A method and apparatus for avoiding a blind spot of a vehicle, where the apparatus for avoiding the blind spot of the vehicle includes an image sensor configured to provide image information by acquiring a surrounding image of a host vehicle, and a vehicle controller configured to sense a large vehicle traveling adjacent to the host vehicle based on the image information, determine a blind spot range of the large vehicle, determine a dangerous level of the blind spot range, and generate a path for the host vehicle to deviate from the blind spot or to avoids the blind spot, based on a traveling situation of the host vehicle.

A system for avoiding blind spot using accident history information, includes an image sensor configured to provide image information by acquiring a surrounding image of a host vehicle, and a vehicle controller. The vehicle controller is configured to detect, through the image sensor, an adjacent vehicle traveling adjacent to the host vehicle and a license plate of the adjacent vehicle; determine a dangerous level of the blind spot of the adjacent vehicle, based on accident history information of the adjacent vehicle and driver tendency information of a driver of the adjacent vehicle obtained by inquiring about the license plate of the adjacent vehicle, after determining a blind spot range of the adjacent vehicle; and generate a path in which the host vehicle deviates from the blind spot or avoids the blind spot to reduce the dangerous level of the blind spot, based on a traveling situation of the host vehicle.

A vehicle controlling apparatus includes a setting unit and an acquiring unit. The setting unit is configured to set a target inter-vehicle distance. The acquiring unit is configured to acquire position information of a temporary stopping location on a traveling route on which an own vehicle travels. The setting unit is configured to, on a condition that the own vehicle travels to follow a preceding vehicle, and that the acquiring unit has acquired the position information of the temporary stopping location, make a setting change to make the target inter-vehicle distance greater than a normal setting value when a distance from the own vehicle to the temporary stopping location reaches a predetermined distance, and make a setting change to bring the target inter-vehicle distance closer to the normal setting value in accordance with the distance until the own vehicle reaches the temporary stopping location.

A method and apparatus are provided for determining one or more behavior models used by an autonomous vehicle to predict the behavior of detected objects. The autonomous vehicle may collect and record object behavior using one or more sensors. The autonomous vehicle may then communicate the recorded object behavior to a server operative to determine the behavior models. The server may determine the behavior models according to a given object classification, actions of interest performed by the object, and the object's perceived surroundings.

A method for operating a vehicle assistance system is described. In one embodiment, when the vehicle is in the autonomous driving mode, encountering an obstacle is prevented independent of the passage height, due to a control unit if is determined that the obstacle is a load supported by a working machine, where the load projects into a driving corridor of the vehicle or moves in the driving corridor. Also described is a device for carrying out the method and to a vehicle having such a device.

An autonomous grain cart includes a width less than or equal to a distance from an end of the header of an agricultural vehicle to a lateral side of the agricultural vehicle, wherein the end and the lateral side are on a same longitudinal side of a lateral centerline of the agricultural vehicle, wherein the autonomous grain cart is configured to receive grain from the agricultural vehicle. The autonomous grain cart also includes a controller, comprising a processor and a memory. The autonomous grain cart further includes a drive system communicatively coupled to the controller, wherein the controller is configured to instruct the drive system to propel the autonomous grain cart. The autonomous grain cart also includes a steering system communicatively coupled to the controller, wherein the controller is configured to instruct the steering system to steer the autonomous grain cart.

A travel control device comprising: a control unit configured to control travel of a vehicle; a first acquisition unit configured to acquire information regarding the surroundings of the vehicle; and a second acquisition unit configured to acquire vehicle information regarding another vehicle traveling in the same direction as the vehicle in a different lane from the lane that the vehicle is traveling in with at least a part of the other vehicle forward of the vehicle, the vehicle information regarding the other vehicle being included in the information regarding the surroundings of the vehicle acquired by the first acquisition unit, wherein, if the vehicle information regarding the other vehicle fulfills a condition, the control unit, in accordance with a state of approach of the vehicle to the other vehicle, performs control so that the vehicle decelerates.

A computer-implemented method for scheduling a vehicle software update in a vehicle, for example, in heavy-duty vehicle which may be operating in a defined area or site, and/or along a defined trajectory, the method comprising associating a probability of the vehicle having an updateable operational state with one or more time periods, wherein the probability of the vehicle being updateable is determined based at least partly on data representing behavioural states of one or more similar vehicles, in other words, other vehicles which have usage characteristics which have a relationship to the usage characteristics of the vehicle; scheduling a pending software update until the next time period of the one or more time periods where the probability of the vehicle having an updateable operational states meets a software update condition; and, enabling the vehicle to perform the software update when the vehicle probability having the updateable operational state meets the software update condition.

A system for notifying emergency services of a vehicular crash may (i) receive sensor data of a vehicular crash from at least one mobile device associated with a user; (ii) generate a scenario model of the vehicular crash based upon the received sensor data; (iii) store the scenario model; and/or (iv) transmit a message to one or more emergency services based upon the scenario model. As a result, the speed and accuracy of deploying emergency services to the vehicular crash location is increased. The system may also utilize vehicle occupant positional data, and internal and external sensor data to detect potential imminent vehicle collisions, take corrective actions, automatically engage autonomous or semi-autonomous vehicle features, and/or generate virtual reconstructions of the vehicle collision.

A method is provided that includes receiving user input identifying a travel destination for a first vehicle, determining, by a processor, a first route for the first vehicle to follow, and configuring the first vehicle to follow the first route. The method further includes obtaining a model for a second vehicle that shares a road with the first vehicle and comparing model to a pre-determined template for a vehicle that is known to be a special purpose vehicle in order to determine whether the first template and the second template match. The method further includes determining, by the processor, a second route that leads to the travel destination, when a match is found to exist, and switching the first vehicle from following the first route to following the second route.