Intelligent vehicles need increasing knowledge about both their own state and the driving environment. In this work a novel method for interpreting this information by a reliable detection of relevant driving situations and driving maneuvers is proposed. The information of a situation or maneuver is extracted and hence provided for subsequent processing in the applications. As a result of different situation perception and maneuver realization of the drivers, the selected method is based on probabilistic decisions. Furthermore the inaccuracy of this decision is estimated by the inaccuracies of the sensor measurements. This value can be seen as quality measure of the probabilistic situation and maneuver detection. In addition the model allows to derivate requirements on the sensors, while determining a relevance ranking of the separate sensor information regarding the situation decision.
Probabilistic approach for modeling and identifying driving situations
2008 IEEE Intelligent Vehicles Symposium ; 343-348
2008-06-01
747686 byte
Conference paper
Electronic Resource
English
Probabilistic Approach for Modeling and Identifying Driving Situations
British Library Conference Proceedings | 2008
|Driving Behavior in Emergency Situations: Psychospacing Modeling Approach
Online Contents | 2012
|Systems and methods for identifying high-risk driving situations from driving data
European Patent Office | 2024
|SYSTEMS AND METHODS FOR IDENTIFYING HIGH-RISK DRIVING SITUATIONS FROM DRIVING DATA
European Patent Office | 2022
|Modeling Driver Adaptation Capabilities in Critical Driving Situations
SAE Technical Papers | 2012
|