city planning simulator.

Publication Date

4-19-2023

Project Designation

Graduate Research

Primary Advisor

Van Nguyen

Primary Advisor's Department

Computer Science

Keywords

Stander Symposium, College of Arts and Sciences

Institutional Learning Goals

Community; Diversity; Scholarship

Detecting Violation of Helmet Rule for Motorcyclists

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