A vehicle-mounted dust sensor observes the roadway surface ahead to estimate road dust load in real time.
A vehicle control device matches stored feature information of preceding vehicles to adjust passing thresholds and suppress unnecessary lane changes.
A longitudinal dynamics control system adjusts feedback parameters based on wheel brake state variables to maintain vehicle spacing.
Front camera module predicts road curvature to adjust transmission speed ratios, resolving delayed inertial sensor response.
Processor estimates trailer length using radar targets, wheel angle, and hitch geometry to resolve measurement precision versus device complexity.
A vehicle control system detects stopped vehicles and adjacent lane traffic to execute avoidance maneuvers.
System generates control signals to disable autonomous driving when sensor viewing angles fall outside computed operational envelopes.
A vehicle merging controller adjusts control strategies based on real-time traffic volume to facilitate stable lane changes.
A vehicle control processor selectively displays only the deceleration target within the driver's visual recognition area.
Analyzing brain wave signals corrects posture-based comfort data to resolve the trade-off between measurement precision and system complexity.
A vehicle traveling control apparatus uses a speed deviation threshold to differentiate driver operations from automatic limit settings.
A computerized driving system adapts vehicle control policies by retrieving individual driver identifiers and applying learned preference data to customize autonomous behavior.
A driver assistance system detects deviations between desired and current driving profiles to automatically adapt vehicle parameters.
An attention calling device displays virtual images with variable conspicuity based on target object position.
A vehicle stop support system sets allowable lateral acceleration based on driver physical abnormality to select safe stop points.
A vehicle control system calculates deceleration to match border speed limits using GPS and sensor data.
A following vehicle generates a target trajectory and compares it with the detected path of a leading vehicle to enable automated driving.
Physics-based forward models convert clean sensor readings into simulated degraded data for training perception systems.
A multi-character search engine generates progressive search strings from sequential single-character inputs to refine database queries within an in-vehicle infotainment system.
A driving support apparatus predicts rear vehicle collisions during obstacle avoidance maneuvers.
A vehicle control system modifies acceleration rates based on rear headway distances to manage following traffic.
Dividing the passage into sections allows independent control of front and rear wheels to reduce impact and vertical motion without excessive system complexity.
A driving assistance apparatus forms a target track by merging lane and preceding vehicle paths.
A vehicle vision system guides a car along narrow driveways using rearward cameras and non-imaging sensors to detect edges and obstacles.
Automated driving systems detect lane cut-outs via lateral sensor data, resolving ambiguous acceleration control during complex traffic interactions.
Real-time dynamic modeling of non-rigid vehicle connections improves autonomous driving control accuracy by continuously updating position data.
Segmenting trajectory prediction into three phases resolves the contradiction between high accuracy and low complexity, reducing unnecessary safety activations.
A computer system generates an ellipse around a target vehicle to identify tangent lines representing potential collision zones.
On-screen blind spot detection icons overlay camera monitor images to show vehicle proximity.
A risk field model quantifies dynamic influences of surrounding vehicles to regenerate safe trajectories when initial plans violate risk constraints.
An electrodermal activity sensor integrated into a dual-sided transparent display detects user physiological conditions to trigger automated vehicle actions.
A control unit combines multiple drowsiness indicator signals to generate a comprehensive detection output.
Segmented flash memory areas in a vehicle control device enable switching to valid programs, preventing system failure during wireless updates.
A sliding mode trajectory voting strategy module integrates reaction time and relative distance into an obstacle feature sliding surface.
A driving support device adjusts obstacle detection based on wiper frequency and vehicle speed.
A wheel load estimation device calculates front-rear and left-right load ratios using wheel speed sensor data to determine relative wheel loads with high accuracy.
A vehicle launch assist function imposes torque constraints on wheels based on terrain data to prevent excessive wheel slip during acceleration.
A vehicle control device adjusts lane change permission conditions based on surrounding traffic detection.
A vehicle detection system monitors average, slope, and variation of range measurements to enhance near-object accuracy.
A control unit predicts overturning by simulating a virtual moving body on a virtual road surface prior to actual travel.
A vehicle control apparatus detects driver carelessness using lane and traffic sign data to issue timely warnings.
A vehicle control system adjusts driving torque using real-time wheel slip and weather data.
System differentiates turning-off from lane-change requests using sensor feedback to adjust deceleration rates for smooth automated driving.
A vehicle control system switches between white line tracing and track tracing modes based on periphery information.
System calculates stopping distance to halt vehicle safely when driver fails to resume manual control after alerting.
A vehicle control system monitors driver engagement using cameras and LIDAR sensors to adjust infotainment functionality.
A vehicle control system automatically activates hazard lights based on detected towing conditions and speed differentials.
A processing system generates individual 3D models for each vehicle sensor field of view and aggregates them into a comprehensive environmental representation.