Road Traffic Accident Prediction Model is artificial intelligence model that can evaluate which factors can be most effectively “controlled” in order to reduce the occurrence of accidents in problematic areas.
Main functionalities/Main features
The model can use various data like traffic offenses, traffic accidents, weather conditions, location and times of police vehicles, traffic count data, road register data etc. On the basis of these data, the forecasting model is able to predict the risk, severity, and root cause of traffic accidents.
- The model is able to predict the probability of accidents, their severity, and the risk factors influencing the occurrence of accidents. This information can be used to develop a safer transport system, plan more sustainable mobility and shape the attitudes and behavior of road users.
- The Police and the Border Guard Board could use this to direct additional forces to areas with a higher probability of traffic accidents. Through this they can ensure public order and calm traffic, and to prevent the occurrence of traffic accidents with their presence.
- Also, due to the forecasting of traffic accidents, other agencies operating in emergencies will have the opportunity to plan work more efficiently and proactively and to intervene in their prevention before accidents occur.
- Road administration authorities
- Traffic accidents prevention
- Knowledge-based planning of road safety prevention activities
- Helps plan safer transport system
- More sustainable mobility
- Patrol planning for law enforcement
References / case study
- The Estonian Road Administration