Analyzing Factors Affecting Road Crash Severity Using Quantum Machine Learning Approach

This research proposal aims to utilize Quantum Machine Learning (QML) techniques to investigate the relationship between independent variables and crash severity. The study focuses on analyzing the impact of various factors such as year, day, school zone, intersection type, road characteristics, weather conditions, and more on crash severity using QML models. The integration of QML in this research is motivated by its potential to process and analyze complex datasets at a quantum level, offering a quantum advantage in solving problems that would be computationally infeasible for classical machine learning algorithms. By harnessing the power of quantum computing, this research seeks to achieve unprecedented insights into road crash severity determinants.