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arXiv · 2304.06121

FollowMe: Vehicle Behaviour Prediction in Autonomous Vehicle Settings

Abduallah Mohamed·Jundi Liu·Linda Ng Boyle·Christian Claudel
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Abstract

An ego vehicle following a virtual lead vehicle planned route is an essential component when autonomous and non-autonomous vehicles interact. Yet, there is a question about the driver's ability to follow the planned lead vehicle route. Thus, predicting the trajectory of the ego vehicle route given a lead vehicle route is of interest. We introduce a new dataset, the FollowMe dataset, which offers a motion and behavior prediction problem by answering the latter question of the driver's ability to follow a lead vehicle. We also introduce a deep spatio-temporal graph model FollowMe-STGCNN as a baseline for the dataset. In our experiments and analysis, we show the design benefits of FollowMe-STGCNN in capturing the interactions that lie within the dataset. We contrast the performance of FollowMe-STGCNN with prior motion prediction models showing the need to have a different design mechanism to address the lead vehicle following settings.

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Abduallah Mohamed, Jundi Liu, Linda Ng Boyle, Christian Claudel. 2023-04-12. FollowMe: Vehicle Behaviour Prediction in Autonomous Vehicle Settings. https://arxiv.org/abs/2304.06121

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