A vehicular personalized adaptive cruise control system includes a forward-viewing camera viewing forward through a windshield of a vehicle, and an electronic control unit disposed at the vehicle. When the vehicle is operating in an adaptive cruise control mode, the system controls driving of the vehicle. When the equipped vehicle is not operating in the adaptive cruise control mode, a driver present in the vehicle drives the vehicle. The system identifies the driver via processing of image data captured by a cabin monitoring camera. When the identified driver drives the vehicle with the vehicle not operating in the adaptive cruise control mode, the system determines and stores personalized parameters for the identified driver. With the identified driver present in the vehicle, and when the vehicle is operating in the adaptive cruise control mode, the system uses the determined personalized parameters.

Aspects of the present invention relate to a control system 208 and method for controlling energy management of a traction battery 200 of a hybrid electric vehicle 10, the traction battery 200 configured to power at least one traction motor 212 coupled to an electric-only axle 213 of the vehicle 10 to provide all-wheel drive, the control system 208 comprising one or more electronic controllers 300, the one or more electronic controllers 300 configured to: determine a change of terrain mode and/or type for the vehicle and/or determine an increase in loading of the vehicle 10; select an energy management control strategy for the traction battery 200 of the vehicle 10 in dependence on the determined change in terrain mode and/or type and/or the determined increase in loading of the vehicle 10, wherein the traction battery 200 is configured to supply power to the at least one traction motor 212 to provide torque to the electric-only axle 213 of the vehicle 10 to enable the vehicle 10 to operate in an all-wheel drive mode, wherein selecting an energy management control strategy of the vehicle 10 comprises at least one of: selecting or adjusting a charge sustain set point 30 for the traction battery 200; and changing energy generation to recharge the traction battery 200.

An autonomous navigation system may autonomously navigate a vehicle through an environment in which one or more non-solid objects, including gaseous and/or liquid objects, are located. Sensors, including sensors which can detect chemical substances in a region of the environment, may detect non-solid objects independently of an opacity of the objects. Non-solid objects may be determined to present an obstacle or interference based on determined chemical composition, size, position, velocity, concentration, etc. of the objects. The vehicle may be autonomously navigated to avoid non-solid objects based on positions, trajectories, etc. of the non-solid objects. The vehicle may be navigated according to avoidance driving parameters to avoid non-solid objects, and a navigation system may characterize a non-solid object as a solid object having dimensions and position which encompasses the non-solid object, so that the vehicle is navigated in avoidance of non-solid objects as if the non-solid objects were solid.

A traveling body includes a range sensor and circuitry. The range sensor is disposed on a front face of the traveling body in a traveling direction in which the traveling body travels on a road surface and disposed obliquely downward at an inclination angle relative to the road surface. The circuitry determines presence of a continuous obstacle in a case where measurement results of a plurality of planes scanned by the range sensor include a plurality of feature values indicating unevenness relative to the road surface similar to each other. The circuitry generates an obstacle map of a front region of the traveling body not scanned by the range sensor, based on sequential feature information indicating that a predetermined number of feature values indicating the unevenness are sequentially present and controls the traveling body to travel on the road surface based on the obstacle map.

A driverless vehicle system comprises a processor that is configured to communicate information related to attributes of a focus autonomous vehicle (FAV) to an other peer vehicle (PV) and/or a central repository system (CRS). The processor is further configured to communicate information about a corrective action by at least one of the FAV and a previously contacted vehicle to the CRS or to a further peer vehicle that is within a predefined region.

A method for influencing driving dynamics of a vehicle, in which the driving dynamics are influenced as a function of parameters allocated to a selected driving dynamics mode when the driving dynamics mode is activated, and the driving dynamics are influenced as a function of road state information representing a road state in the region of the vehicle when an automatic mode is activated.

A road-surface-condition estimation device is configured by a tire-side device and a vehicle-side device so as to grasp a road surface condition based on road surface condition data transmitted from a tire-side device. As a result, the road surface condition or a road surface μ of a traveling road surface of a vehicle can be accurately detected, and a more accurate lane keeping control can be performed according to the detection result. In particular, since the tire-side device estimates the road surface condition by detecting the vibration of a ground contact surface of the tire, the road surface condition can be estimated more accurately. Therefore, the more accurate lane keeping control can be performed.

A vehicle control system to be mounted in a hybrid electric vehicle includes an engine, a center differential that includes a front-wheel-side output portion and a rear-wheel-side output portion and distributes torque outputted from the engine to a front wheel and a rear wheel, a limited slip differential mechanism that limits a differential between the front-wheel-side output portion and the rear-wheel-side output portion, and a motor disposed in a drive-power transferring system that transfers drive power from the rear-wheel-side output portion to the rear wheel. The vehicle control system includes a processor. When the hybrid electric vehicle is switched from a first traveling mode to a second traveling mode, the processor stops the engine while causing the limited slip differential mechanism to limit the differential between the front-wheel-side output portion and the rear-wheel-side output portion.

A vehicle is adapted to sense a condition of use in which a maximum speed control speed is reduced. The condition of use may be indicated by a sensor of the vehicle, or selected according to the kind of terrain across which the vehicle is travelling. Selection of terrain type may be manual or automatic, and may enable a selection of sensors appropriate to the terrain type. A vehicle driver may select a speed control speed lower than the permitted maximum.

An apparatus and a method for estimating a road surface friction coefficient relate to an apparatus of estimating a road surface friction coefficient including an additional power control module that arbitrarily adds a braking force, which causes a wheel speed difference, to an axle of the vehicle to which the braking force is applied, and together adds a driving force that cancels the braking force to an axle of the vehicle to which the driving force is applied, when it is determined that a driving state of the vehicle is an inertial driving state, and a road surface friction coefficient estimation module that estimates the road surface friction coefficient by the wheel speed difference caused by a newly added braking force.