A system receives confirmation that a vehicle has accepted automatic control imposition for a drive within a geo-fenced boundary. The system tracks travel of a plurality of vehicles, including the vehicle, within the geo-fenced boundary. The system may determine that the vehicle has a threshold likelihood of encountering at least one of another vehicle or a boundary of the geo-fence at a threshold speed or above and responsive to the determination, impose automatic control on the vehicle, including at least one of controlled braking or speed limiting.

Vehicle behavioral monitoring includes determining a measure of distraction of the operator of a target vehicle, characterizing the type or category of distraction, determining level of risk that the target vehicle poses, and invoking various responses including host vehicle notifications and evasive actions and external notification and information sharing.

A system for navigating a vehicle automatically from a current location to a destination location without a human operator is provided. The system of the vehicle includes a global positioning system (GPS) for identifying a vehicle location and a communications system for communicating with a server of a cloud system. The server is configured to identify that the vehicle location is near or at a parking location. The communications system is configured to receive mapping data for the parking location from the server, and the mapping data is at least in part used to find a path at the parking location to avoid a collision of the vehicle with at least one physical object when the vehicle is automatically moved at the parking location. The mapping data is processed by electronics of the vehicle so that when the vehicle is automatically moved collision with the at least one physical object is avoided and the electronics of the vehicle is configured to process a combination of sensor data obtained by sensors of the vehicle. The processing of the sensor data uses image data obtained from one or more cameras and light data obtained from one or more optical sensors.

This disclosure provides methods, devices and systems for a vehicle user equipment (VUE) to obtain extrinsic information about an object or location. The VUE may transmit a request for information about the object or the location to a road side unit (RSU). The RSU may receive the request and determine a set of extrinsic information for the first UE regarding the object or the location based on a set of information from one or more other UEs. The extrinsic information includes information that is not provided by the VUE. The RSU may transmit the set of extrinsic information to the VUE. The VUE may determine whether to accept a feature of the object or the location in the extrinsic information based on the set of extrinsic information and a set of intrinsic information detected by the VUE, The VUE may select an autonomous driving action based on the accepted feature.

In a drive assist system, a map data acquiring section acquires at least one of a driver's operation ability and a load of a vehicle. An adjustment section determines an assist control amount as a control parameter of drive assist for the vehicle so that a degree of the driver's operation is increased according to reduction of the driver's operation ability or increasing of the load of the vehicle. An assist control amount calculation section transmits the assist control amount to a steering motor and a notification section so as to execute the drive assist for the vehicle.

An information processing device (20) includes a route acquisition unit (202) and an automatic driving section determination unit (204). The route acquisition unit (202) acquires route information indicating a moving route of a mobile body. The automatic driving section determination unit (204) acquires adaptation coefficients for a plurality of sections included in the moving route indicated by the route information, with reference to an adaptation coefficient storage unit (206) that stores automatic driving adaptation coefficients set for the respective sections. Further, the automatic driving section determination unit (204) determines the automatic driving sections of the mobile body in the moving route, based on the acquired adaptation coefficients.

Specifications are input, comprising: a plurality of lanes in an environment for a controlled system; a plurality of lane maneuvers associated with the plurality of lanes; a plurality of lane subconditions associated with the controlled system; and a rule set comprising a plurality of rules, wherein a rule in the rule set specifies a rule condition and a rule action to take when the rule condition is satisfied, wherein the rule condition comprises a corresponding set of lane subconditions, and wherein the rule action comprises a corresponding lane maneuver. The controlled system is automatically navigated dynamically, at least in part by: monitoring the plurality of lane subconditions; evaluating rule conditions associated with the plurality of rules in the rule set to determine one or more rules whose corresponding rule conditions has been met; and executing one or more lane maneuvers that correspond to the one or more determined rules.

The disclosure provides an early notification system to alert a driver of an approaching unsafe autonomous or semi-autonomous driving zone so that a driver may switch vehicle to a non-autonomous driving mode and navigate safely through the identified location. In response, to a determination of an upcoming unsafe autonomous or semi-autonomous driving zone, the driver or system may take appropriate actions in response to the early notification.

Methods and systems are provided for selectively engaging an electric machine to an electric axle of a vehicle. In one example, a method may include engaging or disengaging the electric machine to a differential of the electric-axle by adjusting pressure in a piston coupled to an axle shaft of the electric-axle via a disconnect clutch.

A method for operating a vehicle includes carrying out a lane-keeping control of the vehicle along a course of a lane travelled in by the vehicle. When lane markings are detected, the course of the lane is determined on a basis of detected lane markings. When lane markings are not detected, the course of the lane is determined in a mapped-based manner on a basis of data from a digital map where a rough localization of the vehicle in the digital map and a fine localization of the vehicle in the digital map is performed.