AIML for Road Accident Analysis
Road traffic accidents pose a significant threat to both developed and developing nations, prompting global efforts to enhance road safety. With cars and drivers on the roads, pedestrians also face risks, often becoming innocent victims of accidents. Various factors contribute to road accidents, including driving under the influence, weather conditions, speed, road type, light conditions, road surface, and design. These accidents can cause severe, sometimes unseen injuries with lasting health implications. This study aims to explore road accidents in India using the random forest classifier algorithm and machine learning techniques.
Authors
- Sudeep Rathore (ORCID: https://orcid.org/0000-0002-2503-8190)
- Manisha Vashisht (ORCID: https://orcid.org/0000-0002-3951-6245)
- Manoj Varshney (ORCID: https://orcid.org/0000-0001-5014-4297)
- Anupama Verma (ORCID: https://orcid.org/0000-0002-2161-2976)
- P C Sanitha
- Aaryan Saharan
Institutions
- Chandigarh University (IN)
- Lingaya's Vidyapeeth (IN)
- Mangalayatan University (IN)
- Dhanalakshmi Srinivasan Group of Institutions (IN)
- Usha Martin (India) (IN)
Publication Details
- Published
- 2024-11-22
- DOI
- https://doi.org/10.1109/aece62803.2024.10911307
- Primary Topic
- Traffic Prediction and Management Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00