A method for acquiring the surrounding environment of a motor vehicle. The motor vehicle has at least one ultrasound sensor. The ultrasound sensor includes an ultrasound transducer for sending, the ultrasound sensor receiving acoustic environmental signals, in particular audible environmental signals, in that the ultrasound sensor is controlled in its evaluation in such a way that sound waves having frequencies below a resonant frequency of the ultrasound transducer, in particular audible sound waves, of an environmental signal are acquired and evaluated. Environmental signals are understood as acoustic signals that are not produced by the ultrasound transducer itself, but rather by an external sound source that in particular differs from the motor vehicle. This can be for example the siren of a rescue vehicle or emergency vehicle, or the horn of some other motor vehicle.

A method for acquiring the surrounding environment of a motor vehicle. The motor vehicle has at least one ultrasound sensor. The ultrasound sensor includes an ultrasound transducer for sending, the ultrasound sensor receiving acoustic environmental signals, in particular audible environmental signals, in that the ultrasound sensor is controlled in its evaluation in such a way that sound waves having frequencies below a resonant frequency of the ultrasound transducer, in particular audible sound waves, of an environmental signal are acquired and evaluated. Environmental signals are understood as acoustic signals that are not produced by the ultrasound transducer itself, but rather by an external sound source that in particular differs from the motor vehicle. This can be for example the siren of a rescue vehicle or emergency vehicle, or the horn of some other motor vehicle.

A method and an apparatus for supporting a camera-based environment recognition by a means of transport using road wetness information from a first ultrasonic sensor. The method includes: recording a first signal representing an environment of the means of transport by the first ultrasonic sensor of the means of transport; recording a second signal representing the environment of the means of transport by a camera of the means of transport; obtaining road wetness information on the basis of the first signal; selecting a predefined set of parameters from a plurality of predefined sets of parameters as a function of the road wetness information; and performing an environment recognition on the basis of the second signal in conjunction with the predefined set of parameters.

A method and an apparatus for supporting a camera-based environment recognition by a means of transport using road wetness information from a first ultrasonic sensor. The method includes: recording a first signal representing an environment of the means of transport by the first ultrasonic sensor of the means of transport; recording a second signal representing the environment of the means of transport by a camera of the means of transport; obtaining road wetness information on the basis of the first signal; selecting a predefined set of parameters from a plurality of predefined sets of parameters as a function of the road wetness information; and performing an environment recognition on the basis of the second signal in conjunction with the predefined set of parameters.

A processing load in a case where a plurality of different sensors is used can be reduced. An information processing apparatus according to an embodiment includes: a recognition processing unit (15, 40b) configured to perform recognition processing for recognizing a target object by adding, to an output of a first sensor (23), region information that is generated according to object likelihood detected in a process of object recognition processing based on an output of a second sensor (21) different from the first sensor.

Sensor data is received from an array of sensors configured to capture one or more objects in an external environment of an autonomous vehicle. A first sensor group is selected from the array of sensors based on proximity data or environmental contexts. First sensor data from the first sensor group is prioritized for transmission based on the proximity data or environmental contexts.

Sensor data is received from an array of sensors configured to capture one or more objects in an external environment of an autonomous vehicle. A first sensor group is selected from the array of sensors based on proximity data or environmental contexts. First sensor data from the first sensor group is prioritized for transmission based on the proximity data or environmental contexts.

Disclosed is an obstacle detection system of a vehicle. The obstacle detection system includes a driving information unit configured to calculate driving position information of the vehicle, a determiner configured to anticipate whether or not the vehicle will enter a joining point where the vehicle meets a target road to be joined based on the driving position information calculated by the driving information unit, a sensing unit configured to sense obstacles located beside the vehicle, and a controller configured to change a sensing range of the sensing unit so as to detect an obstacle moving on the target road to be joined, when the determiner anticipates that the vehicle will enter the joining point.

An apparatus includes a processor configured to be disposed with a vehicle and a memory coupled to the processor. The memory stores instructions to cause the processor to receive, at least two of: radar data, camera data, lidar data, or sonar data. The sensor data is associated with a predefined region of a vicinity of the vehicle while the vehicle is traveling during a first time period. At least a portion of the vehicle is positioned within the predefined region during the first time period. The method also includes detecting that no other vehicle is present within the predefined region. An environment of the vehicle during the first time period is classified as one state from a set of states that includes at least one of dry, light rain, heavy rain, light snow, or heavy snow, based on at least two of the sensor data to produce an environment classification. An operational parameter of the vehicle based on the environment classification is modified.

An ultrasonic sensor 1000 has a transmission/reception processing circuit 100, and the transmission/reception processing circuit 100 has a burst signal transmission circuit 1 that generates and transmits burst signals S0, and a signal processing circuit 7 that processes reception signals received by a piezoelectric element 4. The signal processing circuit 7 verifies the reverberation frequency of the reverberation signals of ultrasonic signals (reception signals) reflected to the piezoelectric element 4 from a subject, and on the basis of the verified reverberation frequency and reverberation time of the reception signals, adjusts the frequency of the burst signals S0 to be substantially equal to the reverberation frequency, said burst signals being to be generated by the burst signal transmission circuit 1.