Automatic Initiations TRIZ Cases

Gentle pre-braking before an intersection uses following-vehicle distance and deceleration-area detection to lower rear-end collision risk.

Braking adapts to pedal return, road, traffic, and driver style to preserve gliding feel while recovering energy in single-pedal driving.

Vehicle sensors detect trailer presence independently of interface signals, enabling safer brake control and shorter stopping distances.

Using an onboard acceleration sensor, this case detects ramp contact and stops the vehicle precisely without complex distance sensors.

Braking force is adjusted to reversing risk and pedal input, avoiding collisions with moving objects without unnecessary full braking.

A phased minimum risk maneuver uses gentle braking first, then full stopping if network disturbance persists, reducing rear-end risk.

Braking is adapted from pedal return behavior plus road and traffic states to improve single-pedal comfort, safety, and energy use.

Past braking hotspots from an external device help target alerts and pre-pressurize brakes, reducing nuisance warnings and response time.

Triggered local odometry capture characterizes autonomous robot motion without manual resets or latency-prone transmission, improving test accuracy.

Candidate paths are scored by predicted fallback stop overlap with nearby vehicle trajectories to reduce collision risk during unexpected stops.

A pressure-threshold brake override keeps automatic braking active for light rider input, then switches cleanly to manual control when force rises.

Two-phase pre-stop brake control raises force before reduction to smooth acceleration changes without unnecessarily extending stopping distance.

Differential braking switches between virtual short and inherent wheelbase models to improve low-speed turning while keeping control stable.

RFID-based electronic tie marking improves railroad asset location, crew collision avoidance, and maintenance workflow when GPS is unreliable.

Braking deceleration is adapted to vehicle speed and transverse acceleration to preserve lateral stability while reducing collision risk.

By switching acceleration models based on whether a target will stop before impact, this AEB case improves braking accuracy and avoids harsh stops.

Deceleration data and learned brake-table updates estimate brake wear, helping autonomous vehicles maintain braking force as components degrade.

Dynamic trajectory selection delays maximum braking until needed, balancing obstacle avoidance, passenger comfort, and following-vehicle risk.

A valve-based brake controller hands authority from autonomous braking to the driver and triggers emergency braking during faults or power loss.

A temporary parking brake override uses door, speed, gear, and driver inactivity checks to support maneuvers without untimely brake disabling.

Sensor-based scoring of AEB event handling adapts vehicle countermeasures to driver behavior and surrounding traffic conditions.

Wheel-speed sensing and a solenoid spool valve inhibit trailer brake pressure during low-speed turns, reducing drag and brake complexity.

Separate detection times for main and auxiliary vehicle power supplies enable earlier fault detection while reducing false alarms and circuit complexity.

Continuous target relevance tracking lets emergency braking ramp out smoothly and react faster to new collision threats without resetting warnings.

Selective braking of one front wheel pivots the steering angle during parking or turning to avoid collisions without added steering hardware.

Intermittent friction braking controls downhill overspeed when motor brake torque is insufficient, reducing brake overheating and failure risk.