A vehicle control system employing acoustic and impact sensors for sensing acoustics and vibrations at a vehicle to detect environmental conditions and provide appropriate vehicle control and driver warnings according to the environmental conditions. The acoustics may include sounds generated by objects in the external environment surrounding the vehicle or sounds generated by impacts on the vehicle. The vibrations may include vibrations of the vehicle generated by the sounds generated by objects in the external environment surrounding the vehicle or vibrations of the vehicle generated by the impacts on the vehicle.

The present disclosure relates to a method of driving a motor vehicle. The method determines position data relating to at least one of a current position or a predicted future position of the motor vehicle detecting, using at least one sensor device, surroundings data relating to a surrounding environment of the motor vehicle, determining at least one driving intervention based on the surroundings data, and controlling at least one vehicle system of the motor vehicle to execute the determined at least one driving intervention. The at least one driving intervention executed by a selected software module that is selected based on the surroundings data, and the selected software module is selected from a plurality of software modules based on the position data. Each software module is configured to execute the at least one driving intervention.

The present invention relates to a method for avoiding collisions of a moving vehicle with other road users in the surroundings of the vehicle, comprising at least the method steps of: a) detecting, by means of one or more sensors, the vehicle surroundings and the other road users located therein; b) dividing the vehicle surroundings into a plurality of occupied areas; c) classifying the other road users detected in method step a), wherein, by means of the classification, at least one road user group is assigned to each of the other road users; d) prioritising the road user classified in method step c), taking into account both the classification carried out in method step c) and the occupied area defined in method step b), wherein road users from one or more predetermined road user groups in the particular occupied area are given a high priority and road users from other, non-predetermined road user groups in the particular occupied area are given a lower priority; and e) determining the probability of collision of the other road users with the vehicle, wherein the collision probability is determined in accordance with the prioritisation carried out in method step d) and the collision probability of the other road users having a high priority is determined first; f) changing or maintaining the current driving behaviour of the vehicle on the basis of the collision probabilities determined in method step e).

A vehicular device is disclosed, including a processor and plurality of sensors. The processor receives sensor data and determines vehicle occupant respiration based on the sensor data. The sensors can include acoustic sensors and imaging sensors. The processor can be configured for executing a machine learning algorithm to determine the occupant respiration.

The invention relates to a method for controlling an at least partially autonomously driving ego vehicle, at least the surroundings, legal driving conditions and the traffic in front of the ego vehicle in a current lane being detected by sensors. The problem addressed by the invention is that of providing an improved method. The problem is solved in that a first query relating to a possible speed is carried out, and a target acceleration is calculated when it is detected that the possible speed is greater than the current speed, and a second query is carried out as to whether there is a vehicle in an adjacent lane within an observation region, whether an acceleration at the calculated target acceleration is carried out, since no vehicle has been detected within the observation region, or whether no acceleration at the target acceleration is carried out, since a vehicle has been detected within the observation region.

A system and method of planning a path for an autonomous vehicle from the vehicle's initial configuration to the goal configuration which is collision-free, kinematically-feasible, and near-minimal in length. The vehicle is equipped with a plurality of perception sensors such as lidar, camera, etc., and is configured to operate in an autonomous mode. An onboard computing device is configured to process the sensor data and provide a dynamic occupancy grid map of the surrounding environment in real-time. Based on the occupancy grid map, the path planner can quickly calculate a collision-free and dynamically feasible path towards the goal configuration for the vehicle to follow.

A vehicle control device is mountable on a vehicle. The vehicle control device includes: a processor; and a memory storing instructions that, when executed by the processor, cause the vehicle control device to perform operations. The operations includes: acquiring detection information obtained by detecting an obstacle around the vehicle; performing collision determination of evaluating a possibility of collision with the obstacle, generating, based on the detection information, information on an approaching object that is an obstacle approaching the vehicle and information on a detection point group that is a set of detection points indicating an obstacle that does not move; and excluding the approaching object from collision determination in a case in which the detection point group has a shielding effect of shielding the vehicle from the approaching object. The shielding effect is evaluated by using a gap threshold that is set based on a vehicle width.

A reversing-assistance system for a vehicle, in particular for a utility vehicle, that exhibits a vehicle wiring harness, including: at least one sensor with a first wireless interface, to register a rear region of the vehicle and to transmit corresponding sensor signals in wireless manner; and a control unit, which is connected to the vehicle wiring harness and which includes a second wireless interface, to receive the sensor signals from the at least one sensor in wireless manner, to evaluate the sensor signals and to make them available; in which the control unit is configured to evaluate vehicle-related data independently of the sensor signals and, based on the data, to carry out a control of at least one component of the vehicle so as to perform a control function that is independent of the reversing assistant. Also described are a related method, a computer readable medium, and a utility vehicle.

In a drive assistance device, a required space estimation unit estimates a required space which is a space required for a subject vehicle to complete a starting. A required time estimation unit calculates an estimated required time which is an estimate value of a time required to complete the starting at a time of starting the subject vehicle. A collision time estimation unit calculates an estimated collision time which is an estimate value of a time until when an obstacle reaches the required space. A start margin calculation unit calculates a start margin indicating a temporal margin for the subject vehicle to complete the starting until the obstacle reaches the required space based on the estimated required time and the estimated collision time. The notification processing unit notifies a driver of the subject vehicle of the start margin.

An improved method for locating an acoustic source relative to a vehicle that requires, for example, only a single microphone is disclosed. The method comprises: obtaining an acoustic signal transmitted by the acoustic source; determining an observer frequency, referenced to the vehicle, of the acoustic signal; stipulating a velocity of the acoustic source; stipulating a relative position of the acoustic source relative to a position of the vehicle; determining a signal frequency; and locating the acoustic source by performing, n times, a Doppler calculation using the determined observer frequency, the stipulated velocity, the determined signal frequency, and the stipulated relative position.