18519203. METHOD AND APPARATUS OF PREDICTING POSSIBILITY OF ACCIDENT IN REAL TIME DURING VEHICLE DRIVING simplified abstract (ELECTRONICS AND TELECOMMUNICATIONS RESEARCH INSTITUTE)
Contents
- 1 METHOD AND APPARATUS OF PREDICTING POSSIBILITY OF ACCIDENT IN REAL TIME DURING VEHICLE DRIVING
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 METHOD AND APPARATUS OF PREDICTING POSSIBILITY OF ACCIDENT IN REAL TIME DURING VEHICLE DRIVING - A simplified explanation of the abstract
- 1.4 Potential Applications
- 1.5 Problems Solved
- 1.6 Benefits
- 1.7 Commercial Applications
- 1.8 Prior Art
- 1.9 Frequently Updated Research
- 1.10 Questions about Predictive Accident Prevention System
- 1.11 Original Abstract Submitted
METHOD AND APPARATUS OF PREDICTING POSSIBILITY OF ACCIDENT IN REAL TIME DURING VEHICLE DRIVING
Organization Name
ELECTRONICS AND TELECOMMUNICATIONS RESEARCH INSTITUTE
Inventor(s)
Kyung Bok Sung of Daejeon (KR)
Kyoung-Wook Min of Daejeon (KR)
Jeong Dan Choi of Daejeon (KR)
METHOD AND APPARATUS OF PREDICTING POSSIBILITY OF ACCIDENT IN REAL TIME DURING VEHICLE DRIVING - A simplified explanation of the abstract
This abstract first appeared for US patent application 18519203 titled 'METHOD AND APPARATUS OF PREDICTING POSSIBILITY OF ACCIDENT IN REAL TIME DURING VEHICLE DRIVING
The abstract describes a method for predicting the possibility of an accident involving an ego-vehicle by abstracting surrounding situation data and movement data from sensors, calculating a digitized score of the accident possibility, and generating action data to decrease the likelihood of the accident.
- Abstraction of surrounding situation data and movement data from sensors
- Calculation of a digitized score for the possibility of an accident
- Generation of action data to reduce the likelihood of the accident
Potential Applications
This technology could be applied in autonomous vehicles, driver assistance systems, and traffic management systems to enhance safety and prevent accidents.
Problems Solved
This technology addresses the challenge of predicting and preventing accidents involving ego-vehicles by analyzing driving situation data and generating appropriate actions to mitigate risks.
Benefits
The benefits of this technology include improved safety on the roads, reduced accidents, and enhanced efficiency in traffic management.
Commercial Applications
Title: Predictive Accident Prevention System This technology could be utilized by automotive manufacturers, transportation companies, and smart city initiatives to enhance road safety and optimize traffic flow.
Prior Art
Further research can be conducted in the fields of autonomous vehicles, artificial intelligence in transportation, and predictive analytics for accident prevention.
Frequently Updated Research
Ongoing research in sensor technology, machine learning algorithms, and real-time data processing could contribute to the advancement of this predictive accident prevention system.
Questions about Predictive Accident Prevention System
How does this technology contribute to the development of autonomous vehicles?
This technology plays a crucial role in enhancing the safety and reliability of autonomous vehicles by predicting and preventing accidents.
What are the potential implications of this technology on insurance policies for vehicles?
The implementation of this technology could lead to changes in insurance policies, with a focus on rewarding safe driving behavior and accident prevention.
Original Abstract Submitted
A method of predicting a possibility of an accident is provided. The method includes abstracting surrounding situation data and movement data of an ego-vehicle input from a sensor to generate abstracted driving situation data by using an abstraction module executed by a processor, calculating a digitized score of a possibility of an accident of the ego-vehicle by using a calculation module executed by the processor, based on the abstracted driving situation data, and generating action data of the ego-vehicle for decreasing the possibility of the accident by using an action generating module executed by the processor, based on the score.
