Abstract: Driving simulations may be generated based on driving log data and used to validate autonomous vehicle safety systems. A driving simulation system may receive driving log data from autonomous vehicles and determine events which caused a vehicle to diverge from a planned trajectory. Driving simulations may be generated based on the driving log data, and executed using a simulated vehicle that follows the initial planned trajectory of the autonomous vehicle. The driving simulations may be analyzed to detect potential collisions and near misses, and to determine success conditions for the behaviors of vehicle safety systems. Driving simulations and associated success conditions may be aggregated and used in validation suites for vehicle controllers and/or vehicle safety systems, thereby providing more comprehensive and robust autonomous vehicle validation based on real-world driving scenarios.

Abstract: Techniques are discussed herein for executing log-based driving simulations to evaluate the performance and functionalities of vehicle control systems. A simulation system may execute a log-based driving simulation including playback agents whose behavior is based on the log data captured by a vehicle operating in an environment. The simulation system may determine interactions associated with the playback agents, and may convert the playback agents to smart agents during the driving simulation. During a driving simulation, playback agents that have been converted to smart agents may interact with additional playback agents, causing a cascading effect of additional conversions. Converting playback agents to smart agents may include initiating a planning component to control the smart agent, which may be based on determinations of a destination and/or driving attributes based on the playback agent.

Abstract: Techniques are discussed herein for executing log-based driving simulations to evaluate the performance and functionalities of vehicle control systems. A simulation system may execute a log-based driving simulation including playback agents whose behavior is based on the log data captured by a vehicle operating in an environment. The simulation system may determine interactions associated with the playback agents, and may convert the playback agents to smart agents during the driving simulation. During a driving simulation, playback agents that have been converted to smart agents may interact with additional playback agents, causing a cascading effect of additional conversions. Converting playback agents to smart agents may include initiating a planning component to control the smart agent, which may be based on determinations of a destination and/or driving attributes based on the playback agent.

Abstract: A system for generating simulated LiDAR data may include a depth offset generator and an intensity value generator. The depth offset generator may be configured to receive environment data including depth information, e.g., a depth map, the environment. The depth offset generator may determine an optical flow field from the depth information and estimate depths for positions to simulate LiDAR sensor data. field. The depth offset generator can also generate timestamp information based on attributes of the simulated LiDAR sensor, and determine the estimated depths using the timestamp information. The intensity value generator may be configured to determine an intensity for pixels based on physical attributes associated with those pixels. The simulated LiDAR data may be used in simulations run on autonomous vehicle control systems.