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Open AccessArticle

Intention Estimation Using Set of Reference Trajectories as Behaviour Model

School of Information Technology, Halmstad University, 30118 Halmstad, Sweden
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Sensors 2018, 18(12), 4423; https://doi.org/10.3390/s18124423
Received: 15 November 2018 / Revised: 11 December 2018 / Accepted: 12 December 2018 / Published: 14 December 2018
(This article belongs to the Special Issue Sensors Applications in Intelligent Vehicle)
Autonomous robotic systems operating in the vicinity of other agents, such as humans, manually driven vehicles and other robots, can model the behaviour and estimate intentions of the other agents to enhance efficiency of their operation, while preserving safety. We propose a data-driven approach to model the behaviour of other agents, which is based on a set of trajectories navigated by other agents. Then, to evaluate the proposed behaviour modelling approach, we propose and compare two methods for agent intention estimation based on: (i) particle filtering; and (ii) decision trees. The proposed methods were validated using three datasets that consist of real-world bicycle and car trajectories in two different scenarios, at a roundabout and at a t-junction with a pedestrian crossing. The results validate the utility of the data-driven behaviour model, and show that decision-tree based intention estimation works better on a binary-class problem, whereas the particle-filter based technique performs better on a multi-class problem, such as the roundabout, where the method yielded an average gain of 14.88 m for correct intention estimation locations compared to the decision-tree based method. View Full-Text
Keywords: behaviour modelling; intention estimation behaviour modelling; intention estimation
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Muhammad, N.; Åstrand, B. Intention Estimation Using Set of Reference Trajectories as Behaviour Model. Sensors 2018, 18, 4423.

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