The present invention relates to a method for detecting objects in a first vehicle detection field (10a), which comprises an interior (12) and an outer region (14) of a vehicle (16), by means of a first sensor unit (18a) of the vehicle (16). The method comprises the following steps: Detecting an object in the outer region (14) of the first vehicle detection field (10a) with the first sensor unit (18a) as first detection data; detecting an object in the interior (12) of the first vehicle detection field (10a) with the first sensor unit (18a) as second detection data; and processing the first and second detection data in a computing unit. The invention also relates to a corresponding detection system.

An in-car safety system includes: a detecting device, a processor, an in-car equipment and a piezoelectric device. The detecting device is disposed on a car. The processor is disposed in the car. The processor is electrically connected to the detecting device. The processor is configured to receive a detecting signal transmitted by the detecting device and transmit an electrical signal in accordance with the detecting signal. The in-car equipment is disposed in the car. The piezoelectric device is disposed on the in-car equipment. The piezoelectric device is electrically connected to the processor. The piezoelectric device is configured to receive the electrical signal and generate a vibration to the in-car equipment in accordance with the electrical signal.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, that obtain scene features in an environment that includes an autonomous vehicle, a first target agent, and a second target agent, and determines whether the first target agent is an emergency vehicle that is active at a current time point. In response to determining that the first target agent is an emergency vehicle that is active at the current time point, an input is generated from the scene features. The input can characterize the scene and indicate that the first target agent is an emergency vehicle that is active at the current time point. Also in response, the input can be processed using a machine learning model that is configured to generate a trajectory prediction output for the second target agent that characterizes predicted future behavior of the second target agent after the current time point.

An autonomous vehicle configured for active sensing may also be configured to weigh expected information gains from active-sensing actions against risk costs associated with the active-sensing actions. An example method involves: (a) receiving information from one or more sensors of an autonomous vehicle, (b) determining a risk-cost framework that indicates risk costs across a range of degrees to which an active-sensing action can be performed, wherein the active-sensing action comprises an action that is performable by the autonomous vehicle to potentially improve the information upon which at least one of the control processes for the autonomous vehicle is based, (c) determining an information-improvement expectation framework across the range of degrees to which the active-sensing action can be performed, and (d) applying the risk-cost framework and the information-improvement expectation framework to determine a degree to which the active-sensing action should be performed.

Methods and apparatus for providing dynamically adjusted radiated signals are disclosed. In one aspect, a method of detecting one or more objects in a path of travel of a vehicle may include generating a laser with radiated power. The method may further include emitting the laser in a direction of travel of the vehicle and receiving one or more reflections of the emitted laser reflected from the one or more objects located in the direction of travel of the vehicle. The method may also further include generating a signal indicating that the one or more objects are in a path of the vehicle based on the received one or more reflections. The method may also include dynamically adjusting the radiated power of the laser based on an input corresponding to one or more of (i) a current speed of the vehicle or (ii) a current position of the vehicle.

A vehicle with a road surface condition detector includes: a vehicle body configured to have one or more passengers; front and rear wheels configured to move the vehicle body; and a road surface condition detector configured to detect road surface conditions in front of the front and rear wheels, wherein the road surface condition detector includes front-wheel road surface condition detectors configured to detect road surface conditions in front of the front wheels and rear-wheel road surface condition detectors configured to detect road surface conditions in front of the rear wheels, and the rear-wheel road surface condition detectors detect areas located outer in a vehicle width direction than ends of detection areas detected by the front-wheel road surface condition detectors.

A method for assisting in the driving of a vehicle on a fast road with carriageways separated by a safety rail in which the presence of the safety rail is detected is disclosed. The safety rail is modelled from measurements performed continuously by at least one laser scanner sensor mounted on the motor vehicle, with the determination of a confidence index associated with the detection by the laser scanner sensor, an automatic driving mode is activated when the confidence index I.sub.CONF is above a confidence threshold. This mode is maintained as long as a current confidence index associated with the detection is above the confidence threshold, and this mode is deactivated when the current confidence index passes below said confidence threshold. The density of traffic in front of the motor vehicle is estimated from images captured by an embedded camera.

A method for determining a trajectory of a motor vehicle for a driver assistance function includes: determining an initial trajectory of the motor vehicle on a road; setting an upper threshold for the lateral acceleration of the motor vehicle; detecting data of the road surface in the direction of travel ahead of the motor vehicle with at least one sensor; determining the vertical profile of the road surface of a plurality of paths running parallel to each other in the direction of travel ahead of the motor vehicle by using the data; determining, when the vertical profile of at least one of the paths indicates a pothole, a lateral deviation from the initial trajectory for which a limit value does not exceed the set upper threshold for the lateral acceleration, wherein the road boundary is not exceeded; and outputting an adjusted trajectory by using the determined lateral deviation.

A method of operating a traffic management system comprises receiving data from a vehicle indicating a traffic state, estimating a future time at which the vehicle will receive driving instructions transmitted by the traffic management system, predicting a future traffic state at the estimated future time, determining the driving instructions for the vehicle based on the predicted future traffic state, and transmitting the driving instructions to the vehicle.

A vehicle with a road surface condition detector includes: a vehicle body configured to have one or more passengers; front and rear wheels configured to move the vehicle body; and a road surface condition detector configured to detect road surface conditions in front of the front and rear wheels, wherein the road surface condition detector includes front-wheel road surface condition detectors configured to detect road surface conditions in front of the front wheels and rear-wheel road surface condition detectors configured to detect road surface conditions in front of the rear wheels, and the rear-wheel road surface condition detectors detect areas located outer in a vehicle width direction than ends of detection areas detected by the front-wheel road surface condition detectors.