Scipediacontent: Scipediacontent moved page Draft Content 441314414 to 238,295ka

2021-03-22T22:37:00Z

Scipediacontent moved page Draft Content 441314414 to 238,295ka

Scipediacontent: Created page with " == Abstract == An accurate prediction of future trajectories of surrounding vehicles can ensure safe and reasonable interaction between intelligent vehicles and other types..."

2021-03-22T22:35:46Z

Created page with " == Abstract == An accurate prediction of future trajectories of surrounding vehicles can ensure safe and reasonable interaction between intelligent vehicles and other types..."

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== Abstract ==

An accurate prediction of future trajectories of surrounding vehicles can ensure safe and reasonable interaction between intelligent vehicles and other types of vehicles. Vehicle trajectories are not only constrained by a priori knowledge about road structure, traffic signs, and traffic rules but also affected by posterior knowledge about different driving styles of drivers. The existing prediction models cannot fully combine the prior and posterior knowledge in the driving scene and perform well only in a specific traffic scenario. This paper presents a long short-term memory (LSTM) neural network driven by knowledge. First, a driving knowledge base is constructed to describe the prior knowledge about a driving scenario. Then, the prediction reference baseline (PRB) based on driving knowledge base is determined by using the rule-based online reasoning system. Finally, the future trajectory of the target vehicle is predicted by an LSTM neural network based on the prediction reference baseline, while the predicted trajectory considers both posterior and prior knowledge without increasing the computation complexity. The experimental results show that the proposed trajectory prediction model can adapt to different driving scenarios and predict trajectories with high accuracy due to the unique combination of the prior and posterior knowledge in the driving scene.

Document type: Article

== Full document ==
<pdf>Media:Draft_Content_441314414-beopen1286-4364-document.pdf</pdf>

== Original document ==

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

* [http://dx.doi.org/10.1155/2020/8894060 http://dx.doi.org/10.1155/2020/8894060] under the license https://creativecommons.org/licenses/by/4.0/

* [http://downloads.hindawi.com/journals/jat/2020/8894060.pdf http://downloads.hindawi.com/journals/jat/2020/8894060.pdf],
: [http://downloads.hindawi.com/journals/jat/2020/8894060.xml http://downloads.hindawi.com/journals/jat/2020/8894060.xml],
: [http://dx.doi.org/10.1155/2020/8894060 http://dx.doi.org/10.1155/2020/8894060]

* [http://dx.doi.org/10.1155/2020/8894060 http://dx.doi.org/10.1155/2020/8894060],
: [https://doaj.org/toc/0197-6729 https://doaj.org/toc/0197-6729],
: [https://doaj.org/toc/2042-3195 https://doaj.org/toc/2042-3195] under the license https://creativecommons.org/licenses/by/4.0/

* [https://www.hindawi.com/journals/jat/2020/8894060 https://www.hindawi.com/journals/jat/2020/8894060],
: [https://academic.microsoft.com/#/detail/3096272849 https://academic.microsoft.com/#/detail/3096272849]

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Scipediacontent: Scipediacontent moved page Draft Content 441314414 to 238,295ka

Scipediacontent: Created page with " == Abstract == An accurate prediction of future trajectories of surrounding vehicles can ensure safe and reasonable interaction between intelligent vehicles and other types..."