Autonomous Decision Making Process TRIZ Cases
- Shared Vehicle Feature Adjustment for Personalized Driver Settings
Stored user profiles automatically adjust seats, mirrors, steering, and camera angles in shared vehicles to improve comfort, safety, and usability.
- Foldable Steering Manipulator for Autonomous-Manual Handover
A movable manipulator with a foldable steering wheel and integrated shift, throttle, and brake controls reduces misoperation during autonomous-manual handover.
- Autonomous Conveyance Control Updates for Rare Hazard Mitigation
Centralized shared learning distributes validated safety updates across autonomous conveyances to mitigate rare and unforeseen hazards faster.
- Autonomous Vehicle Path Control Around Occupied Occluded Sensor Zones
Occupancy detection in occluded sensor zones lets an autonomous vehicle reroute around hidden obstacles while preserving navigation efficiency.
- Multi-Vehicle Motion Planning Across Dynamic Traffic Conflict Zones
A centralized MIP scheduler coordinates CAVs through intersections and merging zones using real-time traffic data to improve safety and flow.
- Human Driving Rule Books for Autonomous Vehicle Decisions
Precomputed human driving rule books let autonomous vehicles handle intersections, parked cars, and jaywalkers with less real-time computation.
- Platooning Vehicle Precognitive Braking for Hazard Gap Control
Following vehicles detect road hazards early and brake preemptively to widen platoon gaps before the lead vehicle reacts, reducing collision risk.
- Construction Machine Turning Curves for Spot-Turn-Free Control
Continuous-curvature turning paths help construction machines reach target positions precisely while avoiding spot-turning and road surface damage.
- Remote Vehicle Monitoring for Obstacle Stop and Restart Control
Duplex monitoring combines onboard obstacle detection with remote video approval to stop safely and restart autonomous vehicles after interruptions.
- Vehicle Camera Data Prioritization for Distributed ADAS Processing
Priority-based image processing keeps safety-critical vehicle camera tasks local while offloading lower-priority ADAS workloads to cloud processors.
- Autonomous Vehicle Coordination Using V2V, V2I, and V2P Rules
Shared V2V, V2I, and V2P rules help autonomous and manual vehicles avoid collisions while improving traffic flow in dynamic road conditions.
- Transfer Hub Arrival Coordination for Capacity-Constrained Assets
Schedules asset arrivals to match transfer hub capacity, cutting wait time, overflow risk, and energy waste in autonomous transport networks.
- Autonomous Low-Speed Maneuver Replay Without Digital Road Maps
Stored low-speed maneuvers are replayed using sensor updates and remote learning to handle new obstacles in map-free driving areas.
- Vehicle Proximity Sensing With Sensor Diagnostics and Auto Braking
Monitored transducer arrays alert drivers to sensor faults and trigger speed or braking control to avoid collisions in poor ambient conditions.
- Autonomous Vehicle Sensor Recalibration Under Road Micromovements
Dynamic online recalibration refines sensor poses and calibration matrices to maintain autonomous vehicle localization on rough roads.
- Adaptive Vehicle Control Using Confidence-Weighted Trajectory Tracking
Confidence-weighted predictive control balances safety and comfort while turning probabilistic vehicle plans into smoother, more natural trajectories.