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Open AccessArticle

Predicting Agent Behaviour and State for Applications in a Roundabout-Scenario Autonomous Driving

School of Information Technology, Halmstad University, Box 823, 30118 Halmstad, Sweden
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Sensors 2019, 19(19), 4279; https://doi.org/10.3390/s19194279
Received: 21 August 2019 / Revised: 29 September 2019 / Accepted: 30 September 2019 / Published: 2 October 2019
(This article belongs to the Special Issue Perception Sensors for Road Applications)
As human drivers, we instinctively employ our understanding of other road users’ behaviour for enhanced efficiency of our drive and safety of the traffic. In recent years, different aspects of assisted and autonomous driving have gotten a lot of attention from the research and industrial community, including the aspects of behaviour modelling and prediction of future state. In this paper, we address the problem of modelling and predicting agent behaviour and state in a roundabout traffic scenario. We present three ways of modelling traffic in a roundabout based on: (i) the roundabout geometry; (ii) mean path taken by vehicles inside the roundabout; and (iii) a set of reference trajectories traversed by vehicles inside the roundabout. The roundabout models are compared in terms of exit-direction classification and state (i.e., position inside the roundabout) prediction of query vehicles inside the roundabout. The exit-direction classification and state prediction are based on a particle-filter classifier algorithm. The results show that the roundabout model based on set of reference trajectories is better suited for both the exit-direction and state prediction. View Full-Text
Keywords: behaviour modelling; roundabout behaviour modelling; roundabout
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Muhammad, N.; Åstrand, B. Predicting Agent Behaviour and State for Applications in a Roundabout-Scenario Autonomous Driving. Sensors 2019, 19, 4279.

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