A device is configured to classify data. Its operation involves providing (210) data samples including one or more of: image data, radar data, acoustic data, and/or lidar data to a processing unit. The data samples include at least one test sample, including positive samples and negative samples. Each positive sample has been determined to contain data relating to at least one object to be detected including at least one pedestrian, car, vehicle, truck or bicycle. Each negative sample has been determined not to contain data relating to the at least one object to be detected. These determinations regarding the positive samples and the negative samples are provided as input data, validated by a human operator, and/or provided by the device itself through a learning algorithm. A first plurality of groups is generated (220) by the processing unit implementing an artificial neural network, wherein at least some of the first plurality of groups are assigned a weighting factor. Each group of the first plurality of groups is populated (230) by the processing unit implementing the artificial neural network with a different at least one of the plurality of negative samples based on a different feature of sample data similarity for each group, which involves processing the negative samples to determine a number of different features of sample data similarity in order to populate different groups with negative samples that share or substantially share that or a similar feature, wherein at least one of the groups of the first plurality of groups contains at least two negative samples. It is determined (240) by the processing unit implementing the artificial neural network whether the at least one test sample contains data relating to the at least one object based on the plurality of the positive samples and the first plurality of groups. The artificial neural network implements the learning algorithm.

A method for controlling a first vehicle, travelling on a road, that has a second vehicle travelling ahead of it, includes the steps of: scanning the second vehicle from the first vehicle by use of multiple sensors; providing individual determinations, each on the basis of scans by only one of the sensors, concerning whether the first and the second vehicle are travelling in the same lane of the road, wherein each sensor has an associated determination certainty; and providing a collision warning if a product of the determination certainties is below a predetermined threshold value.

An apparatus including a capture device and a processor. The capture device may be configured to generate pixel data corresponding to an exterior view from a vehicle. The processor may be configured to generate video frames from the pixel data, perform computer vision operations on the video frames to detect objects in the video frames and determine characteristics of the objects, detect a change in orientation of the vehicle at a first time, analyze the characteristics of the objects at a second time to determine a cause of the change in orientation of the vehicle and generate annotations for the video frames that comprise the objects determined to have caused the change in orientation of the vehicle. The second time may be earlier than the first time.

The present disclosure described herein, in general, relates to a system 500 for controlling headlamps of a vehicle. The system 500 may comprise a signal processing unit 509, a relay circuit 401, a switch 302 and a user device 407. The user device 407 comprises a GPS tracker 408-A, an output unit 409, a processor 408-B and a memory 408-C. The system comprises comparing one or more parameters with the predefined threshold value, notifying information based upon the one or more parameters, instructing the user to change the status of the headlamp using the switch 302 based upon the comparison of the one or more parameters with the predefined threshold value and controlling the status of the headlamps upon receiving command by the user based upon the instructions or automatically operating the relay circuit 401 based upon the received signals.

A network system provides interventions to providers to reduce the likelihood that its users will experience safety incidents. The providers provide service to the users such as transportation. Providers who are safe and have positive interpersonal behavior may be perceived by users as high quality providers. However, other providers may be more prone to cause safety incidents. A machine learning model is trained using features derived from service received by users of the network system. Randomized experiments and trained models predict the effectiveness of various interventions on a provider based on characteristics of the provider and the feedback received for the provider. As interventions are sent to providers, the change in feedback can indicate whether the intervention was effective. By providing messages proactively, the network system may prevent future safety incidents from occurring.

A method for operating a brake system of a vehicle in a maintenance mode and in a normal mode includes providing a brake pressure in the brake system in the normal mode using a brake pressure generator. The method further includes preventing a provision of a brake pressure by the brake pressure generator in the maintenance mode.

A method for operating a brake system of a vehicle in a maintenance mode and in a normal mode includes providing a brake pressure in the brake system in the normal mode using a brake pressure generator. The method further includes preventing a provision of a brake pressure by the brake pressure generator in the maintenance mode.

A vehicle-mounted equipment control device includes a controller configured to cause equipment of any of a headlight, a wiper, and an air-conditioning device to continue a visual securing operation for securing visibility of a driver of a vehicle even after driving control of the vehicle is switched from automated driving control to manual driving control regardless of an operation mode of the equipment specified by an operation switch for setting an operation of the equipment when an operation mode executed by the equipment immediately before driving control of the vehicle is switched from automated driving control to manual driving control is an operation mode corresponding to the visual securing operation.

A system and method for providing point of interest related notifications within a vehicle that include receiving sensor data associated with an opening of at least one vehicle window of the vehicle. The system and method also include storing a first geo-location of the vehicle based on the sensor data and determining if a subsequent geo-location of the vehicle is within a predetermined vicinity of at least one point of interest. The system and method further include providing at least one point of interest related notification associated with the at least one point of interest if it is determined that the subsequent geo-location of the vehicle is within the predetermined vicinity of the at least one point of interest.

A system and method for providing point of interest related notifications within a vehicle that include receiving sensor data associated with an opening of at least one vehicle window of the vehicle. The system and method also include storing a first geo-location of the vehicle based on the sensor data and determining if a subsequent geo-location of the vehicle is within a predetermined vicinity of at least one point of interest. The system and method further include providing at least one point of interest related notification associated with the at least one point of interest if it is determined that the subsequent geo-location of the vehicle is within the predetermined vicinity of the at least one point of interest.