Autonomous Decision Making Process TRIZ Cases

Autonomous submersible structure navigates using sensor data and viability profiles to maintain optimal water conditions for aquatic cargo.

A versatile autonomous vehicle system coordinates multiple robotic chassis to share tasks and navigate charging stations.

A fusion system monitors its own performance by comparing current determinations against previous ones to ensure reliable object classification.

A vision-based system generates driving scenarios by analyzing camera images to identify objects and their movement characteristics.

Segmented sensor data drives adaptive audible and haptic feedback, resolving the contradiction between detection accuracy and system complexity.

Convolutional neural networks transform images into cognitive maps, resolving object detection accuracy versus system complexity trade-offs.

A robot moves to a user blind area and outputs speech to redirect attention.

Electronic control unit selects optimal lane change regions using dynamic attribute correction.

Scout drones scan delivery points to detect obstructions, preventing product damage and reducing delivery delays.

A barrier control panel uses short-range transceivers to detect machine identifiers via radio zone interception.

Action planning system generates vehicle trajectories by estimating future environments and predicting dynamic obstacle reactions.

A trajectory generation system scales point density based on activity levels to optimize computational load.

Automated driving controller derives individual driving characteristics from manual operation history to tailor acceleration and steering behavior.

Offline-trained policies resolve navigation challenges without remote assistance latency.

Autonomous mobile system generates prediction-facilitating movement to resolve collision avoidance versus predictability contradictions.

Generates point confidence scores along obstacle trajectories to guide autonomous vehicle path planning.

A sensor processing module manages heterogeneous data via a message queue and handler to support plug-and-play integration.

Emergency escape mode deactivates collision avoidance to navigate pedestrians, resolving the conflict between occupant safety and pedestrian protection.

A controller calculates lateral offset using a lane marking equation to align radar and camera data.

A vehicle control device assesses driver readiness through specific operation requests before switching to manual driving mode.

Audio notification system conveys driving status to occupants via sound signals, adapting output based on wakefulness detection to prevent sleep disturbance.

A control system calculates material volume in the crest end region to issue specific cut instructions for semi-autonomous tractors.

Sensors monitor the compacting member surface for material buildup, triggering real-time alerts that prevent road indentations and over-compaction.

A vehicle storage platform allocates surplus parking spaces for inventory management.

Predictive trajectory analysis enables proactive autonomous lane merging, resolving the safety versus merging time contradiction in dense traffic.

Transition governance system calculates confidence factors from steering and acceleration errors to smoothly shift autonomous control to manual operation.

Driving controller increases surrounding environment margin after notifying occupants, resolving safety risks from insufficient control adjustments.

A drive mode switch control device acquires operation information from multiple targets to determine driver attitude.

An autonomous driving apparatus selects optimal tracking points around a companion using neural network predictions to guide movement.

A vehicle emergency assistance system detects driver hands-off situations and escalates warnings to prompt immediate reaction.

A passenger interface directs autonomous vehicle movement along a predetermined path via user interaction signals.

A protective action system detects impending weather conditions to assess damage risk for autonomous vehicles.

A common controller coordinates multiple marine vessel autopilots to resolve navigation precision trade-offs against system complexity.

Autonomous vehicles expand sensor measurement ranges to include areas above the vehicle, reducing collision risks during conveyance in confined spaces.

An autonomous aerial vehicle equipped with a mechanical lightbulb changer mechanism performs precise exterior lighting tasks.

A vehicle controller compares autonomous and manual driving data to determine the optimal driving mode for the subject vehicle.

Particle swarm optimization derives optimal controller coefficients for autonomous driving vehicles.

Pre-computed reaching distance maps enable rapid path planning in dynamic environments, reducing recalculation time while maintaining geometric feasibility.

Controller switches active handlers based on current belief state to resolve navigation inaccuracies during unexpected operational conditions.

Embedded ground detectors track ball movement without complex GPS hardware, reducing operational costs while soil sensors optimize water usage.

A controller manages autonomous vehicle movement by processing parking lot map data containing virtual lanes and weighted grid points.

Kinesthetic cues via steering wheel vibration restore driver situational awareness during automated lane changes, reducing information loss.

A vehicle movement control device defines lateral acceleration regions to maximize jerk at low speeds and minimize it at high speeds.

A server control unit matches user service preferences with available autonomous vehicles to generate travel plans.

Data construction units reduce transmission volume during high load, preventing CPU bottlenecks while maintaining situation awareness.

Driving assist system aggregates route data to identify safe napping windows for autonomous vehicle operators.

Vehicle controller transitions driving authority between entities using predicted performance criteria.