Abstract: The present disclosure relates to a method and an apparatus for controlling an electronic control suspension using a deep learning-based road surface classification model. The method for controlling an electronic control suspension in a vehicle including a camera and a GPS receiver may include collecting location information of the vehicle using the GPS receiver while driving, identifying whether there is a previously generated road surface classification model corresponding to a front obstacle when the front obstacle is detected, determining a first control value based on a first characteristic value corresponding to the road surface classification model when there is the road surface classification model as a result of the identification, controlling the electronic control suspension with the determined first control value when entering the obstacle, and collecting new sensing data through a physical sensor, and correcting the first characteristic value based on the new sensing data.

Abstract: The present disclosure relates to a method and an apparatus for controlling an electronic control suspension using a deep learning-based road surface classification model. The method for controlling an electronic control suspension in a vehicle including a camera and a GPS receiver may include collecting location information of the vehicle using the GPS receiver while driving, identifying whether there is a previously generated road surface classification model corresponding to a front obstacle when the front obstacle is detected, determining a first control value based on a first characteristic value corresponding to the road surface classification model when there is the road surface classification model as a result of the identification, controlling the electronic control suspension with the determined first control value when entering the obstacle, and collecting new sensing data through a physical sensor, and correcting the first characteristic value based on the new sensing data.