What is an Autonomous Driving Simulator?

Within the scope of the ATLASCAR2 project, this dissertation is based on studying and developing an autonomous driving assistance simulator named CARLA that implements an interface based in ROS to replicate the ATLASCAR2 setup in the simulation. The idea of using an autonomous driving simulator was proposed as a way to simplify the data aquisition process for the ATLASCAR2 since this process keeps on getting more and more difficult due to factors such as the complexity in the setup and the calibration processes of the installed sensors on the ATLASCAR2, as well as other factors such as the hardware interface and the time that is required to perform a single data aquisition using the ATLASCAR2. This tool can produce realistic scenarios and can be used for testing out the algorithms that are going to be implemented in the ATLASCAR2 in controlled environments, offering a degree of ground truth for these algorithms that can be used to evaluate the performance in these environments before implementing them in the real platform. The replication of the ATLASCAR2 setup process as well as the algorithms involved in CARLA will be discussed in further detail during this dissertation which include sections talking about the replication process and the algorithms involved, showing the results of the ATLASCAR2 setup implementation in CARLA as well as some other results produced from experiments with CARLA simulated data which include the use of computer vision algorithms as well as other algorithms that are currently being used in the ATLASCAR2.

For everyone


Simple and intuitive way to crop and keep track objects present in the image.

Real-time and archived data

Display information about each object present in the road both in real-time and the past history

User reporting

Report results about each object result(datasets) to the learning algorithm, helping in its management