Disclosed herein an apparatus for assisting driving of a vehicle includes a camera installed in the vehicle, having a rear field of view of the vehicle, and obtaining image data; and a controller configured to process the image data; wherein the controller is configured to identify a rear object that interferes with a driving of the vehicle based on processing the image data, control at least one of a display device and an audio device of the vehicle to output a message for inducing a lane change of the vehicle based on an expected collision time remaining until a collision between the vehicle and the rear object being less than or equal to a first reference time, and control a steering device of the vehicle to apply a first torque for performing the lane change of the vehicle based on the expected collision time being less than or equal to a second reference time that is smaller than the first reference time.

A transportation vehicle with at least one first sensor for capturing environment data, at least one second sensor for capturing transportation vehicle data, a communication module for establishing a data connection with another transportation vehicle, a driving system for automated driving of the transportation vehicle, at least one output element for a visible/audible warning signal, and a control unit. The control unit determines a predicted trajectory of the transportation vehicle, determines a predicted path of the transportation vehicle and receives a predicted trajectory and vehicle geometry data of the other transportation vehicle via the data connection, determines a predicted path of the other transportation vehicle, determines a possible collision of the transportation vehicle with the other transportation vehicle, and in response to a possible collision, outputs a warning signal by the at least one output element and/or carries out an automated driving maneuver by the driving system.

An autonomous vehicle uses machine learning based models to predict hidden context attributes associated with traffic entities. The system uses the hidden context to predict behavior of people near a vehicle in a way that more closely resembles how human drivers would judge the behavior. The system determines an activation threshold value for a braking system of the autonomous vehicle based on the hidden context. The system modifies a world model based on the hidden context predicted by the machine learning based model. The autonomous vehicle is safely navigated, such that the vehicle stays at least a threshold distance away from traffic entities.

A method automatically controls an actuator of a control system of an automotive device. The method includes determining a reference trajectory, determining a position of the device with respect to the reference trajectory, acquiring a parameter relating to a force exerted by a driver on a manual control device of the control system, and calculating a controlling setpoint of the actuator. The controlling setpoint is calculated as a function of the parameter and of the position of the device with respect to the reference trajectory.

A control system and a method for vehicle control in geographical control zones is provided. The control system receives traffic information, including a plurality of image frames of a group of moving objects in a geographical control zone and generates a set of images frames of a first moving object of the group of moving objects based on application of a trained Neural Network (NN) model on the received traffic information. The generated set of image frames corresponds to a set of likely positions of the first moving object at a future time instant. The control system predicts the unsafe behavior of the first moving object based on the generated set of image frames and generates first control information, including an alternate route for a first vehicle in the geographical control zone based on the predicted unsafe behavior. The first vehicle is controlled based on the generated first control information.

An autonomous vehicle (AV) includes features that allows the AV to comply with applicable regulations and statues for performing safe driving operation. An example method for operating the AV includes determining a trajectory related information of a vehicle operating on a roadway on which the AV is operating; receiving sensor data of a first area that includes the vehicle; determining an additional trajectory related information for the AV by comparing the trajectory related information of the vehicle to a current trajectory related information of the AV, wherein the additional trajectory related information is based on a category to which the vehicle belongs, and wherein the additional trajectory related information allows the AV to maintain at least a distance between the AV and the vehicle; and causing the AV to operate in accordance with the additional trajectory related information.

A trajectory for an autonomous machine may be evaluated for safety based at least on determining whether the autonomous machine would be capable of occupying points of the trajectory in space-time while still being able to avoid a potential future collision with one or more objects in the environment through use of one or more safety procedures. To do so, a point of the trajectory may be evaluated for conflict based at least on a comparison between points in space-time that correspond to the autonomous machine executing the safety procedure(s) from the point and arrival times of the one or more objects to corresponding position(s) in the environment. A trajectory may be sampled and evaluated for conflicts at various points throughout the trajectory. Based on results of one or more evaluations, the trajectory may be scored, eliminated from consideration, or otherwise considered for control of the autonomous machine.

Disclosed are methods, systems, and non-transitory computer readable media that control an autonomous vehicle via at least two sensors. One aspect includes capturing an image of a scene ahead of the vehicle with a first sensor, identifying an object in the scene at a confidence level based on the image, determining the confidence level of the identifying is below a threshold, in response to the confidence level being below the threshold, directing a second sensor having a field of view smaller than the first sensor to generate a second image including a location of the identified object, further identifying the object in the scene based on the second image, controlling the vehicle based on the further identification of the object.

A vehicle control apparatus includes a recognizer which is configured to recognize a surrounding environment of a host vehicle and a driving controller which is configured to perform automated driving on the basis of a recognition result of the recognizer, wherein the driving controller is configured to perform passing control of causing the host vehicle to pass a preceding vehicle if at least one of a first condition according to a relative speed of the host vehicle with respect to the preceding vehicle and a second condition according to a type of the preceding vehicle is satisfied when the recognizer recognizes the preceding vehicle, and is configured to curb the passing control by changing at least one of the first condition and the second condition when a continuity of a first route on which the host vehicle is traveling decreases.

Provided is a preceding vehicle determining device including: a signal acquisition unit configured to acquire a signal from an object detection device; a border setting unit configured to set a border of a lane on which the own vehicle is traveling; a determination area setting unit configured to set a preceding vehicle determination area being an area forward of the own vehicle based on at least one piece of information out of vehicle type information, device type information, detection state information, or preceding vehicle information being information on a vehicle set as a preceding vehicle in previous processing, and based on the border set by the border setting unit; and a preceding vehicle determining unit configured to determine whether the another vehicle is to be set as the preceding vehicle based on a position of the another vehicle with respect to the preceding vehicle determination area.