Unsupervised Driving Behavior Analysis using Representation Learning and
Exploiting Group-based Training
- URL: http://arxiv.org/abs/2205.07870v1
- Date: Thu, 12 May 2022 10:27:47 GMT
- Title: Unsupervised Driving Behavior Analysis using Representation Learning and
Exploiting Group-based Training
- Authors: Soma Bandyopadhyay, Anish Datta, Shruti Sachan, Arpan Pal
- Abstract summary: Driving behavior monitoring plays a crucial role in managing road safety and decreasing the risk of traffic accidents.
Current work performs a robust driving pattern analysis by capturing variations in driving patterns.
It forms consistent groups by learning compressed representation of time series.
- Score: 15.355045011160804
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Driving behavior monitoring plays a crucial role in managing road safety and
decreasing the risk of traffic accidents. Driving behavior is affected by
multiple factors like vehicle characteristics, types of roads, traffic, but,
most importantly, the pattern of driving of individuals. Current work performs
a robust driving pattern analysis by capturing variations in driving patterns.
It forms consistent groups by learning compressed representation of time series
(Auto Encoded Compact Sequence) using a multi-layer seq-2-seq autoencoder and
exploiting hierarchical clustering along with recommending the choice of best
distance measure. Consistent groups aid in identifying variations in driving
patterns of individuals captured in the dataset. These groups are generated for
both train and hidden test data. The consistent groups formed using train data,
are exploited for training multiple instances of the classifier. Obtained
choice of best distance measure is used to select the best train-test pair of
consistent groups. We have experimented on the publicly available UAH-DriveSet
dataset considering the signals captured from IMU sensors (accelerometer and
gyroscope) for classifying driving behavior. We observe proposed method,
significantly outperforms the benchmark performance.
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