Autonomous Decision Making Process TRIZ Cases

Vehicle control algorithms fuse road condition preview information with sensed vehicle dynamics to adjust headway distance and speed limits.

A lane change control device calculates an abort necessity level from driving environment data to determine driver intent.

A fleet management system determines vehicle operation modes using hierarchical levels or tags to assign appropriate driving capabilities.

A secondary controller validates primary actuator signals to maintain lane position.

Primary controller re-queues incomplete tasks to other slave controllers, ensuring fault tolerance without redundant hardware.

Travel control apparatus adjusts drive torque based on tire grip state during vehicle turns.

A camera with a narrow bandwidth emitter detects oncoming vehicle speed and position to calculate overtaking safety levels.

A scenario-specific operational control module alters vehicle orientation to reduce right-of-way ambiguity.

A vehicle handoff system assesses driver competency through training exercises during autonomous operation to approve control transitions.

A vehicle controller selects a charger within a geofence and joins a queue with a proposed schedule based on state-of-charge.

Replacing bulky mechanical switches, this compact light scanner detects objects with high reliability while reducing device size and cost.

A vehicle control system uses high-frequency electromagnetic pulses to determine precise proximity and position data for onboard movement.

Machine-readable optical markers encode vehicle identifiers to resolve precision and complexity trade-offs in wireless tracking systems.

Remote computing system compares vehicle and external environmental signals to generate restriction commands.

Speed trajectory optimizer generates energy-optimal speed profiles for vehicle control.

A controller manages vehicle movement within defined mining areas using virtual perimeters and dynamic mode switching.

Multiple individual learners apply segmentation and local quality principles to resolve contradictions between simulation accuracy and system complexity.

A vehicle seat integrates passive safety devices that switch between active and inactive states based on detected orientation.

A lawn treatment system uses scanning devices to identify weeds and insects before applying specific chemicals only to affected areas.

A directional acoustic device projects modulated ultrasonic waves along a vehicle travel path to convey auditory guidance messages.

A hidden Markov model calculates traffic sign recognition probabilities using temporal state transitions.

Centralized controller directs self-driving vehicles to pick-up locations based on calendar entries.

Segmented vehicle monitoring system processes external data to generate visual indicators, resolving information overload during autonomous fleet management.

Segmented light-emitting elements mark steering wheel regions to resolve ambiguous driver takeover requests during automated drive transitions.

A learning-based speed planner uses machine learning models to determine initial speeds for autonomous vehicles navigating obstacle-rich paths.

A vehicle control system compares map corridors with sensor-detected paths to select the most accurate data for navigation.

A fatigue monitoring system calculates a weighted alertness score using non-linear functions to track operator drowsiness.

A system analyzes vehicle trajectories to generate lane reference lines for navigation.

A vehicle controller updates displayed speed limits using camera-acquired image information to maintain accurate road data.

A telescopic crossbar rotates a vertical shaft to detect obstacles and calculate missed detection positions.

Segmented reward functions adapt autonomous path planning to individual passenger preferences while reducing real-time computing resource consumption.

A data processor selects detection results within a narrowed range to improve driving behavior model accuracy.

Interface control unit generates vehicle operation contents to alleviate passenger physical abnormalities.

Segmenting radar returns by Doppler shift and return power enables feature correlation that maintains position estimation accuracy in adverse weather.

A vehicle processing system compares object location data across multiple sensor frames to identify static obstacles.

A running control device sets lane change times based on moving object proximity and speed.

A speed profile generator adjusts discomfort thresholds to balance occupant comfort with tailgating vehicle safety.

A parking planner generates smooth reference lines for autonomous vehicles using perception and prediction modules.

A notification apparatus analyzes communication packets from neighboring vehicles to determine manual drive mode changes.

An augmentative control system monitors drone location against authorized zones to alter operations upon violation detection.

A PID embedded LQR control system generates steering commands to track reference trajectories in autonomous vehicles.

A multi-network system generates vehicle paths using deep learning and sensor data for precise autonomous parking.

A vehicle control system manages notification intervals to guide drivers from autonomous to manual operation.

A self-adaptive multiresolution digital plate generates binary multispectral patterns to communicate vehicle state information without wireless links.

A leading vehicle processor predicts collision probabilities and coordinates braking or lane changes with following vehicles.

A vehicle computer measures battery charge and tire pressure using onboard sensors to verify readiness before delivery.

Flight failure recovery system deploys a parachute to minimize damage from uncontrolled descents.

A control feedback loop uses analytical guidance laws to determine acceleration vectors for aerial robot maneuvers through narrow orifices.

Intermittent laser depth sensor operation maintains head pose accuracy while minimizing harmful ocular exposure.

Segmented vehicles with adjustable locators adapt to varied payload sizes, eliminating the need for specialized hardware.