Abstract: The automated driving perception systems described herein provide technical solutions for technical problems facing navigation sensors for autonomous vehicle navigation. These systems may be used to combine inputs from multiple navigation sensors to provide a multimodal perception system. These multimodal perception systems may augment raw data within a development framework to improve performance of object detection, classification, tracking, and sensor fusion under varying external conditions, such as adverse weather and light, as well as possible sensor errors or malfunctions like miss-calibration, noise, and dirty or faulty sensors. This augmentation may include injection of noise, occlusions, and misalignments from raw sensor data, and may include ground-truth labeling to match the augmented data. This augmentation provides improved robustness of the trained perception algorithms against calibration, noise, occlusion, and faults that may exist in real-world scenarios.

Abstract: Systems and techniques for controlling a mobile robot. In an example, the system may include a processor and memory, including instructions, which when executed by the processor, cause the processor to determine a state of the mobile robot. The state of the mobile robot may be determined using at least one of: data provided by the mobile robot or data captured by one or more sensors proximate to or attached to the mobile robot. The system may determine a state of an object proximate to the mobile robot using the data captured by the one or more sensors, and identify information relating to one or more available stopping points. The system may identify a condition of the mobile robot that requires the mobile robot to stop and issue a command to the mobile robot to navigate to a particular one of the one or more available stopping points.

Abstract: Disclosed herein are systems, devices, and methods of a safety system for analyzing and improving the safety of environments that may be shared between robots and humans. The safety system may receive a safety envelope that includes a reachable set of locations at an expected position of an object at a prediction time. The receiver may also receive a perception prediction that may be based on the safety envelope and may include environmental information associated with the object at the expected position at the prediction time. The safety system may also include a processor that generates an instruction to move a robot according to a safe movement instruction based on whether a perception check exceeds a predetermined threshold, wherein the perception check may be based on a difference between the perception prediction and sensor information indicative of the environment of the object at the prediction time.

Abstract: Disclosed herein are systems, devices, and methods of a safety system for analyzing and improving the safety of collaborative environments in which a robot may interact a human. The safety system may determine a monitored attribute of a person within an operating environment of a robot, where the monitored attribute may be based on received sensor information about the person in the operating environment. In addition, the safety system may determine a risk score for the person based on the monitored attribute. The risk score may be defined by (1) a collision probability that the person will cause an interference during a planned operation of the robot and (2) a severity level associated with the interference. The safety system may also generate a mitigating instruction for the robot if the risk score exceeds a threshold level.

Abstract: Various aspects of techniques, systems, and use cases include robot safety. A device in a network may include processing circuitry and memory including instructions, which when executed by the processing circuitry, cause the processing circuitry to perform operations. The operations may include collecting telemetry data for a robot, the robot operating according to a path control plan generated using reinforcement learning with a safety factor as a reward function, and detecting that a safety event, involving a robot action, has occurred with the robot and an object. The operations may include simulating a recreation of the safety event to determine whether a simulated action matches the robot action.

Abstract: Disclosed herein are systems, devices, and methods for efficiently checking the integrity of a robot system. The integrity-checking system may generate a predefined motion instruction for a robot, where the predefined motion instruction instructs the robot to perform a random movement at a test time. The random movement may be associated with an expected observation at the test time. The integrity-checking system may also determine a systematic failure based on a difference between the expected observation and a current observation of the robot at the test time. The current observation may be determined from received sensor data, and if the integrity-checking system detects a failure, it may stop the robot's motion or other mitigating instructions.

Abstract: Devices and methods for determining an action in the presence of road users are provided in this disclosure. A device may include a processor. The processor may be configured to access environment information including an indication of a size of road users intersecting with a predetermined route of a vehicle in a road environment. The processor may further be configured to prioritize an anticipated movement of at least one of the road users over a predicted movement of the vehicle within the predetermined route based on the size of road users. The processor may further be configured to determine a vehicle action allowing the anticipated movement of the at least one road user.

Abstract: According to various aspects, a safety module is described including: one or more processors configured to receive road information representing a geometry of one or more roads in a Cartesian coordinate system, determine a lane coordinate system based on the received road information, the lane coordinate system including a plurality of lane segments arranged along a longitudinal direction and along a lateral direction of the lane coordinate system, wherein a length information and a width information are assigned to each of the lane segments, and determine a potential collision event based on the lane coordinate system.

Abstract: Disclosed herein are systems, devices, and methods of a safety system for monitoring the in-vehicle safety of internal objects within a vehicle. The safety system generates a digital twin of the interior objects from vehicle configuration data indicating a configuration of an interior environment of the vehicle, from interior object data associated with the interior object within the interior environment of the vehicle, and from vehicle situation data that indicates an operating status of the vehicle. The digital twin is an abstract model of the interior objects within the interior environment of the vehicle, and the safety system generates, based on the digital twin, a safety score associated with an operating behavior of the vehicle. Based on the safety score, the safety system determines a target level for the operating behavior.

