Towards Incorporating Contextual Knowledge into the Prediction of Driving Behavior

Wirthmueller, Florian and Schlechtriemen, Julian and Hipp, Jochen and Reichert, Manfred (2020) Towards Incorporating Contextual Knowledge into the Prediction of Driving Behavior. In: 23rd IEEE International Conference on Intelligent Transportation Systems (ITSC 2020), 20-23 September 2020, Rhodes, Greece.

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Official URL: https://doi.org/10.1109/ITSC45102.2020.9294665


Predicting the behavior of surrounding traffic participants is crucial for advanced driver assistance systems and autonomous driving. Most researchers however do not consider contextual knowledge when predicting vehicle motion. Extending former studies, we investigate how predictions are affected by external conditions. To do so, we categorize different kinds of contextual information and provide a carefully chosen definition as well as examples for external conditions. More precisely, we investigate how a state-of-the-art approach for lateral motion prediction is influenced by one selected external condition, namely the traffic density. Our investigations demonstrate that this kind of information is highly relevant in order to improve the performance of prediction algorithms. Therefore, this study constitutes the first step towards the integration of such information into automated vehicles. Moreover, our motion prediction approach is evaluated based on the public highD data set showing a maneuver prediction performance with areas under the ROC curve above 97 % and a median lateral prediction error of only 0.18 m on a prediction horizon of 5 s.

Item Type:Conference or Workshop Item (Paper)
Subjects:DBIS Research > Publications
ID Code:2010
Deposited By: Prof. Dr. Manfred Reichert
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Deposited On:18 May 2021 10:07
Last Modified:18 May 2021 11:45

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