Target detection method based on CARLA simulator

Abstract

A target detection method based on CARLA simulation mainly solves the problems that in existing automatic driving, target detection research is high in cost, poor in precision, low in speed and incapable of dealing with complex road conditions, and the implementation scheme is that the method comprises the steps: calling a sensor provided by a CARLA simulator to acquire image information, and generating a large number of training samples used for training a target detection model; taking the images as a training set, a verification set and a test set of a target detection algorithm; obtaining a model by training a target detection algorithm based on a convolutional neural network, verifying and improving model parameters, repeating the process to obtain a final model, obtaining the related index information of the final model through testing, and finally, applying the target detection model to a CARLA simulator to achieve high-precision, high-speed, efficient and stable target detection in automatic driving.

Description

Technical field [0001] The present invention relates to the field of automatic driving simulation platform design, and more particularly to a target detection method based on a Carla Simulation. Background technique [0002] In recent years, automotive electronic and advanced auxiliary driving systems have been long-term development, and automatic driving as a high-level stage of assist driving technology will become an important way to travel in the future. Environmental perception, precise positioning, path planning and line control are four critical parts of automatic driving technology, where environmental perception technology provides data support for other key technologies. Environmentallyifening technology is primarily responsible for completing the environmental information collection and target inspection work around the vehicle, providing reliable decision-making basis for the safe driving of automatic driving, and is also the basis for automatic driving. Therefore, en...

AI Technical Summary

Problems solved by technology

However, the target detection research based on actual self-driving cars requires a lot of manpower, material resources and time, and is quite difficult.

Secondly, in order to achieve the best accuracy requirements for target detection, target detection needs to be studied in different driving scenarios and different weather conditions, especially to test its performance in extreme bad weather and complex road conditions. However, to simulate such an environment in reality very difficult

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