Vehicle environment data about operation of a plurality of vehicles and vehicle component data for a vehicle component is input into a machine learning program to obtain a transfer function that correlates vehicle environment data to vehicle component data within a specified range of vehicle component parameters. A first event is identified by determining that a datum in the vehicle component data is outside the specified range. A predictive damage model of a vehicle component is updated based on the first event. A virtual parameter of a component model is adjusted based on output from the predictive damage model.

This disclosure relates to a system and method for transitioning vehicle control between autonomous operation and manual operation. The system includes sensors configured to generate output signals conveying information related to the vehicle and its operation. During autonomous vehicle operation, the system gauges the level of responsiveness of a vehicle operator through challenges and corresponding responses. The system determines when to present a challenge to the vehicle operator based on internal and external factors. If necessary, the system will transition from an autonomous operation mode to a manual operation mode.

A driving control method comprises: acquiring a destination of a vehicle; referring to a first map that includes identification information of a travel lane and a second map that does not include the identification information of the travel lane; calculating a route from a current position of the vehicle to the destination; when traveling along a first route included in the route and belonging to the first map, setting first driving control, while when traveling along a second route included in the route and belonging to the second map, setting second driving control with a lower level of autonomous driving than that of the first driving control; and creating a driving plan for the vehicle to travel along the route with contents of the set driving control. A driving control apparatus is based on the method.

A method for determining a demand for processing resources for carrying out processing of data for at least partly automated guidance of a motor vehicle. Provision is made to adapt available processing resources for carrying out data processing to a determined demand for processing resources. An apparatus, a computer system, a computer program, and a machine-readable storage medium are also described.

A behavior prediction apparatus specifies a first object that affects a behavior of a vehicle from objects present around the vehicle. The behavior prediction apparatus performs a prediction process of extracting a second object that affects a behavior of the first object among a plurality of objects present around the first object and predicting a behavior. The behavior prediction apparatus sets the extracted second object as a new first object, and performs a prediction process of extracting a new second object affecting the behavior of the new first object and predicting the behavior. The behavior prediction apparatus repeats the prediction process by a predetermined number of times. The behavior prediction apparatus predicts the behavior of the first object in the first prediction process based on the behavior of each of the second objects subjected to the prediction process.

A driving assistance method includes: detecting a first other vehicle entering an intersection on a first route where a host vehicle is traveling from a second route; predicting whether or not the first other vehicle will stop in the intersection, and predicting a stop position of the first other vehicle; calculating a minimum distance of a first gap between a vehicle body of the first other vehicle and a surrounding object around the first other vehicle or between the vehicle body of the first other vehicle and a road edge of a travel lane of the first other vehicle when the first other vehicle stops at the predicted stop position; and predicting according to the calculated minimum distance whether or not a second other vehicle, which is a following vehicle behind the first other vehicle, may slip through the first gap from behind the first other vehicle.

A method of controlling a hybrid-electric vehicle includes determining that a slow-down condition of the hybrid-electric vehicle comprises a reduction in speed of the hybrid-electric vehicle that is greater than or equal to a threshold. The method also includes modifying transmission shifting points in a regenerative braking mode to rotate an electric machine of the hybrid-electric vehicle above an engine start limit. The method also includes, in response to receiving an indication of an end of the slow-down condition, causing rotation of the electric machine above the engine start limit to trigger starting an engine of the hybrid-electric vehicle.

Systems and methods for controlling navigation of an autonomous vehicle for making an unprotected turn while traversing an intersection. The methods may include identifying a loiter pose of an autonomous vehicle for stopping at a point in an intersection before initiating an unprotected turn, initiating navigation of the autonomous vehicle to the loiter pose when a traffic signal is at a first state, determining whether the traffic signal has changed to a second state during or after navigation of the autonomous vehicle to the loiter pose, and in response to determining that the traffic signal has changed to the second state, generating a first trajectory for navigating the autonomous vehicle to execute the unprotected turn if the expected time for moving the autonomous vehicle from a current position to a position when the autonomous vehicle has fully exited an opposing conflict lane is less than a threshold time.

This document describes methods and systems for enabling an autonomous vehicle (AV) to determine a path to a stopping location. The AV will determine a desired stop location (DSL) that is associated with a service request. The AV's motion control system will move the AV along a path to the DSL. While moving along the path, the AV's perception system will detect ambient conditions near the DSL. The ambient conditions will be parameters associated with a stopping rule. The AV will apply the stopping rule to the ambient conditions to determine whether the stopping rule permits the AV to stop at the DSL. If the stopping rule permits the AV to stop at the DSL, the motion control system will move the AV to, and stop at, the DSL. Otherwise, the motion control system will not stop the AV at the DSL.

A navigation ECU executes processing including the following steps. The steps include: a step of acquiring information on travel sections to destination; a step of setting a starting point travel section and an nth travel section; a step of setting an n+1th travel section as an nth travel section when the starting point travel section and the nth travel section are identical in regulation information and road type, and difference in load is equal to or less than a threshold A; and a step of integrating the travel sections from the starting point travel section to an n−1th travel section when the starting point travel section and the nth travel section are not identical in regulation information and road type, and the difference in load is greater than the threshold A.