To provide a vehicle control system that is capable of planning a trajectory that can ensure more visibility and enables safe traveling when an invisible range of a sensor exists.

A vehicle control system that plans a target trajectory of a vehicle based on recognition information from an external environment sensor, the vehicle control system including a recognizing unit that recognizes an object at a periphery of the vehicle based on the recognition information; and a trajectory planning unit that plans the target trajectory such that an actual detection range of the external environment sensor becomes wide when the recognizing unit recognizes the object.

An autonomous driving system acquires information concerning a vehicle density in an adjacent lane that is adjacent to a lane on which an own vehicle is traveling, when the own vehicle travels on a road having a plurality of lanes. The autonomous driving system selects the adjacent lane as an own vehicle travel lane, when the vehicle density in the adjacent lane that is calculated from the acquired information is lower than a threshold density that is determined in accordance with relations between the own vehicle and surrounding vehicles. The autonomous driving system performs lane change to the adjacent lane autonomously, or propose lane change to the adjacent lane to a driver, when the adjacent lane is selected as the own vehicle travel lane.

A method for selecting a content forwarding node in a vehicle ad-hoc network on the basis of service type, comprising the following steps: calculating a bandwidth occupation proportion factor according to the type of requested content information and a bandwidth occupation situation of a neighboring vehicle which can perform forwarding in a one-hop transmission range; defining a virtual arrival time of a candidate forwarding vehicle to an initial request vehicle according to the distance between the neighboring vehicle and the initial request vehicle and a driving speed of the neighboring vehicle; calculating a forwarding node impact factor according to the bandwidth occupation proportion factor and the virtual arrival time; and selecting a forwarding node according to the forwarding node impact factor.

The travel assistance apparatus includes: a first Operating System (OS) that controls execution of at least one of a first application and/or a second application, the first application being for specifying a first travel control amount of a vehicle based on first movement information on a position and a speed of an object around the vehicle, the second application being for specifying a second travel control amount of the vehicle based on second movement information on a position and a speed of the object; a second OS that controls execution of a third application for performing travel control of the vehicle based on at least one of the first travel control amount and/or the second travel control amount; and a hypervisor that is executed on a processor and controls execution of the first OS and the second OS.

A navigation apparatus includes: an own vehicle position calculation unit, a scroll processing unit, and a map drawing unit that display a map image of an own vehicle position and its surroundings as a current-location window at a current-location scale, and when swiping of the screen by a user's finger is detected using a touch panel, display a map image of which display range is moved in response to this swipe operation as a scroll window at a scroll scale; a scale setting unit that changes the current-location scale and the scroll scale in response to pinch-in/out; and a scale determination unit that, when display of the current-location window is instructed by the user and a predetermined condition is satisfied, updates the current-location scale using the scroll scale, and in other cases, maintains the previous current-location scale.

A method and an apparatus for using a multi-boundary region to provide an Internet of Things (IoT) service according to an entrance and an exit of a preset boundary region based on a location of a vehicle, and an apparatus therefor. A method of controlling a location-based service includes determining a current location of a vehicle, and controlling reception of a notification information service. The notification information services is generated by at least one IoT device corresponding to a preset point in a plurality of states based on an ignition state and a relationship of the current location with respect to a first geo-fence set based on a distance from the preset point and a second geo-fence set based on an expected arrival time from the point. The second geo-fence may be set inside the first geo-fence.

A vehicle control system includes a detector and a processor. The detector is configured to detect a first stop line on the basis of map data stored in a road map database, and detect a second stop line on the basis of traveling environment data acquired by a camera unit. In a case where the detector detects the first stop line, the processor is configured to control a vehicle to decelerate at a first deceleration rate calculated on the basis of a distance from the vehicle to the first stop line. In a case where the detector detects the second stop line after detecting the first stop line, the processor is configured to control the vehicle to decelerate at a second deceleration rate calculated on the basis of a distance from the vehicle to the second stop line and stop at the second stop line.

An apparatus for controlling a distance from a front vehicle includes a receiver to receive information on a host vehicle and information on the front vehicle, an acceleration generator to generate one of first acceleration for the host vehicle or second acceleration for the host vehicle, based on the received information on the host vehicle and the received information on the front vehicle and an output device to output the generated first acceleration or the generated second acceleration.

A vehicle trajectory prediction device is provided. The vehicle trajectory prediction device includes a transceiver, at least one processor, and at least one memory operatively connected with the at least one processor to store at least one instruction causing the at least one processor to perform operations. The operations receive first trajectory data for an ego-vehicle and second trajectory data for at least one neighbor-vehicle, obtain a first feature vector from a first extractor and obtain a second feature vector from a second extractor, obtain an interdependency feature vector between the ego-vehicle and the at least one neighbor-vehicle from a third extractor having mapping data generated by mapping the second feature vector to the second trajectory data as input data, and generate predicted trajectory data of the ego-vehicle from a trajectory generator having the first feature vector and the interdependency feature vector as input data.

Proactively mitigating risk to a vehicle traversing a vehicle transportation network is described. First and second hazard zones for first and second objects ahead of the vehicle are respectively determined. The first hazard zone includes a first target lateral constraint that extends over a left lane boundary, and the second hazard zone includes a second target lateral constraint that extends over a right lane boundary. The lateral constraints separately allow the vehicle to avoid the objects without a speed constraint. Where the first and second hazard zones overlap in the longitudinal direction, a lateral buffer is allocated between the lateral constraints to generate first and second allocated lateral constraints. Longitudinal constraints are respectively determined based on times of arrival at each hazard zone. Using the constraints, a proactive trajectory is determined that includes a lateral contingency, a longitudinal contingency, or both. The vehicle is controlled according to the trajectory.