Methods and systems for monitoring use, determining risk, and pricing insurance policies for a vehicle having autonomous or semi-autonomous operation features are provided. In certain aspects, with the customer's permission, a computer-implemented method for updating an autonomous operation feature may be provided. An indication of a software update associated with the autonomous operation feature may be received, and several autonomous or semi-autonomous vehicles having the feature may be identified. The update may be installed within the several vehicles, such as via wireless communication. Also, a change in a risk level associated with the update to the autonomous operation feature may be determined, and an insurance discount may be determined or adjusted. As a result, an insurance discount may be provided to risk averse customers that affirmatively share their vehicle data with an insurance provider, and promptly and remotely receive new versions of software that operate autonomous vehicle safety features.

In one embodiment, a first set of driving statistics is measured and collected from an autonomous driving vehicle (ADV) at different points in time in response to various control commands while the ADV is driving in various driving environments. Based on the first set of driving statistics, a search is conducted in each of the load calibration tables to find a load calibration table having similar driving statistics. One of the load calibration tables is selected, which contains a second set of driving statistics that are most similar to the first set of driving statistics. A current load of the ADV is determined based on the selected load calibration table, for example, by designating the load associated with the selected load calibration table as the current load of the ADV. The load of the ADV can be utilized as a factor for generating subsequent control commands for the ADV.

A parking device mountable on a vehicle and capable of parking autonomously includes an autonomous-parking-command receiver, a vehicle-occupant detector, and a determination unit. The autonomous-parking-command receiver receives a parking command given by a user to park the vehicle. The vehicle-occupant detector detects whether a vehicle occupant is in the vehicle. The determination unit determines whether to permit the vehicle to park. In a case where the autonomous-parking-command receiver receives the parking command and the vehicle-occupant detector does not detect the vehicle occupant, the determination unit determines permits parking and allows the vehicle to park autonomously. In a case where the autonomous-parking-command receiver receives the parking command and the vehicle-occupant detector detects the vehicle occupant, the determination unit does not permit parking and forbids the vehicle to park autonomously by commanding the autonomous-parking-command receiver to cancel the reception of the parking command.

A method for providing an alert signal to a control unit of a vehicle for controlling driver intervention. The method comprises determining a set of present driving behavior data indicative of a present driving behavior in a present driving situation and retrieving a driving model indicative of expected driving behavior for the present driving situation. Further, a plurality of expected near future paths for the vehicle are predicted and an actual path is additionally determined. The set of present driving behavior data is mapped with the driving model. When a predetermined degree of deviation in the set of present driving behavior data compared to the driving model is found and the actual path deviates from the predicted expected paths, the alert signal is provided.

The vehicle controller performs gear position switch control in which a gear position of an automatic transmission set based on the automated drive control is changed to an upper-level gear position if the driver operates the accelerator pedal under the automated drive control.

A hybrid electric vehicle which may effectively determine a point in time of shift pattern change and a method of controlling a shift pattern therefor are disclosed. The method includes determining whether or not a request for shift pattern change is received, determining HEV mode related conditions, in response to a determination that the request for shift pattern change is received, and changing a shift pattern according to the request for shift pattern change, in response to a determination that the HEV mode related conditions are satisfied.

A system that determines a road surface profile based upon filter coefficient data from noise cancellation systems is disclosed. The system includes a filter coefficient monitoring module that is configured to receive a first set of filter coefficient data from an noise cancellation module. The system also includes a road surface profile module that is configured to receive an input representing a road surface type and generate a road surface profile based upon the road surface type and the first set of filter coefficient data and to store the road surface profile including a correspondence between the road surface type and the first set of filter coefficient data.

A method for detecting parasitic power circulation within a work vehicle may include controlling an operation of the work vehicle such that a transmission of the work vehicle has a first output speed and determining a first power value associated with power transmitted through a drive shaft of the work vehicle at the first output speed. The method may also include adjusting the operation of the work vehicle such that the transmission has a second output speed that differs from the first output speed and determining a second power value associated with power transmitted through the drive shaft at the second output speed. In addition, the method may include comparing the first and second power values to a predetermined relationship to determine whether the work vehicle is currently experiencing parasitic power circulation, wherein the predetermined relationship is associated with operation of the work vehicle without parasitic power circulation.

Examples described may enable provision of remote assistance for an autonomous vehicle. An example method includes a computing system operating by default in a first mode and periodically transitioning from operation in the first mode to operation in a second mode. In the first mode, the system may receive environment data provided by the vehicle and representing object(s) having a detection confidence below a threshold, where the detection confidence is indicative of a likelihood of correct identification of the object(s), and responsive to the object(s) having a confidence below the threshold, provide remote assistance data comprising an instruction to control the vehicle and/or a correct identification of the object(s). In the second mode, the system may trigger user interface display of remote assistor alertness data based on pre-stored data related to an environment in which the pre-stored data was acquired, and receive a response relating to the alertness data.

A parking assistance device includes: an obstacle detection unit that detects an obstacle; a separated distance determination unit that determines a separated distance between the obstacles when a plurality of the obstacles are detected; a target position determination unit that determines a target position in a guidance route; a route calculation unit that calculates the guidance route; and a control unit that guides a vehicle in accordance with the guidance route, wherein, when a second obstacle is detected in a second direction orthogonal to a first direction in which one or plurality of first obstacles extends or are lined up while being separated from each other and at a position separated from the first direction, the separated distance determination unit determines the separated distance between the first and second obstacles.