A processor unit (3) is configured for accessing speed data of a second vehicle (18), the speed data generated by a sensor of a first vehicle (1). The processor unit is also configured for creating a driving behavior profile of the second vehicle (18) based on the speed data and making a prediction about the future driving behavior of the second vehicle (18) based on the driving behavior profile of the second vehicle (18). Moreover, the processor unit is configured for determining a trajectory for the first vehicle (1) by executing an MPC algorithm, which includes a longitudinal dynamic model of the first vehicle and a cost function, such that the cost function is minimized. The prediction about the future driving behavior of the second vehicle (18) is taken into account in the determination of the trajectory.

A vehicle includes a sensor provided to obtain first motion information which is motion state information of an object, a navigator provided to obtain location information of the vehicle, and a controller including at least one processor configured to process the location information and the first motion information, wherein the controller is configured to receive an expected motion value of the object based on the location information, compare the expected motion value with the first motion information to determine a difference value therebetween, and conclude the object as a dangerous object when the difference value is greater than or equal to a predetermined value.

Disclosed are an apparatus for controlling a vehicle, a system including the apparatus, and a method for controlling the apparatus. The apparatus includes: a reference lane calculator to calculate a reference lane based on a traveling condition of the vehicle; a target determining device to determine a target of interest based on the reference lane and a predicted path of an object around the vehicle; and a control parameter calculating device to calculate a control parameter of the vehicle based on a traveling state of the target of interest.

A system and method for recognizing traffic signs during autonomous driving comprises a camera module obtaining a first recognition, a sensor obtains behavior information of the host vehicle and of nearby vehicles and a connected training module generates parameters for traffic sign recognition according to information as to the behavior of the host vehicle and the nearby vehicles. A recurrent neural network module is connected with the training module and the camera module, and outputs a second traffic sign recognition according to the parameters and the first recognition. Training parameters of the second recognition comprise the traffic sign recognition parameters and the first recognition, the accuracy of the training result being improved by combining other sensors to perform traffic sign recognition training.

The disclosure includes embodiments for improving an operation of a vehicular micro cloud by increasing a continuity of a vehicular micro cloud service provided by the vehicular micro cloud. A method includes maintaining a data structure of stored driving maneuver shapes, wherein each stored driving maneuver shape includes a set of driving maneuvers. The method includes sensing a candidate vehicle and a driving maneuver shape of the candidate vehicle. The method includes determining a matching driving maneuver shape from the stored driving maneuver shapes based on a match between the driving maneuver shape of the candidate vehicle and at least a portion of the matching driving maneuver shape. The method includes estimating a next driving maneuver of the candidate vehicle. The method includes assigning a role to the candidate vehicle in the vehicular micro cloud based on the next driving maneuver of the candidate vehicle.

A system for increasing the safety of voice conversations between drivers and remote parties is shown. The system includes an in-vehicle subsystem and a remote subsystem. The system includes a plurality of sensors which are configured to generate monitoring data. The system includes a computing device, which may be distributed between the subsystems and is configured to calculate a risk level as a function of the monitoring data. The computing device may engage an automatic safety response as a function of the risk level, that may include suspension or termination of on-going conversations among the parties, together with notification about the status of the communication channel. The safety response may be communicated to the driver by generating an alert. The in-vehicle and the remote subsystems communicate using a wireless connection and collaborate in engaging the automatic safety response and communicating any alerts to the driver and remote party using notifications.

A control system and a method for vehicle control in geographical control zones is provided. The control system receives traffic information, including a plurality of image frames of a group of moving objects in a geographical control zone and generates a set of images frames of a first moving object of the group of moving objects based on application of a trained Neural Network (NN) model on the received traffic information. The generated set of image frames corresponds to a set of likely positions of the first moving object at a future time instant. The control system predicts the unsafe behavior of the first moving object based on the generated set of image frames and generates first control information, including an alternate route for a first vehicle in the geographical control zone based on the predicted unsafe behavior. The first vehicle is controlled based on the generated first control information.

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.

An autonomous vehicle (AV) includes features that allows the AV to comply with applicable regulations and statues for performing safe driving operation. An example method for operating the AV includes determining a trajectory related information of a vehicle operating on a roadway on which the AV is operating; receiving sensor data of a first area that includes the vehicle; determining an additional trajectory related information for the AV by comparing the trajectory related information of the vehicle to a current trajectory related information of the AV, wherein the additional trajectory related information is based on a category to which the vehicle belongs, and wherein the additional trajectory related information allows the AV to maintain at least a distance between the AV and the vehicle; and causing the AV to operate in accordance with the additional trajectory related information.