Autonomous Decision Making Process TRIZ Cases

A vehicle ride control system uses suspension actuators and audio signals to simulate driving motions that help infants fall asleep.

Segmenting the battery into a removable pack and fixed holder resolves weight trade-offs while maintaining stable center-of-gravity positioning.

A vehicle control system adjusts automatic driving parameters based on detected towing states to enhance operational safety.

A simulator generates driving scenarios with parametric variations to evaluate autonomous vehicle performance under changing conditions.

A driverless vehicle decision system predicts obstacle tracks to determine safe travel motions during lane changes.

Segmented heading estimation models predict vulnerable road user trajectories using location and environmental data.

An inference module adjusts trajectory costs using dynamic obstacle probabilities to generate smooth vehicle paths.

A control system manages interchangeable product containers on autonomous agricultural machines using alignment sensors and automated transfer mechanisms.

Reference maps derived from past driving records correct steering signals, resolving calculation accuracy versus physical steering module distortion trade-offs.

A path generation module expands a search region to produce collision-free trajectory candidates for an autonomous vehicle.

A cognitive architecture predicts autonomous vehicle behavior by classifying taxonomic states from spatiotemporal location data and driving scenario elements.

A control system coordinates vehicle motion using a control invariant set to link trajectory generation with precise execution.

Segmenting centralized control into distributed units preserves vehicle payload volume while maintaining autonomous operation reliability.

A sensor system detects unknown objects and queries external databases to derive driving recommendations for automated vehicles.

Optical signal detection enables autonomous UAV following in GPS-denied environments by predicting target movement.

A dual autonomous mobile system coordinates road travel and store navigation to handle merchandise acquisition without human intervention.

A vehicle processor generates virtual maps using local sensors and external reports to enable precise navigation.

Processor switches Kalman filter parameters using map data to reduce measurement uncertainty across varying environmental conditions.

Vehicle control apparatus selects positions by combining object presence probability with driver travel data to determine a navigation path.

A composite autonomous driving controller manages longitudinal and lateral assistance devices through defined switching thresholds.

An interactive autonomous driving system uses environmental and driver sensors to dynamically switch between manual and autonomous modes.

A UAV storage unit uses integrated sensors and temperature-controlling devices to maintain ideal conditions for physical objects.

A segmented control architecture uses a high ASIL monitoring unit to check and override commands from a lower ASIL first unit.

Controller generates target profiles to autonomously operate machines along work surfaces.

An autonomous vehicle detects launch ramps and positions a trailer for watercraft transfer.

A semiautonomous vehicle controller activates autonomy modes while monitoring occupant attention through sensor feedback.

Segmenting reference trajectories by curvature enables approximate motion primitives that reduce processing time while maintaining route planning accuracy.

Touchscreen image manipulation adjusts following distance and turning speed, eliminating user uncertainty from numeric scales.

A vehicle controller estimates liquid depth via image analysis to adjust steering and acceleration.

Pre-configured effector combinations enable autonomous navigation and damage accommodation without complex real-time optimization.

A decision problem recognition module categorizes driving errors to trigger local and global improvement loops.

Dynamic control band adjustment resolves fixed maximum acceleration limits that prevent drivers from perceiving improved responsiveness during stage changes.

Notification device detects surrounding vehicles and transmits recognition results to entering traffic, resolving blind spot information gaps.