XYZ MOTION PLANNING FOR VEHICLES
Methods and systems are presented for planning and commanding motions of a vehicle in the plane of a road and in the vertical direction, relative to the plane of a road, to enhance vehicle performance, as it may relate to, for example, vehicle safety, occupant comfort, wear and tear on the vehicle, and/or vehicle efficiency. One or more processors may be used to plan XYZ vehicle trajectories and to provide commands to systems such as, for example, active suspension systems, semi-active suspension systems, propulsion systems, braking systems (e.g. ABS), and/or steering systems. The one or more processors may also receive road information from, for example, look-ahead sensors (e.g. LiDAR), local or remote databases, and motion sensors (e.g. IMUs, accelerometers). The one or more processors may also exchange information with a driver and/or other vehicle occupants, various on-board or remote databases, and/or infrastructure systems (e.g. GPS) by means of one or more communication devices.
1 . A method of operating a vehicle, the method comprising:
traveling along a road;
receiving information about a segment of the road ahead of the vehicle, wherein the information includes data about a surface of the road ahead of a current position of the vehicle;
based on the received information, using an algorithm to develop a multiplicity of feasible motion plans for moving forward from the current position of the vehicle;
developing one or more trajectories for each of the multiplicity of feasible motion plans, wherein at least one of the one or more trajectories accounts for out of plane motions induced by one or more anomalies in the road surface;
projecting a cost of traveling along each of the one or more trajectories for each of the multiplicity of feasible motion plans;
selecting a trajectory based at least partially on cost;
providing the selected trajectory to a vehicle operator; and
operating the vehicle by implementing the selected trajectory.
2 . The method of claim 1 , wherein the vehicle operator is selected from the group consisting of a computing device and a person.
3 . The method of claim 1 , wherein at least a portion of the received data is received from a database that includes previously collected information about the road.
4 . The method of claim 1 , wherein at least a portion of the received data is received from a look-ahead sensor on-board the vehicle.
5 . The method of claim 1 , wherein the vehicle is a semi-autonomous vehicle.
6 . The method of claim 1 , wherein the data about the surface of the road includes data about road surface anomalies selected from the group consisting of a pothole, a speed bump, a road surface crack, a manhole cover, and a storm grate.
7 . The method of claim 1 , wherein projecting the cost is based on a factor selected from the group consisting of energy consumption; travel time, occupant comfort, violation of traffic regulations, wear and tear of components, safety and environmental impact.
8 . The method of claim 1 , wherein the multiplicity of feasible motion plans does not include a plan where a probability of collision with another vehicle is greater than a threshold value.
9 . The method of claim 1 , wherein the multiplicity of feasible motion plans does not include a plan where a probability of collision with an obstacle.
10 . A method of operating a vehicle the method comprising:
traveling along a road;
receiving information about a segment of the road ahead of the vehicle, wherein the information includes data about a surface of the road ahead of a current position of the vehicle;
based on the received information, using an algorithm to develop a multiplicity of feasible motion plans for moving forward from the current position of the vehicle;
developing one or more trajectories for each of the multiplicity of feasible motion plans, wherein at least one of the one or more trajectories accounts for out of plane motions induced by the road surface;
projecting a cost for traveling along each of the one or more trajectories for each of the multiplicity of feasible motion plans;
determining a probability of collision, with another vehicle, when implementing a lowest cost trajectory, is greater than a threshold value; and
operating the vehicle by implementing a trajectory with a next lowest cost trajectory where the probability of collision is lower than the threshold value.
11 . The method of claim 10 , wherein the vehicle operator is selected from the group consisting of a computing device and a person.
12 . The method of claim 9 , wherein at least a portion of the received data is received from a database that includes previously collected information about the road.
13 . The method of claim 9 , wherein at least a portion of the received data is received from a look-ahead sensor on-board the vehicle.
14 . The method of claim 9 , wherein the vehicle is a semi-autonomous vehicle.
15 . The method of claim 9 , wherein the data about the surface of the road includes data about road surface anomalies selected from the group consisting of a pothole, a speed bump, a road surface crack, a manhole cover, and a storm grate.
16 . The method of claim 9 , wherein projecting the cost is based on a factor selected from the group consisting of energy consumption; travel time, occupant comfort, violation of traffic regulations, wear and tear of components, safety and environmental impact.
17 . A method of operating a vehicle, the method comprising:
traveling along a road;
receiving information about a segment of the road ahead a current position of the vehicle;
based on the received information, selecting a trajectory with a duration of less than two minutes, wherein the trajectory includes both XY motions and Z motions;
providing the trajectory to a vehicle operator; and
operating the vehicle by implementing the trajectory.
18 . The method of claim 17 , wherein the duration is less than one minute.
19 . The method of claim 17 , wherein the duration is less than thirty seconds.
20 . A method of operating a vehicle, the method comprising:
traveling along a road;
receiving information about a lateral distribution of an anticipated intensity of an adverse effect on the vehicle at a series of discrete longitudinal positions of the road;
receiving at least one constraint limiting an operation of the vehicle;
calculating a cost function based on the intensity and the at least one constraint; and
traversing each of the longitudinal positions at a point determined based on the cost function.
21 . The method of claim 20 , wherein the at least one constraint is selected from the group consisting of prohibition from leaving a lane of travel, offset from a centerline of the lane of travel, and maximum lateral acceleration.