In an abnormality determination device for determining presence or absence of an abnormality of a 6-axis inertial measurement sensor installed in a vehicle to detect a forward-backward acceleration, a lateral acceleration, a vertical acceleration, a roll rate, a pitch rate, and a yaw rate of the vehicle, the abnormality determination device includes: a 3-axis inertial measurement sensor that detects the forward-backward acceleration, the lateral acceleration, and the yaw rate; and an abnormality determination unit that determines presence or absence of an abnormality of the 6-axis inertial measurement sensor, wherein the abnormality determination unit determines the presence or absence of an abnormality of the 6-axis inertial measurement sensor by comparing the forward-backward acceleration, the lateral acceleration, and the yaw rate acquired by the 6-axis inertial measurement sensor with the forward-backward acceleration, the lateral acceleration, and the yaw rate acquired by the 3-axis inertial measurement sensor, respectively.

A vehicle drive assist apparatus includes a traveling environment information acquisition unit, a traveling state information acquisition unit, and a traveling control unit. The traveling environment information acquisition unit acquires traveling environment information. The traveling state information acquisition unit acquires traveling state information. The traveling control unit includes a malfunction detector and a takeover request processor. The malfunction detector detects a malfunction in the traveling environment information acquisition unit and the traveling state information acquisition unit. The takeover request processor executes a takeover request process for manual driving in a case where the malfunction is detected. The takeover request processor includes a waiting time measurement section and an output restricting section. The waiting time measurement section measures a waiting time from detection of the malfunction to transition to the manual driving. The output restricting section restricts an output of a drive source during the waiting time.

Systems, methods and apparatus to collect sensor data generated in an autonomous vehicle. Sensors of the vehicle generate a sensor data stream that is buffered, in parallel and in a cyclic way, in a first cyclic buffer and a larger second cyclic buffer respectively. An advanced driver assistance system of the vehicle generates an accident signal when detecting or predicting an accident and provides a training signal when detecting a fault in object detection, recognition, identification or classification. The accident signal causes a sensor data stream segment to be copied from the first cyclic buffer into a slot of a non-volatile memory, selected from a plurality of slots in a round robin way. The training signal causes a sensor data stream segment to be copied from the second cyclic buffer into an area of the non-volatile memory outside of the slots reserved for the first cyclic buffer.

The present teaching relates to method, system, medium, and implementations for sensor calibration. An ego vehicle determines whether a sensor deployed on the ego vehicle to facilitate autonomous driving of the ego vehicle needs to be calibrated and sends, if it is determined that the sensor needs to be calibrated, a request for assistance in collaborative calibration of the sensor, with a first position of the ego vehicle or a first configuration of the sensor with respect to the ego vehicle. When a response of the request is received, an assisting vehicle is indicated to travel to be near the ego vehicle to facilitate the calibration of the sensor by collaborating with the moving ego vehicle and the ego vehicle coordinates with the assisting vehicle to enable the sensor to acquire information of a target present on the assisting vehicle for the collaborative calibration of the sensor.

An autonomous driving system configured to make an abnormality determination for an in-vehicle device at an abnormality determination point while an autonomous vehicle is driving autonomously includes: a route search unit configured to search for a travel route from a departure point to a destination point; a route determination unit configured to determine a determination route for making the abnormality determination for the in-vehicle device from the searched travel route, based on necessity of making the abnormality determination for the in-vehicle device and the number of the abnormality determination points on the travel route; and an abnormality determination unit configured to make the abnormality determination for the in-vehicle device at the abnormality determination point while the autonomous vehicle is driving along the determination route.

An embodiment vehicle for performing autonomous driving includes a memory configured to store map information, a sensor configured to acquire surrounding objects information related to the vehicle, a communicator configured to communicate with a server and a surrounding vehicle, and a controller configured to form autonomous driving data for the autonomous driving of the vehicle based on the map information and data acquired through the sensor and the communicator, wherein the controller is configured to cause performance of the autonomous driving of the vehicle based on the autonomous driving data formed at a time point closest to a time point at which a failure of the sensor occurs in response to the failure of the sensor and a determination that driving of the vehicle by a driver is not available.

A driving assistance device (10) is mounted in a mobile body (100). An abnormality detection unit (22) detects an abnormality in a sensor mounted in a peripheral body moving on a periphery of the mobile body (100). An assistance determination unit (23) reads a control pattern corresponding to a sensing area of a sensor whose abnormality has been detected by the abnormality detection unit (22), from a pattern storage unit (31). A path generation unit (24) generates path data indicating a moving path of the mobile body (100) to correspond to the control pattern.

A method for the self-check of at least one driving function of an autonomous or semi-autonomous vehicle in vehicle operation, after an error message about the at least one driving function, in which in one step, at least one vehicle electronic system and/or at least one sensor is/are restarted, a check is made for a further appearance of the error message after each restart, and in the event an error message is not repeated after the restart, the driving function in question is checked during operation of the autonomous or semi-autonomous vehicle.

An object recognition apparatus for recognizing an object is provided. The apparatus includes first and second object determinations units configured to determine the object based on at least detection results of the object by first and second sensors and at least detection results of the object by third and fourth sensors, respectively; an object recognition unit configured to recognize the object based on a determination result by the first and/or second object determination unit; first and second calculation units configured to calculate a difference between the detection result by the first sensor and the detection result by the second sensor and a difference between the detection results by the third and fourth sensor, respectively; and a reliability decision unit configured to decide reliabilities of the determination results by the object determination units based on calculation results by the calculation units.

In an embodiment, a method comprises: receiving ambient sound; determining if the ambient sound includes a siren; in accordance with determining that the ambient sound includes a siren, determining a first location associated with the siren; receiving a camera image; determining if the camera image includes a flashing light; in accordance with determining that the camera image includes a flashing light, determining a second location associated with the flashing light; 3D data; determining if the 3D data includes an object; in accordance with determining that the 3D data includes an object, determining a third location associated with the object; determining a presence of an emergency vehicle based on the siren, detected flashing light and detected object; determining an estimated location of the emergency vehicle based on the first, second and third locations; and initiating an action related to the vehicle based on the determined presence and location.