A system evaluates modifications to components of an autonomous vehicle (AV) stack. The system receives driving recommendations traffic scenarios based on user annotations of video frames showing each traffic scenario. For each traffic scenario, the system predicts driving recommendations based on…
A system receives information describing paths traversed by vehicles of a vehicle type, for example, a bicycle or a motorcycle. The system determines locations along the paths. For each location the system determines a measure of likelihood of encountering vehicles of the vehicle type in traffic at…
A system uses a machine learning based model to determine attributes describing states of mind and behavior of traffic entities in video frames captured by an autonomous vehicle. The system classifies video frames according to traffic scenarios depicted, where each scenario is associated with a…
A system uses a machine learning based model to determine attributes describing states of mind and behavior of traffic entities in video frames captured by an autonomous vehicle. The system classifies video frames according to traffic scenarios depicted, where each scenario is associated with a…
An autonomous vehicle collects sensor data of an environment surrounding the autonomous vehicle including traffic entities such as pedestrians, bicyclists, or other vehicles. The sensor data is provided to a machine learning based model along with an expected turn direction of the autonomous…
Systems and methods for predicting user interaction with vehicles. A computing device receives an image and a video segment of a road scene, the first at least one of an image and a video segment being taken from a perspective of a participant in the road scene and then generates stimulus data…
Systems and methods for predicting user interaction with vehicles. A computing device receives an image and a video segment of a road scene, the first at least one of an image and a video segment being taken from a perspective of a participant in the road scene and then generates stimulus data…
A system uses neural networks to determine intents of traffic entities (e.g., pedestrians, bicycles, vehicles) in an environment surrounding a vehicle (e.g., an autonomous vehicle) and generates commands to control the vehicle based on the determined intents. The system receives images of the…
An autonomous vehicle uses machine learning based models such as neural networks to predict hidden context attributes associated with traffic entities. The hidden context represents behavior of the traffic entities in the traffic. The machine learning based model is configured to receive a video…
An autonomous vehicle uses machine learning based models such as neural networks to predict hidden context attributes associated with traffic entities. The hidden context represents behavior of the traffic entities in the traffic. The machine learning based model is configured to receive a video…