Using Machine Learning Algorithms to Improve Road Safety
| dc.contributor.author | Kotikalapudi, Lakshmi Praneetha | |
| dc.contributor.author | Chao, Yen Ling | |
| dc.contributor.author | Reddy, Sri Siddhartha | |
| dc.date.accessioned | 2022-06-08T16:18:57Z | |
| dc.date.available | 2022-06-08T16:18:57Z | |
| dc.date.issued | 2022-06-08 | |
| dc.description.abstract | Transportation facilities are becoming more developed as society develops, and people's travel demand is increasing, but so are the traffic safety issues that arise as a result. And car accidents are a major issue all over the world. The cost of traffic fatalities and driver injuries has a significant impact on society. The use of machine learning techniques in the field of traffic accidents is becoming increasingly popular. Machine learning classifiers are used instead of traditional data mining techniques to produce better results and accuracy. As a result, this project conducts research on existing work related to accident prediction using machine learning. We will use crash data and weather data to train machine learning models to predict crash severity and reduce crashes. | |
| dc.identifier.uri | https://hdl.handle.net/1920/12895 | |
| dc.rights | Attribution-NonCommercial-NoDerivs 3.0 United States | |
| dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/3.0/us/ | |
| dc.subject | Machine learning | |
| dc.subject | Road Safety | |
| dc.title | Using Machine Learning Algorithms to Improve Road Safety | |
| dc.type | Working Paper |