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Lehrstuhl fr Fahrzeugtechnik Fakultt fr Maschinenwesen Technische Universitt MnchenSemesterarbeit/MasterarbeitInteractionaware prediction: Modelling human behavior through synthetic vision in a 2dimensional
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Collect historical vehicle data including speed, acceleration, braking patterns, and location.
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Use machine learning algorithms to analyze the data and identify patterns in vehicle behavior.
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Implement the predictive model in a software system that can be used in real-time to predict vehicle behavior.

Who needs predicting vehicle behavior using?

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Vehicle manufacturers looking to improve safety features in their vehicles.
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City planners interested in optimizing traffic flow and reducing accidents.
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Predicting vehicle behavior is typically done using data analytics, machine learning algorithms, and sensor data to forecast how vehicles will behave under various conditions.
Manufacturers and developers of autonomous vehicles and related technologies are generally required to file information on predicting vehicle behavior.
To fill out predicting vehicle behavior documentation, follow the guidelines provided by the regulatory authority, ensuring all relevant data and analysis methods are clearly documented.
The purpose is to ensure safety, enhance the reliability of autonomous systems, and comply with regulatory standards.
Reports must include modeling approaches, data sources, validation results, and any assumptions made during the predictions.
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