Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
Due to the exponential increase in traffic nowadays, the incidence of accidents also increases proportionally. With the rapid increase in accidents, the ability to predict and predict the best path to an accident is very important not only for the transport department to make scientific decisions, but also for individuals to know less paths to accidents to travel the safest way. According to the current scenarios, it would be good to analyze the correct path with less accidents. In this, we studied the interrelationship between accidents, road conditions, weather conditions and predicted a safe and less frequent accident occurrence path among all the paths that can be taken from the source to the destination. We built using machine learning algorithms like Support Vector Machines and Logistic Regression. The main topic is to design the safest route of all the routes based on the accident rate. Conditions such as weather conditions, road conditions, lighting conditions, vehicle type, etc. By inputting these conditions into a machine learning model for a specific location, one can predict the frequency of accidents that will occur at a specific location, whether the location is safe. Based on the safety of individual locations, user can concludes the safety of the path.
Keywords:
Support Vector Machines, Logistic Regression, Machine Learning Model,Location
Cite Article:
"Safe Path Prediction Using Machine Learning", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.8, Issue 3, page no.649 - 651, March-2023, Available :http://www.ijrti.org/papers/IJRTI2303114.pdf
Downloads:
000205092
ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator