External Condition Input Parameters TRIZ Cases

A pod-mounted display, microphone, and speaker enable two-way local and remote communication for stalled autonomous vehicle support.

Switching among guided, operator-steered, and autonomous modes gives transit vehicles rail-like path precision without fixed tracks.

Variable steering correction ramp-down uses target-versus-actual control mismatch to end lane-keeping control without delay or premature release.

Occupied-area prioritization filters road users by location and class, enabling faster collision probability assessment and vehicle response.

Dual OTA software versions in a vehicle update controller preserve ECU update compatibility when server software changes across vendors.

Onboard sensor data estimates freight vehicle weight in real time to adjust braking control and verify load-limit compliance.

Adjustable wiper-based interlocks add alerts, speed de-rate, and delayed shutdown to avoid unsafe or unnecessary cruise control deactivation.

Driver-state monitoring gates autonomous-to-manual handover, preventing unsafe mode switches when recovery ability is insufficient.

Load-aware adaptive cruise control compares driver inputs with expected towing behavior to tune braking, acceleration, and following distance.

Projected 2D trajectory checks let autonomous machines weight or reject unsafe paths in real time without costly 3D collision simulation.

Adaptive path correction accounts for vehicles on both sides to keep safe distance without causing unnecessary occupant discomfort.

Remote tele-assist helps autonomous vehicles overcome impasses with less latency burden and less exhaustive rare-scenario training.

By switching ACC parameters before low-visibility zones, the vehicle avoids jerky acceleration and deceleration while maintaining stable speed control.

Minor abnormal driving detected by vehicle sensors is amplified into visual, audio, or haptic alerts so drivers can perceive it and trust the system.

Slip-aware control expands 2WD operation in autonomous driving, then switches to 4WD when traction risk rises to limit fuel loss.

Dynamic rear-vehicle distance thresholds let the host vehicle decelerate for needed lane changes while preserving safe following margins.

Shared driving-zone metadata lets vehicles anticipate risky areas early and guide safer maneuvers before drivers enter them.

Continuous sound changes reflect vehicle behavior, giving drivers real-time stability feedback without visual distraction.

An earlier disengage boundary gives drivers more takeover time while shadow ADS activates safety features before the ODD limit.

Automatic set speed carryover smooths transitions between automated driving functions while blocking unsafe adoption in exceptional cases.

A bypass control unit lets a vehicle start during emergencies or sensor faults while logging use and issuing alarms to limit drunk-driving abuse.

Gear and torque change detection lets the vehicle assess collision risk in the intended travel direction before unintended movement triggers impact.

Sensor-based mode switching balances automatic convenience control with driver input during autonomous driving transitions.

A steering assist controller resets the lane-keeping path from obstacle and oncoming-vehicle priorities to avoid abrupt lane departure control.

Biasing a vehicle within its lane before a steering maneuver signals intended direction, reducing unnecessary driver takeovers in SAE 2 driving.

Precomputed perception error distributions replace repeated full pipeline runs, cutting autonomous vehicle simulation time while preserving reliability estimation.

Rear-vehicle visibility and collision risk guide emergency deceleration control to reduce secondary rear-end crashes during sudden stops.

When counter-steering fails on ice or snow, controlled front-wheel slip redirects lateral forces to help the vehicle recover from severe skids.

Adaptive ATN and RTN models estimate driver recovery and action time during ODD exits to trigger safer hand-over requests.

Directional air or haptic cues map external hazards to the driver's body, improving immediate awareness and response.

Dual observers and fuzzy fusion estimate road adhesion accurately under longitudinal-lateral coupling, with faster convergence and robust real-time tracking.

When following-vehicle detection fails, the control narrows speed and spacing ranges to prevent excessive changes and keep traffic smooth.

Compares planned vehicle travel with reference vehicle records to detect autonomous driving abnormalities without relying on recognition accuracy.

A model-based inversion controller converts acceleration commands into cruise control settings to improve traffic flow without replacing existing modules.

Precalculated paths and driver-state sensing let autonomous vehicle control accept driver input while avoiding unstable driving states.

Validates autonomous driving trajectories by checking lateral range, lane boundaries, and evasive acceleration to avoid rejecting safe defensive maneuvers.

Aggregated route, powertrain, and automated-mode data enables tailored guidance that improves feature awareness and safer use of automated driving.

ROI lane modeling combines object and lane sensor data to track ego and adjacent lanes when markings are obscured, improving hazard awareness.

An autonomous intermediate driving state smooths control handover between remote and passenger driving while reducing operation interference.

Altering nominal paths only within target zones helps autonomous vehicles handle pickup, drop-off, and turns with lower processing and energy use.

Combined laser and ultrasonic sensing filters noisy weather-driven readings to warn overheight vehicles and cut false alarms.

Structured scenario schemas turn raw vehicle sensor data into agent and motion encodings for more reliable hazard detection in complex environments.

Pressure, temperature, and tire wear state are combined to estimate rolling resistance in real time for better fuel economy and range prediction.

Mobile immersion-cooled computing units restore connectivity during disruptions by deploying autonomous vehicles where capacity is needed.

Pre-applying the parking brake before shift changes prevents unintended vehicle movement during remote parking, even if the foot brake is abnormal.

When GNSS signals drop in road tunnels, onboard sensors and relay vehicles help autonomous vehicles keep navigating and send status reports.

Dynamic shortening of a control transfer region avoids overlap with a vehicle passage region, enabling safer automatic lane changes with less driver intervention.

When an autonomous vehicle stalls in unpredictable crowds, remote guidance temporarily lowers speed and buffer settings to restore safe progress.

Lateral offset sensing helps motorcycle ACC choose the right lead vehicle in staggered group riding, reducing unnecessary braking and discomfort.

Classifying steering torque, angle, and rate lets the vehicle limit overreaction during automated-to-manual handover and maintain stability.