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Dynamic and Systematic Survey of Deep Learning Approaches for Driving Behavior Analysis
[article]
2021
arXiv
pre-print
Improper driving results in fatalities, damages, increased energy consumptions, and depreciation of the vehicles. Analyzing driving behaviour could lead to optimize and avoid mentioned issues. By identifying the type of driving and mapping them to the consequences of that type of driving, we can get a model to prevent them. In this regard, we try to create a dynamic survey paper to review and present driving behaviour survey data for future researchers in our research. By analyzing 58 articles,
arXiv:2109.08996v1
fatcat:r2faox3pdrfedb72ewkecpp64a