Camera based artificial intelligence for a smart vehicle braking system

A braking system is an essential value in a vehicle particularly for a safety precaution. The higher number rate of traffic accidents mostly in Indonesia shows that the dominant cause of accidents is due to the human factor. The physical condition such as tired or sleepy during driving is the primary problem according to the survey. In order to assist a person when driving a vehicle, an artificial intelligence method is necessary to be integrated to ensure the safety of surrounding people inside and outside the vehicle. This study focuses on implementing the method of identifying object and distance to provide an indicator for braking action. Images from a stereo camera is processed by a neural network technique via a mini computer to classify as well as the distance of objects. Furthermore, selection of priorities are done to obtain the intensity of braking action. The result shows that process of classification and measurement requires period around 200 ms. Furthermore, braking action done by fuzzy controller sub-system shows that the intensity has smoother signal with the object distance variation compare to the direct method. Objects are firstly identified by the presence of a stereo camera, later on the decision of braking intensity is generated by two processing unit namely conventional and fuzzy unit. This is achieved by processing the data saved from the object detection using two system via MATLAB software. The object identification result, distance measurement and the period of object detection is presented. Moreover, the response of braking intensity using data is processed with both conventional and fuzzy unit systems are also presented. he implementation of this study is for the heavy vehicle such buses or trucks that requires higher safety during the journey.