SYSTEM FOR INTEGRATING DYNAMICALLY OBSERVED AND STATIC INFORMATION FOR ROUTE PLANNING IN A GRAPH BASED PLANNER
First Claim
1. A method of controlling an autonomous vehicle using a graph representing a plurality of routes the vehicle can travel, the graph comprising a plurality of vertices and a plurality of edges, wherein the vertices represent waypoints and each edge connects a respective two of the vertices, the method comprising:
- controlling operations of the vehicle based at least in part on edge costs, wherein the edge costs are determined by an estimation system and are based on at least one of an estimated travel time for one of the plurality of edges and a traverse-ability of the edge;
sensing conditions of edges the vehicle is traversing; and
based on the sensed conditions, dynamically updating the edge costs for a current traversal from a starting point to a destination.
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Abstract
Methods and systems of controlling an autonomous vehicle are provided. A method comprises controlling operations of the vehicle based at least in part on edge costs. An edge is a representation of a path the vehicle can traverse. Edge costs are determined by an estimation system and are based on at least one of an estimated travel time for an edge and a traverse-ability of the edge. The method further comprises sensing conditions of edges the vehicle is traversing and based on the sensed conditions, dynamically updating the edge costs.
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Citations
20 Claims
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1. A method of controlling an autonomous vehicle using a graph representing a plurality of routes the vehicle can travel, the graph comprising a plurality of vertices and a plurality of edges, wherein the vertices represent waypoints and each edge connects a respective two of the vertices, the method comprising:
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controlling operations of the vehicle based at least in part on edge costs, wherein the edge costs are determined by an estimation system and are based on at least one of an estimated travel time for one of the plurality of edges and a traverse-ability of the edge; sensing conditions of edges the vehicle is traversing; and based on the sensed conditions, dynamically updating the edge costs for a current traversal from a starting point to a destination. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. A method of operating an autonomous vehicle using a graph representing a plurality of routes the vehicle can travel, the graph comprising a plurality of vertices and a plurality of edges, wherein the vertices represent waypoints, the method comprising:
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implementing the graph describing an area to be traversed by the vehicle; connecting the waypoints of the graph with traversable edges; associating edge costs for each edge based at least in part on at least one of a distance of the edge, an estimated time to traverse the edge and traverse-ability of the edge; based on the edge costs of the edges, planning a path to a destination through select edges at a graph-based long term path planner; while traversing through the select edges, updating the edge costs at the graph-based long term path planner based on sensed information relating to conditions of the edges received from a short term planner; and updating the path based on the updated edge costs at the graph-based long term path planner. - View Dependent Claims (11, 12, 13, 14, 15)
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16. An autonomous vehicle, the vehicle comprising:
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a vehicle controller configured to control operations of the vehicle using a graph representing a plurality of routes the vehicle can travel, the graph comprising a plurality of vertices and a plurality of edges, wherein the vertices represent waypoints and each edge connects a respective two of the vertices; a long term planner configured to determine a path set out by waypoints to a destination, wherein the long term planner determines the path based on edge costs associated with the edges that connect the waypoints, sensors configured to sense conditions associated with an edge while traversing the edge; and a short term path planner configured to provide vehicle control directions to the vehicle controller using real-time processed sensor data from the sensors to a next waypoint in the path set out by the long term planner, the short term planner further configured to provide sensed condition signals based on the sensor data to the long term planner, wherein the long term planner is further configured to update edge costs based on the sensed condition signal. - View Dependent Claims (17, 18, 19, 20)
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Specification