An approach to arrange sensors needed for automated driving, especially where semitrailer trucks are operating in an autonomous convoy with one automated or semi-automated truck following another. The sensors are fitted to a location adjacent to or within the exterior rearview mirrors, on each of the left- and right-hand side of the tractor. The sensors provide overlapping fields of view looking forward of the vehicle and to both the left and right hand sides at the same time.

This application describes a method, system, and apparatus for measuring the depth of a body of water ahead of the user's location or position. The user can be a driver of a vehicle. The apparatus includes a fording depth sensor, a second fording depth sensor, a proximity sensor to determine road angle or position ahead of the vehicle, wherein the proximity sensor is designed to operate underneath the water surface and a control unit configured to use signals of the wading depth and sensors to compute a wading depth at a location ahead of the direction of vehicle movement and/or to compute a distance ahead of the direction of vehicle movement to maximum wading depth. A method of building the apparatus, system, and vehicle is also provided.

An on-vehicle flash flood safety system is disclosed to install a water level sensor between front tires, underneath of vehicle which checks the water level on road. When the water level is found above a predetermined mark, an extendible-retractable shaft is extended which contains a water flow sensor and SONAR device to find the depth and speed of flash flood water. This data is sent to a Control, Display, and Alert Unit which calculates if it is dangerous to enter into such water. If found dangerous, the system gives an audio-visual alarm. System also collects location using GPS and sends location, water, and speed of water data to a computer server to be stored and distributed to other vehicles. By means of the aforesaid performance, on-vehicle flash flood alarm System informs the driver of the motor vehicle to not proceed if there is danger of the vehicle getting swept away.

A vehicle floor assembly includes a floor structure and a capacitive proximity sensor assembly configured to detect a user touch command and a user pressure command. The floor assembly further includes a controller for receiving the user touch command and pressure command and controlling a vehicle related operation based on the detected user input commands.

An object identification device according to the present invention includes: an acquisition unit that acquires, from a sensor that measures a position of an object and a speed of the object, sensor information measured by the sensor, and acquires size information from a device that transmits size information indicating a size and a position of the object; a designator adding unit that adds, to each piece of the sensor information, a sensor position designator indicating which part of the object is likely to be detected; and an information integration unit that determines, based on the sensor position designator, whether the object corresponding to the size information and the object corresponding to the sensor information are the same.

A controlling apparatus 1 according to an embodiment is a controlling apparatus of a hybrid vehicle 30 including a motor generator 3 that is mechanically connected to an internal combustion engine 2 and that can generate power in response to rotation of the internal combustion engine 2 and provide torque to the internal combustion engine 2, the controlling apparatus 1 including a rotation information acquiring unit 11 that acquires rotation information of the motor generator 3 with a higher resolution than rotation information of the internal combustion engine 2 and a power generation determining unit 12 that makes a determination regarding the power generation by the motor generator 3 based on the rotation information of the motor generator 3.

This disclosure is generally directed to systems and methods for detecting a water depth level using capacitive sensors. The systems and methods disclosed herein receive a first capacitive signal from a first capacitive sensor in a wheel well of an autonomous vehicle (AV) and determine that the first capacitive signal exceeds a threshold value. The AV controller may be configured to determine water levels using a capacitive sensor system, and perform mitigating actions that cause the vehicle to either clean soiled capacitive sensors, or move the vehicle to a location that mitigates the risk of vehicle damage. Other mitigating actions may be performed as well, including disabling or powering down critical vehicle components when the vehicle cannot be moved to another location, providing means for emergency vehicle exit, and sending warning messages to the fleet control server, to occupants of the AV, or to other emergency personnel.

Method and device for processing LIDAR sensor data are disclosed. The method includes (i) receiving from the LIDAR sensor a first dataset having a plurality of first data points representative of respective coordinates and associated with respective normal vectors, (ii) determining an uncertainty parameter for a given first data point based on a normal covariance of the normal vector of the given first data point where the normal covariance takes into account a measurement error of the LIDAR sensor when determining the respective coordinates of the given first data point, (iii) in response to the uncertainty parameter being above a pre-determined threshold, excluding the given first data point from the plurality of first data points, (iv) using the filtered plurality of first data points, instead of the plurality of first data points, for merging the first dataset of the LIDAR sensor with a second dataset of the LIDAR sensor.

An automatic driving vehicle that is automatically movable, the automatic driving vehicle includes a LIDAR configured to acquire external world information on an automatic movement, and a bracket holding the LIDAR and fixed to the automatic driving vehicle. The bracket is fixed to a rearview mirror which is as another device different from the LIDAR.

A slope estimation device estimates a slope of a vehicle traveling road, and includes an input section that acquires a detected value of an acceleration sensor for detecting acceleration in a front-back direction of the vehicle, a centripetal force detecting section that detects centripetal force acting on the acceleration sensor due to a turning motion of the vehicle, and a slope computing section that computes the slope of the vehicle traveling road based on the detected value of the acceleration sensor. When the vehicle is in the turning motion, the slope computing section computes the slope of the traveling road by determining a component of the centripetal force superimposed on the detected value of the acceleration sensor based on a turning center position of the vehicle, a gravity center position of the vehicle, and an installation position of acceleration sensor, and subtracting the component of the centripetal force from the detected value of the acceleration sensor.