Self-driving vehicles steer onto specific tire paths to distribute weight and reduce premature roadway rutting.
Segmenting anticipated routes enables precise speed adjustments that reduce friction braking energy loss.
An automated driving system detects rear vehicles and executes lane changes or adjusts forward spacing to manage aggressive traffic interactions.
A vehicle control device filters planned lane changes to prioritize critical route adjustments for the driver.
A cognitive dialog system adjusts biometric thresholds using environmental data to monitor driver focus.
A driver attention detection system acquires steering control values and verifies road type changes to assess vigilance levels accurately.
A vehicle control apparatus adjusts determination thresholds based on detected road surface states to identify dangerous driving conditions.
A vehicle control module simulates localization at hypothetical future positions to initiate autonomous-to-manual driving transitions.
A vehicle agent device manager executes a unified stop command for activated function units.
A vehicle detection system transmits electromagnetic energy to determine the actual position of objects outside the field of view.
A vehicle control device limits automatic lane changes using external recognition and map data to determine safe maneuver windows.
A motorcycle assistance system compares current speed and lean angles against upcoming curve data to issue timely warnings.
A compact device combines GPS receivers with digital accelerometers to capture road curve properties.
Segmented ECUs with security measures improve measurement precision and reliability while managing device complexity.
A vehicle controller adjusts target selection criteria based on predicted travel road environments to identify appropriate lead vehicles.
A motor vehicle method trains artificial intelligence using archived operating data to optimize electronic control unit functions.
Curve fitting on point cloud center points calculates obstacle velocity to resolve trajectory deviations caused by posture fluctuations.
Travel control unit computes separation between vehicle and lane markings to enable precise obstacle avoidance maneuvers.
Segmented first and second sensors project different field distances to resolve measurement precision versus device complexity in vehicle alignment.
Electronic control device prevents stressful passenger scenarios by disabling autonomous overtaking when predetermined safety conditions remain unsatisfied.
A vehicle control system adapts ego-vehicle driving strategies based on lead vehicle maneuvers and sensor data.
An electronic control unit determines driving modes from a stored map based on GPS location and user sensitivity input to reduce driver distraction.
A safety speed threshold maintains ego vehicle velocity during sensor occlusions.
A standby terminal detects master failures through periodic heartbeat signals, enabling seamless manual takeover and preventing safety accidents.
A vehicle control unit selects a target preceding vehicle by comparing its position with the driver's visual line angle to adjust traveling speed.
A V2V notification system alerts drivers to remote vehicle movement.
A vehicle speed control system adjusts torque to maintain target speed while predicting the travel path.
Processor assesses collision risk before switching autonomous driving mode, preventing accidents from unintentional user inputs during emergency maneuvers.
A management device adjusts unmanned vehicle speed limits based on downhill inclination angles and manual input values.
A tire rolling radius analysis system determines grip potential by linking wheel rotation characteristics to vehicle parameters.
A vehicle control unit adjusts brake torque and suspension parameters based on detected road profiles.
A vehicle control system uses dual processors to determine target speeds at different periods for rapid obstacle avoidance.
Vehicle controller generates candidate avoidance routes and designates reach locations based on speed intervals to prevent collisions with cut-in vehicles.
A driver assistance system dynamically adjusts following distance using sensor data to optimize vehicle spacing.
A vehicle controller adjusts driver torque demand to increase perceived resistance and maintain safe following distance.
Dynamic detection range adjustment based on predicted minimum turn radius enables timely driver attention when moving objects cross the path.
A vehicle guidance system manages driving responsibility transitions between autonomous and manual modes through predefined operating ranges.
A vehicle control system applies reverse torque to driven wheels and brake pressure to non-driven wheels during braking stops.
A vehicle controller adjusts lead gaps based on rear sensing data to maintain safe trailing distances during adaptive cruise control.
A vehicle parking system uses sensor fusion to navigate and park autonomously.
Distributed sensors in mirror housings resolve blind spots and hood occlusion, enabling accurate lane detection during close-proximity truck platooning.
A vehicle state estimation system manages a rule set based on rough set theory to estimate operational states from conditional attributes.
A vehicle analysis device detects environmental transitions and vehicle parameters to determine driver behavioral changes.
Affective interfaces generate alerts via voice and graphical displays to inform operators about vehicle system confidence levels.
A vehicle control system calculates maximum limiting speeds based on ahead route curvature to proactively adjust actual speed before critical positions.
Controller coordinates retarder, transmission, and braking systems to manage deceleration and reduce sudden g-force changes during adaptive cruise control.
Automated driving system acquires surrounding vehicle data to determine contingency actions when the driver fails to accept manual control.
Navigation device supplies changed route data to cruise control, which evaluates traversal parameters to adjust target speeds without manual reference runs.
A vehicle control system manages wheel slip and torque distribution to maintain stability during low-speed off-road navigation.
An adaptive differential lock controller monitors wheel speed, incline angle, and curvature to automatically disengage the lock before tire wear occurs.