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.

A method for operating a vehicle in an automatic driving operation not requiring any user action which can be deactivated by a deactivation action of a driver of the vehicle includes, during the automatic driving operation in a learning phase, driving situations in which the driver deactivates the automatic driving operation are recorded by a surroundings recording device and the recorded driving situations are stored in a memory as subjectively critical driving situations. The method further includes, during an operating phase of the automatic driving operation, comparing a currently recorded driving situation to the stored subjectively critical driving situations and emitting a warning to the driver when the currently recorded driving situation matches one of the stored subjectively critical driving situations within a tolerance range.

A control device for a vehicle drive unit is configured to control, based on an operating state of a vehicle, a vehicle drive unit having one or more power sources. The control device includes a processor and a storage device. The storage device is configured to store a vehicle front-rear acceleration prediction model being a machine learning model that receives as an input a command torque and outputs predicted acceleration. The processor is configured to: execute a predicted acceleration calculation process using the vehicle front-rear acceleration prediction model; and execute a command torque calculation process to calculate the command torque that minimizes an evaluation function. The evaluation function minimizes a deviation of the predicted acceleration with respect to a target vehicle front-rear acceleration according to a target torque based on the operating state while reducing a deviation of the command torque with respect to the target torque.

An advanced driver assistance system configured to implement one or more automotive V2V applications designed to assist a driver in driving a Host Motor-Vehicle. The advanced driver assistance system is configured to be connectable to an automotive on-board communication network to communicate with automotive on-board systems to implement one or different automotive functionalities aimed at assisting the driver in driving the Host Motor-Vehicle, controlling the Host Motor-Vehicle, and informing the driver of the Host Motor-Vehicle of the presence of Relevant Motor-Vehicles deemed to be relevant to the driving safety of the Host Motor-Vehicle.

There is provided a travel reference line determination system and an automatic driving system capable of determining a travel reference line of a vehicle appropriately even under conditions where information representing the track environment of the vehicle is hard to get. An ECU of an automatic driving system calculates a model y coordinate value ymw_i using a map in FIG. 4 (Step 12), calculates an estimated y coordinate value y_i using track environment data D_info (Step 11), calculates curvature C so that an error between the model y coordinate value ymw_i and the estimated y coordinate value y_i may be minimized (Step 18), calculates a travel trajectory Xf using the curvature C (Step 4), and executes automatic driving control using the travel trajectory Xf (Steps 31 to 33).

A transportation vehicle with at least one first sensor for capturing environment data, at least one second sensor for capturing transportation vehicle data, a communication module for establishing a data connection with another transportation vehicle, a driving system for automated driving of the transportation vehicle, at least one output element for a visible/audible warning signal, and a control unit. The control unit determines a predicted trajectory of the transportation vehicle, determines a predicted path of the transportation vehicle and receives a predicted trajectory and vehicle geometry data of the other transportation vehicle via the data connection, determines a predicted path of the other transportation vehicle, determines a possible collision of the transportation vehicle with the other transportation vehicle, and in response to a possible collision, outputs a warning signal by the at least one output element and/or carries out an automated driving maneuver by the driving system.

A vehicle behavior generation device sets multiple possible behaviors of an own vehicle when the own vehicle travels along a planned route; sets multiple possible behaviors of a different vehicle existing around the own vehicle corresponding to each of the set multiple possible behaviors of the own vehicle; outputs information indicating a contact possibility between the own vehicle and the different vehicle for each of combinations of the set multiple possible behaviors of the own vehicle and the set multiple possible behaviors of the different vehicle; and selects one of the multiple possible behaviors of the own vehicle based on the outputted information.

A travel assistance device includes: an inner area prediction unit predicting a with-vehicle interaction that is a behavior taken, in response to a state of the subject vehicle, by a moving object within an inner area around the subject vehicle; an outer area prediction unit predicting a with-environment interaction that is a behavior taken by a moving object according to surrounding environment of the moving object within an outer area further to the subject vehicle than the inner area; an outer area planning unit planning a future behavior of the subject vehicle based on the predicted with-environment interaction, wherein the future behavior is a behavior pattern of the subject vehicle realized by traveling control; and an inner area planning unit planning a future trajectory of the subject vehicle in accordance with the future behavior based on the predicted with-vehicle interaction.

A driving support device includes a prediction unit, a trajectory determination unit, and a necessity determination unit. The prediction unit is configured to predict an increase degree of an inter-vehicle distance between other vehicles in response to the cut-in of the subject vehicle, and determine whether the lane change is permissible based on the increase degree. The necessity determination unit is configured to determine whether a necessity level of the lane change is within an acceptable range. The prediction unit is configured to cancel the determination whether the lane change is permissible based on the increase degree when it is determined that the necessity level is within the acceptable range, and determine whether the lane change is permissible based on a linear prediction of a behavior of the other vehicles.

A vehicle-based safety intervention system receives sensor data collected or generated by an onboard computing system of a vehicle. The sensor data is divided into a plurality of blocks, each of the blocks having a duration. A driver behavioral model is applied to one or more of the plurality of blocks to generate one or more driver behavioral parameters. A trend of the one or more driver behavioral parameters is extracted from the plurality of blocks. Based on the extracted trend, it is determined that a driver's performance when operating the vehicle is unsatisfactory or will be unsatisfactory in the future. A vehicle-based intervention is generated based on the determination that the driver's performance is unsatisfactory or will be unsatisfactory in the future.