Research shows that urban intersections are a hotspot for traffic accidents which cause major human injuries. Predicting turning, passing, and stop maneuvers against surrounding vehicles is considered to be fundamental for advanced driver assistance systems (ADAS), or automated driving systems in urban intersections. In order to estimate the target intent in such situations, an interacting multiple model (IMM)-based intersection-target-intent estimation algorithm is proposed. A driver model is developed to represent the driver’s maneuvering on the intersection using an IMM-based target intent classification algorithm. The performance of the intersection-target-intent estimation algorithm is examined through simulation studies. It is demonstrated that the intention of a target vehicle is successfully predicted based on observations at an individual intersection by proposed algorithms.

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The different versions of the original document can be found in:

https://doaj.org/toc/2076-3417 under the license cc-by
https://academic.microsoft.com/#/detail/3013781994 under the license https://creativecommons.org/licenses/by/4.0/
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Published on 01/01/2020

Volume 2020, 2020
DOI: 10.3390/app10062138
Licence: Other

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