Autonomous Decision Making Process TRIZ Cases
- Roadway Markers with Electromagnetic Signatures for Radar Detection
Radar detects lane markers via electromagnetic signatures, maintaining reliability through precipitation and wear.
- Autonomous Cab-Less Yard Truck Trailer Positioning
Sensors on an autonomous cab-less yard truck enable precise trailer positioning while preventing collisions in dense storage areas.
- Vehicle State Determination for Sidewalk Crossing
A vehicle state determination device assesses sidewalk and roadway conditions to manage entry operations.
- V2X Sensor Fusion for Obstacle Awareness in Autonomous Vehicles
Merging onboard sensor data with V2X communications overcomes blocked views and improves path planning reliability.
- Pedal Sensor System for Seamless Autonomous to Manual Control Transition
Proximity sensors detect foot movements to switch vehicle control modes between autonomous and manual driving.
- Automated Landmark Tagging for Robotic Navigation
Automated image analysis replaces manual surveys by identifying and storing landmark attributes for accurate robotic localization.
- Vehicle Lane Change Control Maintaining New Path
Automatic driving controller maintains a new lane after occupant-initiated changes until specific conditions are met.
- Drive Planning Device Time-Series Event Segmentation
A drive planning device determines actions for events in a time-series manner to plan driving operations.
- Vehicle Sensor Accuracy Verification via Fleet Data Comparison
A vehicle environmental sensing evaluation system compares wireless reports from multiple cars to assess individual sensor reliability.
- Autonomous Vehicle Sound Detection via Sensor Fusion
Classifier identifies sound types and cross-verifies with sensor data to detect hazards before visual occlusion limits perception.
- Scrape Detection for Motor Vehicle Bumpers
A vehicle control system predicts trajectory paths and compares bumper elevations with roadway data to prevent scrapes.
- Automated Driving Rule Adaptation via Vehicle Behavior Observation
A driving-rule system modifies automated vehicle parameters by detecting deviations in surrounding traffic behavior.
- Activation Bypass and Weight Pruning for Vehicle Perception Neural Networks
Neural network activation bypass skips zero-value multiplications while weight pruning removes redundant synapses to optimize processing resources.
- Vehicle Mode Switching via Virtual Speed and Steering Angle Matching
A controller calculates virtual speed and steering angle from pedal displacement to enable safe manual driving mode transitions.
- Vehicle Direction Sensing System Torque Control
ECU compares GPS location with orientation data to reduce torque, preventing collisions from wrong-way vehicle entry.