A vehicle control system includes a recognizer that recognizes a peripheral situation of a vehicle, a driving controller that automatically performs speed control and steering control of the vehicle on the basis of a recognition result of the recognizer, and a determiner that determines whether a predetermined condition indicating that automated parking is not adequate is satisfied when a user exits the vehicle. The driving controller causes the vehicle to start to travel from a stop state and stop at a parking lot in a case where it is determined by the determiner that the predetermined condition is not satisfied, and causes the vehicle not to start to travel from a stop state and stop at a parking lot in a case where it is determined by the determiner that the predetermined condition is satisfied.

A hybrid electric vehicle includes an intelligent vehicle controller, an electric motor, a battery, an internal combustion engine (ICE), and an electrical generator coupled to the ICE configured to provide electricity to the battery and the electric motor. The intelligent vehicle controller receives ICE power level shifting data from the electrical generator, ICE, battery, and electric motor. The intelligent vehicle controller determines a desirable torque and/or a desirable revolutions per minute (RPM) for the ICE based on the received ICE power level shifting data by utilizing an efficiency map that includes fuel efficiency contours and noise, vibration, and/or harshness (NVH) level lines for the hybrid electric vehicle. The intelligent vehicle controller may have first and second vehicle operation modes, and may derive first and a second desirable power levels for the ICE in the first and second operation modes, based on the ICE power level shifting data.

Disclosed embodiments include a method and apparatus for controlling system energy saving in an unmanned vehicle. In some embodiments, the method comprises: determining, via a sensing device and a high-precision map, whether the unmanned vehicle is in a stop-and-wait state; positioning the unmanned vehicle system in a standby state if the unmanned vehicle is in the stop-and-wait state. Some embodiments lower wear and loss of the unmanned vehicle system, improve the continued travel capacity of the unmanned vehicle and make the design of the unmanned vehicle more green and environment-friendly.

The present invention relates to a method of determining at least one area (ZON) of a road network reachable by a vehicle driving on the road network. The method is based on the use of a dynamic model (MOD) of the vehicle depending on the vehicle speed and acceleration, the construction of a line graph (GA) and a shortest path algorithm (ALG).

A method for determination of state information, especially describing a tribological state of a drive train of a motor vehicle, wherein the drive train comprises an electric machine as a first drive machine and a second drive machine, wherein upon fulfillment of a diagnostic condition the first drive machine is operated in an electrical idling mode, in which it is electrically separated from all current sources and current sinks and coupled to at least one of the wheels of the motor vehicle, and during the operation of the first drive machine in the electrical idling mode a performance measure is acquired for the performance of the second drive machine, while at least one of the wheels of the motor vehicle is driven by the second drive machine, after which the state information is determined in dependence on the performance measure and given reference information.

A vehicle controller includes: an engine controller configured to perform an IS control upon satisfaction of a predetermined stop condition and an engine restart control upon satisfaction of a predetermined restart condition; an HDC controller configured to perform, when the vehicle is traveling on a downhill road and a deceleration request according to an HDC control occurs, a target vehicle speed-based deceleration irrespective of brake operations by the driver; and an information acquisition part configured to acquire progress status information related to the engine restart control and including information on initiation and completion thereof. When an engine restart request according to the IS control and the deceleration request according to the HDC control occur in a temporally overlapping manner, while the engine controller performs the engine restart control in a prioritized manner, the HDC controller allows performing the target vehicle speed-based deceleration on the basis of the progress status information.

An evacuation control apparatus includes a decrease detecting unit, a rear monitoring unit, and an evacuation control unit. The decrease detecting unit detects decrease in a consciousness level of a driver of an own vehicle. The rear monitoring unit monitors a state behind the own vehicle. The evacuation control unit outputs control information for making the own vehicle perform an emergency evacuation based on monitoring results of the rear monitoring unit, when the decrease detecting unit detects decrease in the consciousness level of the driver.

Methods and systems are provided for managing torque arbitration for a hybrid powertrain. In one example, a method may include operating the hybrid powertrain over a predetermined route with a torque arbitration, and updating the torque arbitration based on a vehicle mass.

A hybrid electric vehicle includes an intelligent vehicle controller, an electric motor, a battery, an internal combustion engine (ICE), and an electrical generator coupled to the ICE configured to provide electricity to the battery and the electric motor. The intelligent vehicle controller receives ICE power level shifting data from the electrical generator, ICE, battery, and electric motor. The intelligent vehicle controller determines a desirable torque and/or a desirable revolutions per minute (RPM) for the ICE based on the received ICE power level shifting data by utilizing an efficiency map that includes fuel efficiency contours and noise, vibration, and/or harshness (NVH) level lines for the hybrid electric vehicle. The intelligent vehicle controller may have first and second vehicle operation modes, and may derive first and a second desirable power levels for the ICE in the first and second operation modes, based on the ICE power level shifting data.

Method and apparatus are disclosed for lead vehicle monitoring for adaptive cruise control. An example vehicle includes a communication module for V2V communication, a camera, a sensor, and an adaptive cruise control unit. The adaptive cruise control unit is to determine an acceleration oscillation value of a lead vehicle based upon measurements collected via at least one of the camera and the sensor and send, via the communication module, an instruction to the lead vehicle to activate cruise control responsive to determining the acceleration oscillation value exceeds a threshold.