Determining portions of a roadway model requiring updating

摘要

A computer-implemented method for determining which portions of a roadway model used by self-driving road vehicles require updating uses discrepancy data derived from the sensors of a plurality of self-driving road vehicles. The discrepancy data may indicate discrepancies between the sensor data and the roadway model, or may indicate portions of the roadway where a self-driving road vehicle underperformed. The discrepancy data is aggregated, and the aggregated discrepancy data is used to identify, as the portions of the roadway model which require updating, those portions of the roadway model corresponding to portions of the roadway for which the aggregated discrepancy data exceeds a threshold.

主权项

1. A computer-implemented method for determining which portions of a roadway model representing a real-world roadway require updating, the method comprising:
maintaining a roadway model of the real-world roadway, the roadway model being sufficient to enable autonomous driverless operation of a self-driving road vehicle; receiving, from a plurality of self-driving road vehicles on the roadway, discrepancy data for known positions on the roadway; aggregating the discrepancy data into aggregated discrepancy data, wherein the aggregated discrepancy data comprises, for at least some portions of the roadway, discrepancy data from a plurality of individual self-driving road vehicles; using the aggregated discrepancy data to identify, as the portions of the roadway model which require updating, those portions of the roadway model corresponding to portions of the roadway for which the aggregated discrepancy data exceeds a threshold; and responsive to identifying the portions of the roadway model which require updating, doing at least one of:
dispatching one or more survey vehicles to the portions of the roadway for which the aggregated discrepancy data exceeds the threshold; andmodifying an existing plan for updating the roadway model to include the portions of the roadway for which the aggregated discrepancy data exceeds the threshold.