Abstract: The present disclosure involves systems and methods for detecting road blockages and generating alternative routes. In some cases, a system detects, based at least in part on sensor data associated with an autonomous vehicle, a portion of an environment that impedes a planned path of the autonomous vehicle. The system determines a semantic classification associated with the portion of the environment and transmits a re-routing request comprising the semantic classification to one or more remote computing devices. The system receives an instruction associated with navigating the autonomous vehicle around the portion of the environment from the remote computing devices, where the instruction includes an alternative route determined from a plurality of alternative routes. The system further controls the autonomous vehicle to navigate around the portion of the environment based at least in part on the instruction.

Abstract: The present disclosure involves systems and methods for detecting road blockages and generating alternative routes. In some cases, a system detects, based at least in part on sensor data associated with an autonomous vehicle, a portion of an environment that impedes a planned path of the autonomous vehicle. The system determines a semantic classification associated with the portion of the environment and transmits a re-routing request comprising the semantic classification to one or more remote computing devices. The system receives an instruction associated with navigating the autonomous vehicle around the portion of the environment from the remote computing devices, where the instruction includes an alternative route determined from a plurality of alternative routes. The system further controls the autonomous vehicle to navigate around the portion of the environment based at least in part on the instruction.

Abstract: Techniques for identifying road segments associated with an object trajectory are discussed herein. A computing device can implement a model that extracts points from an object trajectory and identifies road segments along a path between the extracted points. The model can determine a set of road segments for the path based on searching a graph. The graph can comprise nodes to represent different road segments, and a graph search algorithm can output road segments representing a shortest path between the nodes associated with the extracted points. The road segments can be used by a vehicle computing device for predicting vehicle actions to control a vehicle.

Abstract: Techniques and methods for determining a distance between a point within an environment and a reference line are discussed herein. For instance, a vehicle may be navigating. While navigating, the vehicle may receive a reference line that represents a road segment and determine various regions relative to the reference line. Additionally, the vehicle may generate sensor data representing the environment and identify an object using the sensor data. The vehicle may then determine that a location of the object corresponds to a region from the regions. Based on the region, the vehicle may determine a rule for identifying the distance between the vehicle and the reference line. The vehicle may then determine the distance using the rule, the location of the object, and the reference line. Additionally, the vehicle may determine an action for the vehicle to perform that is based on the distance.

Abstract: The present disclosure involves systems and methods for detecting road blockages and generating alternative routes. In some cases, a system detects, based at least in part on sensor data associated with an autonomous vehicle, a portion of an environment that impedes a planned path of the autonomous vehicle. The system determines a semantic classification associated with the portion of the environment and transmits a re-routing request comprising the semantic classification to one or more remote computing devices. The system receives an instruction associated with navigating the autonomous vehicle around the portion of the environment from the remote computing devices, where the instruction includes an alternative route determined from a plurality of alternative routes. The system further controls the autonomous vehicle to navigate around the portion of the environment based at least in part on the instruction.