Lane change assist control unit monitors vehicle position to execute steering adjustments during lane changes.
A vehicle object detection apparatus estimates target positions using last known data when direct sensor calculation is impossible.
A collision avoidance system classifies sensor data within a vehicle corridor to determine object positions and velocities for trajectory control.
A work vehicle monitoring system synthesizes bird's eye images and displays overlaid radar marks on a single monitor screen.
A detection unit identifies rescue lane formation using camera and acoustic sensors to alert drivers.
A virtual road plane merges multiple camera images into a single perspective view.
A driving assist device executes autonomous lane changes to maintain travel in a non-passing lane when approaching an area border.
A post-processing module fits lane markings into arcs to generate stable templates for autonomous vehicle navigation.
Apparatus calculates reliability of surrounding-based risk by comparing it against behavior-derived risk, resolving mismatched evaluation results.
A travel vehicle system calculates turn data from attitude and speed measurements to correct detected steering angle signals.
A recognition system clusters three-dimensional scan points using voxel identification data to isolate moving objects from static backgrounds.
Estimation drive control unit switches to alternative sensor data when primary sensors fail.
Adjusts collision probability sensitivity based on object position and movement direction to trigger avoidance support.
A vehicle danger notification control apparatus detects moving objects using stereo cameras to identify collision risks between vehicles and pedestrians.
Top-down image display visualizes external object distance to resolve spatial situation awareness loss during parking exit maneuvers.
A vehicle traveling control apparatus adjusts target speed based on detected steering wheel holding state during automatic driving.
A driving support apparatus sets an extrapolation cruising lane when detection fails, using vehicle distance and lateral speed to determine the duration.
A vehicle control unit assesses lane marking accuracy by measuring distances between the host lane and surrounding vehicles.
A lane model parameter estimation method uses tangential direction of road-parallel structures to define the course of the lane.
A vehicle operation support device predicts future lateral position to initiate obstacle avoidance control.
Generates space-time trajectories from object position and internal state to predict probabilistic paths.
Shifting a reference line toward the target lane signals intent, reducing waiting time while maintaining safety during gap search.
A braking assistance apparatus determines cut-in vehicle accelerability to set the braking level.
Output controller manages multi-modal information delivery via visual displays, light emitters, and seat belt vibrations.
A driving assistance apparatus predicts future movement points using speed vectors to adjust detection ranges for lateral targets.
Association device links occupant viewing direction to detected vehicle surroundings objects using gaze and sensor data.
A driving control device adjusts target deceleration based on inter-vehicle distance to maintain safe following spacing.
Computing unit predicts driver gaze via sensor patterns to time alerts, preventing distraction during critical traffic events.
A vehicle information transmitting device shifts display position, size, and color to convey danger.
A vehicle control prediction unit anticipates peripheral vehicle positions using dynamic acceleration models and virtual object tracking.
Control circuit adjusts automatic lane change operational conditions to execute a shoulder maneuver.
A multi-task CNN extracts shared features across perception tasks to process object detection and semantic segmentation concurrently.
A clear path detection method fuses camera and radar data to identify navigable surfaces.
Cloud-based digital behavioral twin system aggregates vehicle sensor data to predict driving contexts and modify ADAS operations at intersections.
A sensor calibration system acquires three-dimensional shape information to determine relative positions and orientations of vehicle-mounted sensors.
A vehicle control unit estimates future positions using WAVE messages to generate accident risk warnings.
A computer system calculates nominal vehicle paths by serving digital road frames to an annotation portal for lane marker labeling.
Microcomputer compares actual parking technique against a model to prevent unnecessary assistance when driver skills match the model.
An electronic control unit predicts intersections with dynamic objects to determine evasive trajectories that release traffic area space.
Control unit filters multipath ghost reflections by comparing distance and speed differences between left and right detection units.
A hazard reporting system converts verbal driver reports into machine-readable data using speech recognition.
A driver assistance device merges camera image data with ultrasonic sensor readings to identify objects in the vehicle environment.
Autonomous vehicles detect disasters via sensor data and machine learning, altering drive modes to ensure passenger safety during emergencies.
An object validation system stores sensor data in modality-specific buffers to classify perceived objects as validated or unvalidated.
A driver monitor camera measures eye-closing periods to trigger an early-warning mode via a warning control ECU.
Control system detects following vehicles and determines lane occupancy using environmental sensor data to resolve complex traffic scenario contradictions.
Feedback system guides inexperienced drivers through optimal trajectory timing to balance safety with driving pleasure.
A driver assistance system executes lateral guidance interventions independently of longitudinal control via a single on-off button.
A computerized object-tracking system generates kinematic models from sensor scan data to determine object size, shape, and orientation.