Abstract: A vehicle capable of autonomous driving includes a lane detection system. The lane detection system is trained to predict lane lines using training images. The training images are automatically processed by a training module of the lane detection system in order to create ground truth data. The ground truth data is used to train the lane detection system to predict lane lines that are occluded in real-time images of roadways. The lane detection system predicts lane lines of a roadway in a real-time image even though the lane lines maybe indiscernible due to objects on the roadway or due to the position of the lane lines being in the horizon.

Abstract: A vehicle capable of autonomous driving includes a lane detection system. The lane detection system is trained to predict lane lines using training images. The training images are automatically processed by a training module of the lane detection system in order to create ground truth data. The ground truth data is used to train the lane detection system to predict lane lines that are occluded in real-time images of roadways. The lane detection system predicts lane lines of a roadway in a real-time image even though the lane lines maybe indiscernible due to objects on the roadway or due to the position of the lane lines being in the horizon.

Abstract: A modeling system trains computer models for an autonomous control system using computer simulated models of objects. The objects may be vehicles, and the computer simulated models may be virtual models of vehicles simulated by computer software. Since the vehicle models are computer simulated, various characteristics of the vehicle can be easily obtained by the modeling system. The various types of data may include geometric information of the vehicle, views of the vehicle from different perspectives, and the like. The modeling system can easily generate and label a large amount of training data using the characteristics of the computer simulated vehicles. The modeling system can use the training data to train computer models for the autonomous control system.

Abstract: A vehicle capable of autonomous driving includes a lane detection system. The lane detection system is trained to predict lane lines using training images. The training images are automatically processed by a training module of the lane detection system in order to create ground truth data. The ground truth data is used to train the lane detection system to predict lane lines that are occluded in real-time images of roadways. The lane detection system predicts lane lines of a roadway in a real-time image even though the lane lines maybe indiscernible due to objects on the roadway or due to the position of the lane lines being in the horizon.

Abstract: A modeling system trains computer models for an autonomous control system using computer simulated models of objects. The objects may be vehicles, and the computer simulated models may be virtual models of vehicles simulated by computer software. Since the vehicle models are computer simulated, various characteristics of the vehicle can be easily obtained by the modeling system. The various types of data may include geometric information of the vehicle, views of the vehicle from different perspectives, and the like. The modeling system can easily generate and label a large amount of training data using the characteristics of the computer simulated vehicles. The modeling system can use the training data to train computer models for the autonomous control system.

Abstract: A modeling system trains computer models for an autonomous control system using computer simulated models of objects. The objects may be vehicles, and the computer simulated models may be virtual models of vehicles simulated by computer software. Since the vehicle models are computer simulated, various characteristics of the vehicle can be easily obtained by the modeling system. The various types of data may include geometric information of the vehicle, views of the vehicle from different perspectives, and the like. The modeling system can easily generate and label a large amount of training data using the characteristics of the computer simulated vehicles. The modeling system can use the training data to train computer models for the autonomous control system.

Abstract: A vehicle capable of autonomous driving includes a lane detection system. The lane detection system is trained to predict lane lines using training images. The training images are automatically processed by a training module of the lane detection system in order to create ground truth data. The ground truth data is used to train the lane detection system to predict lane lines that are occluded in real-time images of roadways. The lane detection system predicts lane lines of a roadway in a real-time image even though the lane lines maybe indiscernible due to objects on the roadway or due to the position of the lane lines being in the horizon.

Abstract: A vehicle capable of autonomous driving includes a lane detection system. The lane detection system is trained to predict lane lines using training images. The training images are automatically processed by a training module of the lane detection system in order to create ground truth data. The ground truth data is used to train the lane detection system to predict lane lines that are occluded in real-time images of roadways. The lane detection system predicts lane lines of a roadway in a real-time image even though the lane lines maybe indiscernible due to objects on the roadway or due to the position of the lane lines being in the horizon.

Abstract: A modeling system trains computer models for an autonomous control system using computer simulated models of objects. The objects may be vehicles, and the computer simulated models may be virtual models of vehicles simulated by computer software. Since the vehicle models are computer simulated, various characteristics of the vehicle can be easily obtained by the modeling system. The various types of data may include geometric information of the vehicle, views of the vehicle from different perspectives, and the like. The modeling system can easily generate and label a large amount of training data using the characteristics of the computer simulated vehicles. The modeling system can use the training data to train computer models for the autonomous control system.

Abstract: A vehicle capable of autonomous driving includes a lane detection system. The lane detection system is trained to predict lane lines using training images. The training images are automatically processed by a training module of the lane detection system in order to create ground truth data. The ground truth data is used to train the lane detection system to predict lane lines that are occluded in real-time images of roadways. The lane detection system predicts lane lines of a roadway in a real-time image even though the lane lines maybe indiscernible due to objects on the roadway or due to the position of the lane lines being in the horizon.