Patent classifications
B60W2050/0025
Systems and methods for controlling vehicle systems based on driver assessment
A system may include sensors that may acquire health data related to an individual. The system may also include a processor that may receive trip data associated with a current location of the individual and a destination location for the individual, traffic condition data associated with routes between the current location and the destination location, and weather related data associated with the routes. The processor may also receive the health data from the sensors and determine whether the individual is associated with a driver assessment score above a threshold based on the trip data, the traffic condition data, the weather data, the health data, or any combination thereof. The processor may then send an activation signal to a vehicle control system in response to the driver assessment score being above the threshold, such that the activation signal may enable the vehicle control system to control operations of a vehicle.
DEVICE, A METHOD, AND A COMPUTER PROGRAM FOR DETERMINING THE DRIVING BEHAVIOR OF A DRIVER
The invention relates to a device for determining the driving behavior of a driver, the device comprising at least means for receiving data from two or more data sources, of which at least one produces data relating to changes in the state of motion of a vehicle and at least one other produces measured data on the well-being of the driver; means for scoring the received data by comparing it with data-specific reference values; means for forming a respective sub-index from each scored item of data; means for determining a driving behavior index on the basis of the formed sub-indices; and means for controlling control equipment of the vehicle on the basis of the driving behavior index and/or for storing the driving behavior index in a database.
METHOD AND DEVICE FOR CONTROLLING AUTONOMOUS DRIVING
A method for controlling autonomous driving in a vehicle capable of the autonomous driving may include collecting vehicle travel status information and system status information during the autonomous driving, sensing a failure based on the system status information, identifying normally controllable actuators when sensing the failure, determining a risk degree corresponding to the sensed failure based on the normally controllable actuator information and the vehicle travel status information, determining a safety state based on normally controllable actuator information and the risk degree, and determining a failure safety strategy corresponding to the safety state.
SITUATION-ADAPTED ACTUATION FOR DRIVER ASSISTANCE SYSTEMS AND SYSTEMS FOR THE AT LEAST PARTIALLY AUTOMATED CONTROL OF VEHICLES
A method for generating an actuation signal for a driver assistance system and/or a system for the at least partially automated control of a vehicle. In the method, suggestions are made available for trajectories to be traveled by the vehicle and/or for other actions to be triggered that affect the driving dynamics of the vehicle. The suggestions are evaluated by a cost function, this cost function including a weighted sum of multiple cost terms, the weights being dynamically adapted. Utilizing the evaluations ascertained using the cost function, at least one trajectory or action is selected from among the suggestions. At least one actuation signal is generated that when conveyed to the driver assistance system or the system for the at least partially automatic control of the vehicle, induces the respective system to travel the selected trajectory with the vehicle or to trigger the suggested action.
APPARATUS AND METHOD FOR CONTROLLING DRIVING OF VEHICLE
An apparatus for controlling driving of a vehicle includes: an input device that receives an input signal corresponding to an operation of a driver; and a controller that sets a weight to a careless state of the driver based on a separation distance between the driver and the input device operated by the driver, a spaced angle, and a scheme of operating the input device, and calculates a braking application time point based on the weight.
VEHICLE LAUNCH FROM STANDSTILL UNDER ADAPTIVE CRUISE CONROL
In accordance with an exemplary embodiment, a vehicle is provided that includes a body, a drive system, and a control system for controlling the adaptive cruise control functionality for the vehicle. The drive system is disposed within the body, and has adaptive cruise control functionality. The control system includes: one or more sensors disposed onboard the vehicle and configured to obtain sensor data for monitoring a driver of the vehicle while the vehicle is stopped during adaptive cruise control operation while a target vehicle in front of the vehicle has stopped; and a processor coupled to the one or more sensors and configured to provide instructions for automatically resuming movement of the vehicle, when the target vehicle resumes movement, based on the monitoring of the driver of the vehicle.
ROUTE SELECTION DEVICE AND METHOD
A route selection device includes a processor configured to identify a position of a lane on which a vehicle is traveling; search for candidate partial routes leading from a current position of the vehicle to a waypoint on a route leading from a start point to a destination, the waypoint being located between the current position and the destination; determine a lane change location where a lane change will be made for each of the candidate partial routes found by searching; and select, as a partial route, a candidate partial route having a minimum total score regarding the lane change location from the candidate partial routes found by searching. The score is weighted depending on the position of the determined lane change location or whether a lane change at the lane change location can be controlled by a travel controller.
Systems and Methods for Optimizing Trajectory Planner Based on Human Driving Behaviors
In one embodiment, a computing system of a vehicle may receive vehicle driving data associated with a vehicle driving in an environment and detected environment data associated with the environment. The system may generate a reference trajectory of the vehicle driving in the environment based on the vehicle driving data. The system may determine driving constraints associated with the environment based on the detected environmental data. The system may generate a trajectory of the vehicle based on the driving constraints. The system may determine a difference in at least one parameter associated with the trajectory relative to at least one corresponding parameter associated with the reference trajectory. The system may adjust weight values associated with cost functions of the trajectory based on the difference between the at least one parameter associated with the trajectory and the corresponding parameter associated with the reference trajectory.
REGENERATIVE ELECTRICAL POWER SYSTEM WITH STATE OF CHARGE MANAGEMENT IN VIEW OF PREDICTED AND-OR SCHEDULED STOPOVER AUXILIARY POWER REQUIREMENTS
A vehicle with a hybrid drivetrain including a fuel-fed engine coupled to a first drive axle, an electric motor coupled to a second drive axle and an APU for providing electrical power at stopover locations, and further including a controller for determining a location of the vehicle, a location of a stopover location, determining a target SOC of a battery for operating the APU at the stopover location and operating a hybrid control system to provide the target SOC for the vehicle at the stopover location.
APPARATUS AND METHOD FOR DETERMINING OPTIMAL VELOCITY OF VEHICLE
An apparatus of determining an optimal velocity of a vehicle, may include an information receiving unit configured to receive and provide vehicle traveling information and traveling environment information which are state variables representing vehicle states required to determine a target velocity for optimizing vehicle fuel economy; and an optimal velocity determination unit configured to determine the target velocity in accordance with a vehicle traveling environment by use of a state variable and reward estimation model and a Q table having values according to the state variables and a control input, from the vehicle traveling information and the traveling environment information provided by the information receiving unit, and a method of determining an optimal velocity of a vehicle.