In response to a DN operation that changes a shift position SP from a D position to an N position during forward drive in an HV drive mode, then an accelerator position Acc is not less than a reference accelerator position Aref (step S130), a mechanical neutral control is performed to provide a neutral state by releasing transmission of power between an intermediate shaft 32 and a driveshaft 36 by a multi-speed transmission 60 (step S230). An engine and two motors are then controlled to be rotated at rotation speeds close to rotation speeds Nedn, Nm1dn and Nm2dn at the time of DN operation (steps S250, S270 and S280).

To achieve an information processing apparatus and a mobile apparatus that individually calculate an inclination of the mobile apparatus itself and an inclination of a traveling surface. A measurement value of an air pressure sensor that measures an air pressure of a tire of the mobile apparatus is received, and the inclination of the mobile apparatus is calculated on the basis of the tire air pressure. Furthermore, a measurement value of an absolute pressure sensor attached to the mobile apparatus is received, and an angle of the traveling surface on which the mobile apparatus travels and a position of the mobile apparatus are calculated on the basis of a horizontal movement amount of the mobile apparatus and a vertical movement amount that is calculated on the basis of the measurement value of the absolute pressure sensor. Furthermore, a plurality of different state values such as inclination information of the traveling surface that changes with time transition is input to a Kalman filter, and state values that have already been acquired are updated on the basis of the newly input state values to generate and output the latest state values.

The pedestrian tracking system implemented in a host vehicle is disclosed. The system estimates trajectories of the host vehicle and the pedestrian based on factors of position and velocity of the host vehicle and parameters of position and velocity of the pedestrian. The trajectories of the host vehicle and the pedestrian are estimated to estimate a point of intersection of the host vehicle and the pedestrian. Further, the system estimates time to collision based on the estimated point of intersection and determines trajectory of the pedestrian in path of the host vehicle. Furthermore, the system assesses collision risk to select the pedestrian as a target and generates a deceleration actuation command to decelerate the host vehicle based on the selected target, which is provided to an automatic emergency braking (AEB) actuation unit.

A biased driving system and a biased driving method are capable of controlling biased driving of a vehicle in consideration of host vehicle location recognition accuracy, nearby vehicle risk, driving style, road curvature, and road shape. The biased driving system includes a control parameter creation unit configured to extract an object causing biasing of a host vehicle using converged object information, which is map information including location and speed of a vehicle around the host vehicle, to create an imaginary line of the extracted object by reflecting at least one of risk of a nearby vehicle, location recognition accuracy, driving style of a driver of the host vehicle, road curvature, or road shape, and to create a control parameter using the imaginary line.

A vehicle system is provided in a vehicle that is capable of running in an autonomous driving mode. The vehicle system includes: a sensor configured to acquire detection data indicating a surrounding environment of the vehicle; a generator configured to generate surrounding environment information indicating a surrounding environment of the vehicle, based on the detection data; and a use frequency setting module configured to set a use frequency for the sensor, based on predetermined information related to the vehicle or surrounding environment of the vehicle.

Disclosed is a vehicle allocation method of a server in an automated vehicle and highway system, which acquires a state information of a user, using a home Internet of Things (IoT), determines behavior information of the user, sets a going out stage related to an action sequence for going out of the user, based on the behavior information, transmits a vehicle allocation request message to the vehicle in order for the user to use the vehicle, based on the going out stage, whereby efficient vehicle allocation can be provided to users. One or more of an autonomous vehicle, a user terminal and a server may be connected to an artificial intelligence (AI) module, a drone (unmanned aerial vehicle, UAV) robot, an augmented reality (AR) apparatus, a virtual reality (VR) apparatus, a 5G service related apparatus or the like.

A vehicle control apparatus selects at least one oncoming vehicle and sets the selected oncoming vehicle as a control target vehicle when an own vehicle turns right or left in a traffic intersection, acquires a first index value which represents a collision probability, and executes a collision avoiding control when the first index value satisfies a predetermined condition. The vehicle control apparatus calculates a second index value which represents a degree of turning of the own vehicle, moves an area used to select the control target vehicle toward the own vehicle in an opposite direction to a turning direction of the own vehicle as the second index value increases, and selects, as the control target vehicle, the oncoming vehicle which has been in the area for a predetermined time threshold or more.

A method for determining a trajectory of an autonomous vehicle includes a first phase that is carried out while the trajectory of the vehicle is controlled manually. The first phase includes calculating a first theoretical trajectory of the vehicle, measuring a trajectory actually followed by the vehicle, and calculating a correction factor. Calculating the correction factor includes a comparison of the first theoretical trajectory with the trajectory actually followed. The method also includes a second phase that is carried out while the trajectory of the vehicle is controlled autonomously. The second phase includes calculating a second theoretical trajectory of the vehicle, and calculating a customised trajectory of the vehicle. Calculating the customised trajectory is based on the second theoretical trajectory and on the correction factor.

The invention relates to a method for improving the energy efficiency of a motor vehicle (1) comprising the steps of: detecting a driving situation; determining an efficient load range (23) for a power train (2) of the motor vehicle (1) depending on the detected driving situation; detecting a current load of the power train (2); and indicating the determined efficient load range (23) and the detected current load in a combined display device (4), so that a driver may selectively move the power train (2) of the motor vehicle (1) into the efficient load range (23).

The invention further relates to a motor vehicle (1) and a computer-readable medium comprising executable program code configured to execute the above method.

A driverless traffic management vehicle has a control system having a controller interfacing steering and drive interfaces for control of respective steering and drive subsystems of the vehicle. The vehicle also has an impact attenuator and actuator therefor for configuring the attenuator in deployed and stowed configurations. The control system comprises at least one driverless mode controller operably controlling the steering and drive interfaces for controlling the vehicle in at least one of follow mode, remote-control and autonomous driverless mode of operation. To control traffic, the vehicle may be driven to a roadside location and set in the at least one driverless mode of operation to control the steering and drive interfaces accordingly.