A system for providing situational recommendations within a vehicle includes a system controller in communication with a plurality of onboard sensors, the plurality of onboard sensors adapted to collect real-time data related to a location of the vehicle and operating conditions of the vehicle, a database in communication with the system controller adapted to store data related to past actions and data related to a location of the vehicle and operating conditions of the vehicle when such past actions occurred, the system controller including a driver specific machine learning model adapted to predict a desired action based on the real-time data related to the location and operating conditions of the vehicle and data from the database, the system controller further adapted to initiate the predicted desired action, receive input from an occupant within the vehicle, and update the driver specific machine learning model.

Trip is analyzed from a population of drivers in order to determine one or more indicators of one or more driving styles. The trip data may include sensor information obtained from one or more sensor devices which are present in a vehicle of each driver of the population. A driving style is determined for the driver during a monitored trip by analyzing sensor information obtained from one or more sensor devices of the driver during the trip for at least one of the indicators of the one or more driving styles.

A system includes a computer programmed to identify, from a first vehicle, one or more second vehicles within a specified distance to the first vehicle. The computer is further programmed to receive data about operations of each of the second vehicles, including trajectory data. Based on the data, the computer is programmed to identify, for each of the second vehicles, a distribution of probabilities of each of a set of potential planned trajectories. The computer is further programmed to determine a planned trajectory for the first vehicle, based on the respective distributions of probabilities of each of the set of potential planned trajectories for each of the second vehicles. The computer is further programmed to provide an instruction to at least one controller associated with the first vehicle based on the determined planned trajectory.

An apparatus for estimating a motion of a vehicle occupant, and a method therefor, can store motion estimating models of a vehicle occupant, collect behavior data of a vehicle, determine a traveling mode of the vehicle based on a longitudinal acceleration among the behavior data of the vehicle, and estimate a motion of the vehicle occupant using at least one of the motion estimating models corresponding to the traveling mode of the vehicle. The motion estimating models can include a first model corresponding to a dynamic mode of the vehicle and a second model corresponding to a steady state mode of the vehicle.

A vehicle control unit includes: a sensor-signal processing unit that acquires sensor signals from multiple sensors detecting physical quantities related to the surrounding environment of a vehicle and acquires, from at least one camera capturing images of the surrounding of the vehicle, image data indicating the captured images; a human-vision calculating unit that uses a human visual model calculated in advance calculates a visibility repulsive potential affected by vision of a human recognizing the images; and a potential-risk-prediction-model processing unit that uses a potential-risk prediction model for predicting a potential risk from characteristic quantities of the surrounding environment of a target vehicle to calculate a physical repulsive potential caused by the surrounding environment of the target vehicle on the basis of the physical quantities and the images, and calculates an integrated repulsive potential obtained by correcting the physical repulsive potential with the visibility repulsive potential.

A steering wheel hands-on/off detection device includes: an imaging part provided in a vehicle and configured to capture a motion of a driver; a dynamic sensor configured to measure a dynamics motion of the vehicle; an image processor configured to process an image obtained from the imaging part; and a vehicle safety controller. The image processor includes a driver monitoring part configured to derive a behavior type of the driver from the image and a keypoint extraction part configured to extract keypoints of the driver. An optimal torque and an optimal contact force are applied to the keypoints of the driver so that a driver dynamics model optimally controlled to follow a position of the driver is applied. The vehicle safety controller configured to determine steering wheel hands-on/off on the basis of a magnitude of a force applied to the steering wheel, which is estimated from the driver dynamics model.

A vehicle has a recommendation system, which includes a data collection module, a prediction module, and a recommendation module. The data collection module collects vehicle data, surroundings data, and/or environmental data. The prediction module reads a driver profile from a multitude of driver profiles, each driver profile including a machine learning model trained specifically for the respective driver profile set up to read the vehicle data, surroundings data, and/or environmental data at least for a route portion lying ahead and to issue a predictive indication value as an output variable. The recommendation module compares the predictive indication value to an indication threshold value and prompts a recommendation to be issued for a person driving the vehicle or a driver assistance system to take over vehicle control depending on the position of the predictive indication value in relation to the indication threshold value.

Methods and systems for determining impaired driving is provided. The methods include acquiring controller area network (CAN) data and location data of a vehicle, comparing the CAN data to a reference data associated with driving behavior of a driver of the vehicle, determining the driver is impaired driving in response to determining that a level of deviation of the CAN data from the reference data is greater than a threshold value, changing the threshold value in response to determining that the location data indicates the vehicle is located in an area associated with a place offering access to alcohol, and controlling operations of the vehicle in response to determining that the driver is impaired driving.

A system for providing situational recommendations within a vehicle includes a system controller in communication with a plurality of onboard sensors, the plurality of onboard sensors adapted to collect real-time data related to a location of the vehicle and operating conditions of the vehicle, a database in communication with the system controller adapted to store data related to past actions and data related to a location of the vehicle and operating conditions of the vehicle when such past actions occurred, the system controller including a driver specific machine learning model adapted to predict a desired action based on the real-time data related to the location and operating conditions of the vehicle and data from the database, the system controller further adapted to initiate the predicted desired action, receive input from an occupant within the vehicle, and update the driver specific machine learning model.

Systems and methods are provided for determining vehicle configurations. The system can receive simulation data or actual driving data of a driving track corresponding to a driver and associate the simulation data or actual driving data with one or more driving parameters. A driver style can be determined based on the one or more driving parameters. A vehicle configuration can be determined for a vehicle of the driver based on the determined driver style. The system can display one or more vehicle settings associated with the vehicle configuration on a user interface.