Abstract

Over the past decade more people are opting in to purchase and own their own personal vehicle and in some instances several, which means that road accidents rates are doomed to increase. And this presents a challenge to the government, individuals and the collective community as car accidents are in most cases life threatening and a hazard to society. Thus, this paper aims to tackle this issue and dig deep to explore the main factors contributing to the increase of car accidents rate. The dataset used in this research is data collected from traffic accidents events captured by the department of transportation, law-enforcement agencies, and traffic cameras continuously in the United States from 2016 to 2020. Two models were performed to predict the impact of car accidents on road traffic, with a focus on the leading factors contributing to road accidents. Results showed that the main two factors affecting car accidents rate are traffic caused by work rush hour and population density. Furthermore, this research can be used to create solutions to limit and decrease car accidents in cities, such as adopting the working from home concept, facilitating the ownership of self-driving vehicles, creating a seamless public transportation infrastructure, and distributing rush hours throughout the day to name a few.

Publication Date

12-19-2021

Document Type

Master's Project

Student Type

Graduate

Degree Name

Professional Studies (MS)

Department, Program, or Center

Graduate Programs & Research (Dubai)

Advisor

Sanjay Modak

Advisor/Committee Member

Ehsan Warriach

Campus

RIT Dubai

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