Probability-based obstacle avoidance

This invention describes a vehicle safety system that uses sensor data to detect potential hazards. It compares these hazards against a database of known obstacles, which includes information about how likely it is to encounter them in different places and at different times. Based on this, the system calculates a 'probability index' for the current hazard and decides whether the vehicle needs to change its path to avoid a collision. The claims specifically narrow this to using estimated spatial and temporal probabilities to determine the likelihood of encountering a hazard.

Why it matters: Filed before significant advancements in machine learning for real-time predictive modeling. The ability to dynamically generate and update complex spatial and temporal probability distributions for diverse obstacles has become more robust and efficient with improved ML algorithms and edge computing capabilities since 2021.

Status: Not in forceListed as no longer active. The specific reason is not in the record we hold.
How hard to build: SpecializedMachine learning, real-time processing, sensor integration

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