Developing an AI-based system that predicts incidents


Researchers have developed a new early warning system for autonomous vehicles using artificial intelligence that is able to learn from thousands of real traffic scenarios.


According to a new study carried out with the BMW Group and published in IEEE magazine for intelligent transportation systems, you can soon ride a self-driving car by pressing the drive button using artificial intelligence to survive fatal accidents; Because you will be warned 7 seconds before the accident, which is long enough to make quick decisions that can save thousands of lives.


According to the study, which was reviewed by the interesting engineering site, artificial intelligence can make these predictions with more than 85% accuracy, as the artificial intelligence early warning system predicts critical scenarios.


The research team collaborated with Professor Eckhard Steinbach, Head of Media Technology and Board Member of the Munich School of Robotics and Machine Intelligence (MSRM), and tried a new approach to solve the problem of unexpected traffic behavior.


They took into account scenarios controlled by a human driver; Because the driver dislikes self-driving for safety reasons.


The new system uses cameras and sensors to capture surrounding conditions, and record vehicle condition data including road conditions, visibility, wheel angle, weather and speed.


The AI ​​system, which uses a Recurrent Neural Network (RNN), adapts to identify patterns in the data. When unique scenarios arise that the control system cannot handle on its own, the driver will be alerted in advance to any potentially dangerous situation.


To make vehicles more independent, many of the methods currently used study what cars understand about traffic, and then try to improve the models used in them, a report by TechXplore said.


But the big advantage of our technology is that we completely ignore what the car thinks," he added. Instead, we limit ourselves to data based on what is actually happening, and look for patterns. In this way, artificial intelligence detects critical situations, which the vehicle may not be able to recognize, or have not yet detected.


According to Steinbach, the system they developed provides a safety function that knows when and where the vehicle's vulnerabilities are.


Artificial intelligence data stored centrally can enable entire fleets of self-driving cars to adapt, and the research team and BMW Group have tested the new AI technology with the latest autonomous driving vehicles on public roads, and tested nearly 2,500 scenarios, in which the driver had to Manually control it after being alerted.


According to the study, artificial intelligence was already able to predict potentially critical scenarios with more than 85% accuracy, and even 7 seconds before the accident.


Every time a potential awkward situation arises on a test drive, we make it a good example of a new coaching, said Christopher Kuhn, one of the study's authors. This means that large amounts of new data are needed. Because AI can only recognize and predict scenarios it has encountered before.


Once enough data is gathered, new data is practically generated on its own. Centralized data storage enables the aggregation of all these scenarios, and with each scenario of imminent death in transit being stored the entire fleet learns how to avoid this situation in the future.

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