A vehicular test system for testing a vehicular sensing system includes a sensor support structure having a proximal end disposed at a vehicle, a distal end extending away from the vehicle, and a force providing element that provides a force to move the distal end of the sensor support structure. A vehicular sensor is disposed at the distal end of the sensor support structure. When the vehicular sensor is approaching a collision with an object, such as during testing of vehicular sensors and vehicular sensing systems, a control controls the force providing element to move the distal end of the sensor support structure and the vehicular sensor to avoid the collision.

Provided are methods for assisting a user in interaction with a vehicle. The methods can include obtaining sensor data representing a user; determining at least one of: (i) a distance between a body part of the user and an object associated with the vehicle, or (ii) a direction from the body part of the user to the object; and causing, by the accessibility system, at least one notification to be presented to the user, where the least one notification indicates at least one of: (i) the distance between the body part of the user and the object, or (ii) the direction from the body part of the user to the object. Systems and computer program products are also provided.

A system and method for collision warning. The method includes calculating a dynamic trajectory of a vehicle, the vehicle including at least one camera for capturing visual multimedia content, wherein the dynamic trajectory indicates a projected movement path of the vehicle, wherein the dynamic trajectory is calculated based on a respective stopping distance and a radius of movement determined for the vehicle; generating an overlay based on the at least one dynamic trajectory, wherein the overlay indicates at least one risk, wherein each of the at least one risk is located within the at least one dynamic trajectory; and applying the overlay to the visual multimedia content.

A vehicle analysis environment includes one or more display screens, such as a display screen wall or an array of display screens. While a vehicle is in the vehicle analysis environment, a vehicle analysis system renders and displays one or more vehicle sensor calibration targets and/or one or more simulated events on the one or more display screens. Vehicle sensors of the vehicle capture sensor data while in the vehicle analysis environment. The sensor data depict the vehicle sensor calibration targets and/or the simulated events that are displayed on the one or more display screens. The vehicle can output actions based on the simulated event and/or can calibrate its vehicle sensors based on the vehicle sensor calibration targets.

A method, system, and device for mobile robot operations. The method comprises a mobile robot comprising at least one sensor configured to capture data related to the robot's surroundings traveling on a pedestrian pathway. The method also comprises the mobile robot using the sensor to collect data relating to moving objects in the robot's surroundings. The method further comprises detecting at least one pedestrian within the collected data, said pedestrian moving with a motion pattern. The method also comprises analyzing the pedestrian's motion pattern to determine and output the pedestrian's intent. The system comprises at least one mobile robot configured to travel on pedestrian pathways. The robot comprises at least one sensor configured to capture data related to the robot's surroundings and to collect data relating to moving objects in said surroundings. The system also comprises at least one pedestrian detector. The pedestrian detector is configured to process the sensor data to at least detect a pedestrian moving with a motion pattern. It is also configured to analyze the pedestrian's motion pattern and determine and output the pedestrian's intent. The robot comprises at least one sensor configured to capture data related to the robot's surroundings and to collect data relating to moving objects in said surroundings. The robot also comprises at least one processing component configured to process the sensor data to at least detect a pedestrian moving with a motion pattern, and analyze the pedestrian's motion pattern, and determine and output the pedestrian's intent.

A work vehicle periphery monitoring system includes: an alarm range storage unit that stores an alarm range, in which an alarm output is required when an object is present, in a detection range of an object detection device that detects an object present in a periphery of a work vehicle; a work mode determination unit that determines a work mode of the work vehicle; an alarm range changing unit that changes the alarm range in the detection range when it is determined that the work mode is a specific work mode; and an alarm control unit that causes an alarm device to output an alarm when an object is present in the alarm range.

In a case where a person moves away in a longitudinal direction from the vicinity of a vehicle, a condition for generating a warning is satisfied due to a change in a speed in a transverse direction. Thus, a warning system generates an erroneous warning. In order to solve this problem, there are proposed a target detection system for a vehicle and a target detection method for a vehicle, both of which are capable of computing a final risk level, taking into consideration not only results of recomputing a time-to-collision and an impact point, but also the presence or absence of a target that is detected by a camera sensor. The time-to-collision and the impact point are recomputed, taking into consideration a change in a speed in a transverse direction that occurs when the target moves in the longitudinal direction.

The techniques and systems herein enable target-velocity estimation using position variance. Specifically, a plurality of detections of a target are received for respective times as the target moves relative to a host vehicle. Based on the detections, two-dimensional positions of the target relative to the host vehicle are determined for the respective times. Based on the positions of the target at the respective times, a first variance is determined for a first dimension of the positions, and a second variance is determined for a second dimension of the positions. Based on the first and second variances, an estimated velocity of the target is calculated. By basing the estimated velocity on the variances of the positions, more-accurate estimated velocities may be generated sooner, thus enabling better performance of downstream operations.

A method for automatically training a neural network includes at a trainer having a first communication device and a perception recorder, continuously recording the surroundings in the vicinity of the first object; receiving, at the trainer, a message from a communication device associated with an object in the vicinity of the trainer, the message including information about the position and the type of the object; identifying a recording corresponding to the time at which the message is received from the object; correlating the received positional information about the second object with a corresponding location in the recording to identify the object in the recording; classifying the identified object based on the type of information received in the message from the object; and using the classified recording to train the neural network.

A sensing device detects an object in a blind spot in a surrounding environment of a mobile body. The sensing device includes a distance measurer, a detector, and a controller. The distance measurer acquires distance information indicating a distance from the mobile body to the surrounding environment. The detector detects the object in the blind spot. The controller controls operation of the detector. The controller detects the blind spot in the surrounding environment, based on the distance information acquired by the distance measurer. The controller controls precision at which the detector is caused to detect the object in the blind spot, according to a distance to the blind spot.