Abstract: Disclosed herein is an active cyclist and/or pedestrian safety system for identifying, warning, and reacting to dangerous situations that may be experienced by cyclists and/or pedestrians. The safety system may receive first information indicative of a head position of a cyclist and determine, based on the first information, a field of view of the cyclist. The safety system may receive second information indicative of an environment of the cyclist and determine, based on the field of view and the environment, an expected trajectory of the cyclist in a next road segment. The safety system may also determine, based on the field of view and the environment, a risk probability for the expected trajectory of the cyclist in the next road segment. The safety system may also generate an instruction to transmit a warning to the cyclist if the risk probability exceeds a threshold value.

Abstract: Techniques are disclosed to facilitate path planning safety guiding robots (SGR) for safely navigating and guiding humans through autonomous environments having other autonomous agents such as stationary and/or mobile robots.

Abstract: A monitoring system may include a memory having computer-readable instructions stored thereon and a processor operatively coupled to the memory. The processor may read and execute the computer-readable instructions to perform or control performance of operations. The operations may include receive, prior to a collision involving a vehicle, sensor data representative of a feature of an internal environment and determine the collision has occurred. The operations may include automatically instruct, based on the collision, a sensor to generate another sensor data representative of another feature of the internal environment. The operations may include receive the another sensor data from the sensor and compare the sensor data and the another sensor data to accident data corresponding to previous accidents. The accident data may include a diagnosed injury and an accident severity of each of the previous accidents. The operations may include determine a severity of the collision based on the comparison.

Abstract: Disclosed herein are systems and methods for detecting and mitigating inappropriate behavior. The systems and methods may include receiving data. Using the data a harassment score and/or classification for a behavior may be determined. Using the harassment score and/or classification, a determination may be made as to when the harassment score and/or classification for the behavior exceeds a threshold. When the threshold is exceeded, a protection system and/or action engine may be activated to mitigate the inappropriate behavior.

Abstract: Disclosed herein is a vehicle handover system that monitors an environment of a vehicle. The vehicle handover system receives a transition request to change control of the vehicle from an automated driving mode to a passenger of the vehicle. The vehicle handover system detects a key event that may be relevant to the transition request and the detection of the key event is based on the monitored environment. The vehicle handover system may generate a handover scene that includes images associated with the key event, and the images include an image sequence over a time-period of the key event. Before the vehicle handover system changes control of the vehicle from the automated driving mode to the passenger, the handover scene is displayed to the passenger.

Abstract: Disclosed herein is a passenger monitoring system for monitoring an observed attribute of a passenger in a vehicle. The observed attribute may include a gaze of the passenger, a head track of the passenger, and other observations about the passenger in the vehicle. Based on the observed attribute(s), a field of view of the passenger may be determined. Based on the field of view, a focus point of the passenger may be determined, where the focus point is estimated to be within the field of view. If a sign (e.g., a road sign, a billboard, etc.) is within the field of view of the passenger, record an attention score for the sign based on a duration of time during which the sign is within the field of view and estimated to be the focus point of the passenger.

Abstract: A vehicle control system for proactively calculating a safe motion range (e.g., safe speed, a safe acceleration, and/or a safe jerk range) for a road segment and selecting and verifying an appropriate domain for the vehicle using, for example, information about the current road segment, information about the next road segment(s), information obtained from sensors, information obtained from map systems, information from an object-based safety layer, and/or other information about the vehicle's operating conditions in the current and future road segments. In addition, once the safe motion range is calculated, this information may be used to either warn/inform a human driver or directly enforce an appropriate vehicle maneuver to ensure a safe motion in the vehicle's next road segment(s).

Abstract: A system of a collaborative Autonomous Vehicle (AV) Safety Driving Model (SDM) system, including at least one processor; and a non-transitory computer-readable storage medium including instructions that, when executed by the at least one processor, cause the at least one processor to: generate, in response to a condition being satisfied, an SDM message including encoded data representing a warning or a safety parameter; and cause a transceiver to transmit the generated SDM message.

Abstract: Disclosed are embodiments for coupling an autonomous vehicle with service equipment. The service equipment is configured to perform one or more services when coupled with the autonomous vehicle. In some embodiments, an environmental model generated by the autonomous vehicle is shared with a controller of the service equipment, which fuses sensor data collected from an on-board sensor and the environmental model from the autonomous vehicle to generate an integrated environmental model. The controller of the service equipment then performs the service based on the integrated environmental model.

Abstract: A safety system for a vehicle may include a processor configured to determine whether a further vehicle is approaching the vehicle from a backside or a lateral side; determine that a collision of the further vehicle with the vehicle is likely; determine an evasive maneuver of the vehicle such that the evasive maneuver reduces the collision likelihood or impact between the vehicle and the further vehicle; and provide control instructions to control the vehicle to perform the evasive maneuver.

Abstract: Disclosed are embodiments for adjusting a vehicle stopping point. The vehicle stopping point is a point between a route of the vehicle and a second route. in some embodiments, an adjustment to the stopping point is determined based on ranking secondary routes that are adjusted based on the adjusted vehicle stopping point. Tanking of the secondary routes is based, in sonic embodiments, on a score of segment(s) included in the secondary routes. In some cases, the ranking of the segments considers safety information associated with each of the segments.