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A review on machine learning-based models for lane-changing behavior prediction and recognition

Overview of attention for article published in Frontiers in Future Transportation, January 2023
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1 X user

Citations

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5 Dimensions

Readers on

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13 Mendeley
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Title
A review on machine learning-based models for lane-changing behavior prediction and recognition
Published in
Frontiers in Future Transportation, January 2023
DOI 10.3389/ffutr.2023.950429
Authors

Ruth David, Dirk Söffker

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 13 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 13 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 38%
Researcher 1 8%
Student > Doctoral Student 1 8%
Unknown 6 46%
Readers by discipline Count As %
Engineering 5 38%
Unspecified 2 15%
Unknown 6 46%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 24 January 2023.
All research outputs
#21,509,573
of 26,388,722 outputs
Outputs from Frontiers in Future Transportation
#70
of 108 outputs
Outputs of similar age
#366,152
of 491,307 outputs
Outputs of similar age from Frontiers in Future Transportation
#5
of 8 outputs
Altmetric has tracked 26,388,722 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 108 research outputs from this source. They receive a mean Attention Score of 1.6. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 491,307 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 13th percentile – i.e., 13% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 8 others from the same source and published within six weeks on either side of this one. This one has scored higher than 3 of them.