A lane change control unit restricts an automatic lane change in the case of predicting that a user's own vehicle after having made the automatic lane change will be adjacent to another vehicle that exists inside of a third lane or on a third lane dividing line, and executes the automatic lane change without restriction in the case of predicting that the user's own vehicle after having made the automatic lane change will be adjacent to another vehicle that exists inside a fourth lane or inside of a road shoulder.

A method for tracking occluded objects includes encoding locations of a plurality of objects in an environment, determining a target object, receiving a first end point corresponding to a position of the target object before occlusion behind an occlusion object, distributing a hypothesis between both sides of the occlusion object during occlusion from a subsequent frame of the sequence of frames, receiving a second end point corresponding to a position of the target object after emerging from occlusion from another subsequent frame of the sequence of frames, and determining a trajectory of the target object when occluded by the occlusion object by performing inferences using a spatio-temporal probabilistic graph based on the current frame and the subsequent frames of the sequence of frames. The trajectory of the target object when occluded is used as a learning model for future target objects that are occluded by the occlusion object.

A vehicle control device that autonomously controls a vehicle so as not to cause rapid deceleration that leads to a deterioration in ride quality. The vehicle control device controls first and second deceleration, means that reduce a speed at a deceleration rate large than a deceleration rate of the first deceleration means. The vehicle control device includes a blind spot area detecting unit that detects a blind spot area of a sensor that recognizes an external environment, and a blind spot object estimating unit that estimates a blind spot object that is a virtual moving body hidden in the blind spot area. When a vehicle approaches the blind spot area at a speed reduced by the first deceleration means, the vehicle is decelerated by the second deceleration means when a type of a moving body detected by the sensor is different from a type of the blind spot object.

There is provided a method for preventing car collision, the method comprising: obtaining information about a vehicle stopped in front of a preceding vehicle acquired by the preceding vehicle; calculating a deceleration amount for preventing a collision with the stopped vehicle based on the information about the stopped vehicle; predicting a preset event related to the preceding vehicle based on a change in the position of the preceding vehicle; and controlling an autonomous driving vehicle based on the deceleration amount according to a prediction result.

Provided are methods, systems, and computer program products for vehicle dynamics classification for collision and loss of control detection. Some methods described also include obtaining sensor data associated with dynamics of a vehicle, wherein the dynamics characterize motion of the vehicle and the vehicle is associated with a dynamics event classification. The methods include obtaining predicted dynamics, wherein the predicted dynamics are based on control signals and feedback on control signals from a previous time instance. Additionally, the methods include determining the dynamics event classification of the vehicle based on the dynamics and the predicted dynamics and controlling operation of the vehicle according to the dynamics event classification.

A computing device for a radar sensor for identifying a disruption of the radar sensor through blocking or interference includes at least one interface for receiving radar data from the radar sensor and at least one processing device configured to determine at least one characteristic figure for a range of values in a noise distribution in the radar data, in which at most few and/at most weakly reflecting objects are present, and evaluate the characteristic figure in order to identify a disruption of the radar sensor.

A system for associating a physical identity and a virtual identity of a target vehicle includes a data processor, including a wireless communication module, positioned within an ego vehicle, and a plurality of perception sensors, positioned within the ego vehicle and adapted to collect data related to a physical identity of the target vehicle and to communicate the data related to the physical identity of the target vehicle to the data processor via a communication bus, the data processor adapted to receive, via a wireless communication channel, data related to a virtual identity of the target vehicle and to associate the physical identity of the target vehicle with the virtual identity of the target vehicle.

A vehicle traveling control apparatus includes a sensor and a traveling control processor configured to function as an identification unit and a tentative identification calculation unit. The identification unit identifies whether the target detected by the sensor is a ghost or a real object based on results of the detection for first number of measurement cycles, and if the target is the real object and a possibility that the target and the vehicle come into contact with each other is present, causes a first traveling control to be executed. The tentative identification calculation unit determines whether the target is the ghost or the real object based on results of the detection for second number of measurement cycles, and when the target is the ghost and the possibility is present, causes a second traveling control to be executed. The second number is less than the first number.

A vehicle control system includes a recording device configured to record vehicle information in files. The recording device includes: an event information receiving unit configured to receive information about prescribed events; a tag providing unit configured to provide protection tags to the files, the protection tags being of different types according to magnitude of the events; and an overwriting setting unit configured to prohibit overwriting of the files provided with the protection tags of a same type in a case where the number of the files provided with the protection tags of the same type is within a prescribed upper limit number, and to permit the overwriting of the files provided with the protection tags of the same type in a case where the number of the files provided with the protection tags of the same type exceeds the upper limit number.

A method, a computer program, an apparatus, a transportation vehicle, and a traffic entity for updating an environmental model at a transportation vehicle. The method for a traffic entity and for updating a first environmental model at a transportation vehicle includes receiving information related to the first environmental model from the transportation vehicle wherein the first environmental model has at least first information on an object in an environment of the transportation vehicle and the first environmental model includes confidence information related to the first information. The method also includes obtaining information related to a second environmental model of the transportation vehicle at the traffic entity wherein at least second information on the object in the environment of the transportation vehicle and the second environmental model includes confidence information related to the second information.