Method for determining an evasive path for a host vehicle
First Claim
1. A method, comprising:
- detecting a traffic object that is external to a host vehicle in an external environment vehicle by one or more sensors of the host vehicle; and
causing a processor of the host vehicle or an electronic control unit of the host vehicle to, in response to the detecting of the traffic object by the one or more sensors, perform the steps of;
establishing a predicted traffic environment of the host vehicle in a time-lateral position domain, the predicted traffic environment comprising an object prediction representation of the traffic object,determining a start node for the host vehicle, the start node representing a start time and a start lateral position in the predicted traffic environment,defining an end node for the host vehicle, the end node representing an end time in the predicted traffic environment,placing several boundary nodes relative to the object prediction representation in the predicted traffic environment between the start node and the end node, wherein the object prediction representation of the traffic object includes a set of points connected by straight lines in the time-lateral position domain, and wherein each boundary node is placed a predetermined lateral distance from a respective corner of the object prediction representation,setting node connections between the start node, the boundary nodes, and the end node, thereby defining a connectivity map with possible node connections in the predicted traffic environment, andtraversing the start node, the boundary nodes, and the end node using a graph-search algorithm in order to find a path from the start node to the end node with a lowest cost, whereby the path with the lowest cost is selected as an evasive path associated with the host vehicle, wherein the lowest cost is a lowest cost of maximum lateral jerk, a lowest cost of maximum lateral acceleration, or a lowest cost of a sum of lateral movement.
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Abstract
The present invention relates to a method for determining an evasive path for a host vehicle (10), the method i.a. comprising: establishing (S1) a predicted traffic environment (12) of the host vehicle in a time-lateral position domain, the predicted traffic environment comprising an object prediction representation (16) of a traffic object; determining (S2) a start node (24) for the host vehicle; defining (S3) an end node (26) for the host vehicle; placing (S4) several boundary nodes (28) relative to the object prediction representation; setting (S5) node connections (30, 32, 34a-b, 36a-b, 38, 40, 42) between the start node, the boundary nodes, and the end node; and traversing (S6) the nodes using a graph-search algorithm in order to find a path from the start node to the end time with a lowest cost.
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Citations
17 Claims
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1. A method, comprising:
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detecting a traffic object that is external to a host vehicle in an external environment vehicle by one or more sensors of the host vehicle; and causing a processor of the host vehicle or an electronic control unit of the host vehicle to, in response to the detecting of the traffic object by the one or more sensors, perform the steps of; establishing a predicted traffic environment of the host vehicle in a time-lateral position domain, the predicted traffic environment comprising an object prediction representation of the traffic object, determining a start node for the host vehicle, the start node representing a start time and a start lateral position in the predicted traffic environment, defining an end node for the host vehicle, the end node representing an end time in the predicted traffic environment, placing several boundary nodes relative to the object prediction representation in the predicted traffic environment between the start node and the end node, wherein the object prediction representation of the traffic object includes a set of points connected by straight lines in the time-lateral position domain, and wherein each boundary node is placed a predetermined lateral distance from a respective corner of the object prediction representation, setting node connections between the start node, the boundary nodes, and the end node, thereby defining a connectivity map with possible node connections in the predicted traffic environment, and traversing the start node, the boundary nodes, and the end node using a graph-search algorithm in order to find a path from the start node to the end node with a lowest cost, whereby the path with the lowest cost is selected as an evasive path associated with the host vehicle, wherein the lowest cost is a lowest cost of maximum lateral jerk, a lowest cost of maximum lateral acceleration, or a lowest cost of a sum of lateral movement. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12)
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13. A non-transitory computer program product comprising code configured to, when executed by a processor or an electronic control unit, perform a method, the method comprising:
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establishing a predicted traffic environment of a host vehicle in a time-lateral position domain; establishing an object prediction representation of a traffic object in the predicted traffic environment based on detection of the traffic object in an external environment by one or more sensors of the host vehicle, the traffic object and the external environment being external to the host vehicle, determining a start node associated with the host vehicle in the predicted traffic environment, the start node representing a start time and a start lateral position in the predicted traffic environment, defining an end node associated with the host vehicle, the end node representing an end time in the predicted traffic environment, establishing a plurality of boundary nodes relative to the object prediction representation in the predicted traffic environment between the start node and the end node, wherein the object prediction representation of the traffic object includes a set of points connected by straight lines in the time-lateral position domain, and wherein each boundary node is placed a particular lateral distance from a respective corner of the object prediction representation; setting node connections between the start node, the boundary nodes, and the end node, thereby defining a connectivity map with possible node connections in the predicted traffic environment, and traversing the start node, the boundary nodes, and the end node using a graph-search algorithm in order to find a path from the start node to the end node that is associated with a lowest cost, whereby the path with the lowest cost is selected as an evasive path associated with the host vehicle, wherein the lowest cost is a lowest cost of maximum lateral jerk, a lowest cost of maximum lateral acceleration, or a lowest cost of a sum of lateral movement. - View Dependent Claims (14, 15)
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16. A vehicle comprising:
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one or more sensors configured to detect a traffic object that is external to the vehicle in an external environment that is external to the vehicle; and an electronic control unit configured to; establish a predicted traffic environment of the vehicle in a time-lateral position domain, establish an object prediction representation of the traffic object in the predicted traffic environment based on the detection of the traffic object by the one or more sensors, determine a start node associated with the vehicle in the predicted traffic environment, the start node representing a start time and a start lateral position in the predicted traffic environment, define an end node associated with the vehicle, the end node representing an end time in the predicted traffic environment, establish a plurality of boundary nodes relative to the object prediction representation in the predicted traffic environment between the start node and the end node, wherein the object prediction representation of the traffic object includes a set of points connected by straight lines in the time-lateral position domain, and wherein each boundary node is placed a particular lateral distance from a respective corner of the object prediction representation; set node connections between the start node, the boundary nodes, and the end node, thereby defining a connectivity map with possible node connections in the predicted traffic environment, and traverse the start node, the boundary nodes, and the end node using a graph-search algorithm in order to find a path from the start node to the end node that is associated with a lowest cost, whereby the path with the lowest cost is selected as an evasive path associated with the vehicle, wherein the lowest cost is a lowest cost of maximum lateral jerk, a lowest cost of maximum lateral acceleration, or a lowest cost of a sum of lateral movement. - View Dependent Claims (17)
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Specification