A Scalable service-Oriented MiddlewarE over IP (SOME/IP)-based debug system and method are provided. The SOME/IP-based debug system includes: a debug device configured to determine a debug instruction based on an input of a user; and a plurality of vehicle-mounted ECUs, where each of the vehicle-mounted ECUs includes a lower debug service configured to establish an SOME/IP communication connection with the debug device, receive the debug instruction via the SOME/IP communication connection, and execute a corresponding debug action based on the debug instruction. According to the technical solution of the present disclosure, debugging functions of vehicle-mounted ECUs can be implemented.

This disclosure describes systems and methods for training a neural network with a training data set including data items labeled at different granularities. During training, each item within the training data set can be fed through the neural network. For items with labels of a higher granularity, weights of the network can be adjusted based on a comparison between the output of the network and the label of the item. For items with labels of a lower granularity, an output of the network can be fed through a conversion function that convers the output from the higher granularity to the lower granularity. The weights of the network can then be adjusted based on a comparison between the converted output and the label of the item.

Devices, systems, and methods for a vehicular safety system in autonomous vehicles are described. An example method for safely controlling a vehicle includes selecting, based on a first control command from a first vehicle control unit, an operating mode of the vehicle, and transmitting, based on the selecting, the operating mode to an autonomous driving system, wherein the first control command is generated based on input from a first plurality of sensors, and wherein the operating mode corresponds to one of (a) a default operating mode, (b) a minimal risk condition mode of a first type that configures the vehicle to pull over to a nearest pre-designated safety location, (c) a minimal risk condition mode of a second type that configures the vehicle to immediately stop in a current lane, or (d) a minimal risk condition mode of a third type that configures the vehicle to come to a gentle stop.

This drive assistance device comprises an ACC unit, an abnormality detection unit for detecting an abnormality from a detector used to perform ACC, and a vehicle stop control unit for performing control to stop an ego vehicle when an abnormality is detected by the abnormality detection unit and an inter-vehicle distance to a preceding vehicle satisfies a certain condition.

A control method and system to control a pair of electric motors driving a vehicle. The steps provided for are: determining, in a control cycle N and by means of a first processing core, for a first electric motor, a first electric current target based on a first torque or speed target; determining, in the control cycle N and by means of a second processing core, for a second electric motor, a second electric current target based on a second torque or speed target; controlling, in the control cycle N and by means of the first processing core, a first electronic power converter connected to the first electric motor so as to pursue the first electric current target; and controlling, in the control cycle N and by means of the second processing core, a second electronic power converter connected to the second electric motor so as to pursue the second electric current target.

An information processing apparatus detects occurrence of a request to switch to manual driving during autonomous driving control of a first vehicle, acquires an utterance of a driver in a case where there is occurrence of the request to switch to manual driving, and presents, to the driver, a part of an explanation about a reason for occurrence of the request to switch to manual driving according to the utterance of the driver.

A fault diagnosis method and a fault diagnosis apparatus for a vehicle speed measurement apparatus. The method includes: obtaining a first vehicle speed measured by the speed measurement apparatus; obtaining reference information of a static reference object at N moments, where N is an integer greater than 1, and the reference information includes information about a location relationship of the static reference object relative to a vehicle in which the speed measurement apparatus is located at each of the N moments; calculating a second vehicle speed based on the reference information; and determining, based on the first vehicle speed and the second vehicle speed, whether the speed measurement apparatus is faulty.

A method for processing sensor data in a system that includes multiple sensors for detecting at least a subarea of surroundings around the system. The method includes at least the following steps: a) reading in sensor data detected at least partially in parallel, b) checking whether an at least partial impairment of the detection by the respective sensor may be established for one or for multiple of the sensors on the basis of the read-in sensor data, c) adapting the use of the sensor data, taking the check from step b) into account.

An integrated control apparatus for in-wheel system vehicle is provided. The apparatus includes a shift button for a shift control and a dial for a steering control which are assembled integrally to each other to form one integrated component. The apparatus provides a driver with vehicle information through an operation of the dial when the steering control is not performed, and eliminates a risk of accidents occurring due to a control error by configuring a shift control manner and a steering control manner to be different from each other.

Systems, methods and apparatus of recordation of vehicle data associated with errant vehicle behavior. For example, a vehicle includes: sensors configured to generate sensor data; control elements configured to generate control signals to be applied to the vehicle in response to user interactions with the control elements; electronic control units configured to provide status data in operations of the electronic control units; and a data storage device. The data storage device is configured to receive input data including the sensor data, the control signals and the status data, store the input data in a cyclic way in an input partition over time, generate a classification of errant behavior based on the input data and using an artificial neural network, and preserve a portion of the input data associated with the classification of errant behavior.