A method for controlling a vehicle controllable in a highly/fully automated manner. The method includes: ascertaining a malfunction of a vehicle control unit of the vehicle, the vehicle control unit being designed for a highly automated and/or fully automated control of the vehicle; switching from the vehicle control unit to an emergency control unit, the emergency control unit being based on a driver assistance system and designed for maximally a conditionally automatic control of the vehicle, and the emergency control unit being configured to effectuate a control of the vehicle in the event of a malfunction of the vehicle control unit; executing the emergency control of the vehicle; and controlling the vehicle with the aid of the emergency control unit based on surroundings sensor data of the vehicle.

A manager is installed in a vehicle. The manager includes: an accepting unit that accepts, from a plurality of advanced driver assistance system applications, a plurality of kinematic plans including first information that is information representing lateral-direction motion of the vehicle; an arbitration unit that performs arbitration of the kinematic plans; a first output unit that distributes a motion request based on a result of arbitration performed by the arbitration unit to at least one of a plurality of actuator systems; and a second output unit that outputs second information used for generating the first information to at least one of the ADAS applications.

Embodiments of the present disclosure relate to generating velocity profiles for an autonomous vehicle (101). An ECU (107) of the autonomous vehicle (101) receives road information from one or more sensors (106) associated with the autonomous vehicle (101). One or more parameters related to smooth movement of the autonomous vehicle on the road is determined from the road information. Further, a first velocity profile is produced using an AI model and a second velocity profile is produced using a hierarchical model, based on the one or more parameters. Furthermore, one of the first and the second velocity profile is selected by comparing the first and the second velocity profiles. The selected velocity profile has a lower value of velocity value compared to the other velocity profile. The selected velocity profile is provided to the autonomous vehicle (101) for navigating on the road (102) smoothly.

A memory device includes a first memory area including a first memory cell array having a plurality of first memory cells each for storing N-bit data according to an M-bit data access scheme, where N is a natural number, and a first peripheral circuit for controlling the first memory cells and disposed below the first memory cell array, a second memory area including a second memory cell array having a plurality of second memory cells each for storing M-bit data according to an M-bit data access scheme, where M is a natural number greater than N, and a second peripheral circuit for controlling the second memory cells and disposed below the second memory cell array, the first memory area and the second memory area are included in a single semiconductor chip and share an input and output interface, and a controller configured to generate calculation data by applying a weight stored in the first memory area to sensing data in response to receiving the sensing data obtained by an external sensor, and store the calculation data in one of the first memory area or the second memory area according to the weight.

An advanced driver assistance system is provided. The advanced driver assistance system of the vehicle comprises a communicator configured to communicate with an obstacle detector configured to detect an obstacle; and a processor configured to determine a riding intention of a user in response to reception of a door unlocking instruction, obtain location information of other vehicles based on obstacle information detected by the obstacle detector in response to determining that the riding intention exists, determine a collision possibility with other vehicles based on the location information of other vehicles, and control output of notification information for a collision in response to determining that the collision possibility exists.

The present disclosure provides a method, system, and apparatus for processing parking and a vehicle controller, and relates to the field of intelligent transportation technology, specifically to the field of automated parking technology. The method is executed by a parking system deployed on a vehicle controller, the parking system including a perception module and other modules except the perception module; the perception module being deployed on a first operating system in the vehicle controller; and the other modules being deployed on a second operating system in the vehicle controller; the method includes: processing an image collected by an image collector through the perception module to obtain perception result data; and controlling a vehicle based on the perception result data obtained from the perception module by the other modules.

A method may include obtaining one or more inputs in which each of the inputs describes at least one of: a state of an autonomous vehicle (AV) or a state of an object; and identifying a prediction context of the AV based on the inputs. The method may also include determining a relevancy of each object of a plurality of objects to the AV in relation to the prediction context; and outputting a set of relevant objects based on the relevancy determination for each of the plurality of objects. Another method may include obtaining a set of objects designated as relevant to operation of an AV; selecting a trajectory prediction approach for a given object based on context of the AV and characteristics of the given object; predicting a trajectory of the given object using the selected trajectory prediction approach; and outputting the given object and the predicted trajectory.

Disclosed is a vehicle path control apparatus including a memory provided to store danger driving vehicle data, a communication device provided to receive road information from an external server, and a processor configured to identify a danger driving vehicle driving on a road based on the road information and the danger driving vehicle data, select an unmanned vehicle driving within a preset distance from the danger driving vehicle based on the road information, generate a driving path of the unmanned vehicle for obstructing a course of the danger driving vehicle based on an expected path of the danger driving vehicle, and control the communication device to transmit information on the driving path to the unmanned vehicle.

A vehicle sensor data processing method and system are provided. The method includes: a vehicle sensor data processing system processes and fuses, by using a plurality of levels of control units, a signal sensed by a sensor, and a higher-level control unit makes a control decision based on received data of a plurality of types or a plurality of processing levels. In addition, a priority of a sensor may be further configured based on a vehicle function that needs to be implemented by the system, thereby implementing more stable and reliable vehicle control and ensuring safe driving while satisfying a delay requirement.

Provided are an intelligent parking method and apparatus, relating to the technical field of vehicles. The method comprises: determining a target parking route from at least one pre-stored parking route; determining a target position point in the target parking route closest to a vehicle; sending a prompt message for driving the vehicle to the target position point to a driver of the vehicle when a current position point of the vehicle and the target position point satisfy a proximity matching condition; and when the vehicle drives to the target position point, controlling the vehicle to park according to the target parking route from the target position point. Thus, the driver merely needs to drive the vehicle to a vicinity of the target parking route, and the vehicle may perform intelligent parking and may complete intelligent parking at a longer distance.