A device for searching a parking space includes at least one space detection sensor mounted on a vehicle, and a controller that analyzes sensed information obtained through the space detection sensor to recognize space and object information within a parking lot, predicts a distribution of available parking spaces in the parking lot based on the recognized space and object information, and determines an optimal available parking space based on the distribution of the available parking spaces and characteristics of a driver.

A method of estimating an operating parameter of industrial mechanical power transmission equipment is provided. The method includes acquiring data of a first parameter of the gearbox using a sensor, inferring a second parameter of a gearbox based on the acquired data of the first parameter by using a machine learning model, wherein the second parameter is of a different type from the first parameter and includes at least one of a torque of the gearbox, a rotational speed of the gearbox, or an overhung shaft force of the gearbox, and outputting the estimated second parameter.

Disclosed are an ultrasonic sensor, a parking assistance system including the ultrasonic sensor, and a signal processing method, the ultrasonic sensor being provided with two different signal processing paths referred to as a data compression unit and a data extractor and transmitting both processed signal data to a controller by a data transmitter, thereby complementing the advantages of each signal processing path to enhance the precision of the detection result of the sensor.

Commercial personal mobile vehicles (PMVs) managed by a fleet management system are sometimes equipped with a radar sensor to detect objects in an environment external to the PMVs. Specifically, the PMV may be equipped with a variety of sensors, such as a radar, a sonar sensor, a (optional) camera, an inertia measurement unit (IMU), and/or the like. The combination of a radar reflection signal and a sonar signal may provide measurements of characteristics such as a Doppler velocity and height information of a nearby object, which may be input to a machine learning classifier to determine the probability that the nearby object is a VRU. For another example, the reflection pattern from radar and ultrasonic may be used to input to a machine learning classifier to determine a type of the road surface, e.g., an asphalt road surface, a concrete sidewalk surface, a wet-grass lawn surface, and/or the like.

A method for inertia drive control is provided. The method includes performing advanced inertia drive control by an inertia drive controller. The controller detects a speed reduction event during road driving of a vehicle, lane division together with road type division for a road, and performs inertia drive control guide and the inertia drive control based on drive conditions of lane change and lane maintenance.

A method for supplying data for an at least partially automated vehicle. The method including: detecting the sensor data of an infrastructure; fusing the sensor data to form an environment model; wireless transmission of the environment model data to the at least partially automated vehicle; and wireless transmission of context data, relating to a location of the at least partially automated vehicle, to the at least partially automated vehicle, it being possible to evaluate the environment model data in a defined manner with the aid of the context data.

A method, system, apparatus, and architecture are provided for generating a sound-enhanced sensing envelope. A plurality of sensors and one or more passive sound sensors of a vehicle are used to collect and process sensor data signals characterizing an exterior environment of the vehicle, thereby generating a sensing envelope around the vehicle using direct sensing data signals and a sound-enhanced sensing envelope around the vehicle using indirect sensing data signals. The sound-enhanced sensing envelope is used to evaluate advanced driver assistance system commands for the vehicle with respect to safety-related events identified by the indirect sensing data signals.

A method of sensing a three-dimensional (3D) space using at least one sensor is proposed. The method can include acquiring spatial information over time for the sensed 3D space, applying a neural network based object classification model to the acquired spatial information over time to identify at least one object in the sensed 3D space. The method can also include tracking the sensed 3D space including the identified at least one object, and using information related to the tracked 3D space.

A system for monitoring an acoustic scene outside a vehicle; the system including: a vehicle with wheels and a trunk, an acoustic sensor disposed in the trunk, a control unit operatively connected to the acoustic sensor, and at least one neural network operatively connected to the control unit, and trained in such a way to correlate the characteristics of an audio signal with types of road surfaces; the control unit is configured in such a way to receive an audio signal detected by the acoustic sensor while the vehicle is traveling, extract the characteristics of the audio signal and input said characteristics of the audio signal to the neural network in order to identify the type of road surface covered by the vehicle wheels.

A system and corresponding method for autonomous driving of a vehicle are provided. The system comprises at least one neural network (NN) that generates at least one output for controlling the autonomous driving. The system further comprises a main data path that routes bulk sensor data to the at least one NN and a low-latency data path with reduced latency relative to the main data path. The low-latency data path routes limited sensor data to the at least one NN which, in turn, employs the limited sensor data to improve performance of the at least one NN's processing of the bulk sensor data for generating the at least one output. Improving performance of the at least one NN's processing of the bulk sensor data enables the system to, for example, identify a safety hazard sooner, enabling the autonomous driving to divert the vehicle and avoid contact with the safety hazard.