Optimized path planner for an autonomous valet parking system for a motor vehicle

A method for autonomously parking or un-parking a motor vehicle includes locating the motor vehicle relative to a parking area, selecting a destination location within the parking area, generating a path from the location of the motor vehicle to the destination location, wherein the path includes a plurality of linked nodes, each node having a cost associated therewith, wherein the cost of a child node is equal to an inherited cost plus a base cost and a change cost, wherein the change cost is a function of characteristics of a parent node, and autonomously driving the motor vehicle along the path from the location of the motor vehicle to the destination location.

FIELD

The invention relates generally to autonomous driver assistance systems for motor vehicles, and more particularly to an optimized path planner method for autonomous driver assistance systems for parking and un-parking or retrieving a motor vehicle.

BACKGROUND

Smart car technologies such as free-ranging on grid navigation, as well as parking guidance and information systems, aid in the prevention of human error when drivers operate a vehicle. Such technologies have been used to improve navigation of roadways, and to augment the parking abilities of motor vehicle drivers while the drivers are present within the motor vehicle. For example, rear view camera systems and impact alert systems have been developed to assist the operator of the motor vehicle while parking to avoid collisions. In addition, autonomous parking systems have been developed that autonomously park the motor vehicle in a parallel parking spot once the operator of the motor vehicle has positioned the motor vehicle in a predefined location proximate the parking spot.

While these systems are useful for their intended purpose, they require that the operator of the motor vehicle locate the parking spot and drive to the parking spot. Thus, there is a need in the art for improved smart car technologies that utilize preexisting infrastructure to autonomously park a motor vehicle. Moreover, there is a need to implement automatic parking systems in motor vehicles that are optimized to mimic human drivers by reducing certain behavior patterns that emerge in path planning.

SUMMARY

A method for autonomously parking or un-parking a motor vehicle is provided. The method includes locating the motor vehicle relative to a parking area, selecting a destination location within the parking area, generating a path from the location of the motor vehicle to the destination location, wherein the path includes a plurality of linked nodes, each node having a cost associated therewith, wherein the cost of a child node is equal to an inherited cost plus a base cost and a change cost, wherein the change cost is a function of characteristics of a parent node, and autonomously driving the motor vehicle along the path from the location of the motor vehicle to the destination location.

In one aspect, the change cost includes a turning cost and a direction cost.

In another aspect, the characteristics include a location of the plurality of linked nodes in the parking area and a heading.

In another aspect, the method further includes increasing the turning cost of the child node if a difference between the heading of the parent node and the child node is greater than a predetermined amount.

In another aspect, the method further includes increasing the direction cost of the child node if the parent node required a gear change between forward and reverse the child node also requires a gear change between forward and reverse.

In another aspect, the turning cost is zero if the child node has the same heading as the parent node.

In another aspect, the method further includes the turning cost is a function of a difference between a steering angle of the parent node and a steering angle of the child node.

In another aspect, the method further includes determining whether the location of the child node is within an obstructed area and only generating a path having nodes outside the obstructed area plus a safety factor.

In another aspect, the safety factor is approximately six inches.

In another aspect, the safety factor is a function of the type of obstructed area.

In another aspect, the base cost of the child node is a function a distance from the child node to the destination location.

In another aspect, the base cost of the child node is also a function of a distance from the parent node to the destination location.

In another aspect, the base cost is the difference between the distance from the child node to the destination location and the distance from the parent node to the destination location.

In another aspect, the inherited cost of the child node is equal to the cost of the parent node.

Further aspects, examples, and advantages will become apparent by reference to the following description and appended drawings wherein like reference numbers refer to the same component, element or feature.

DETAILED DESCRIPTION

With reference toFIG. 1, an autonomous valet system according to the principles of the present disclosure is indicated by reference number10. The autonomous valet system10is used with an exemplary motor vehicle12and an exemplary mobile device14. The motor vehicle12is illustrated as a passenger vehicle, however, the motor vehicle12may be a truck, sport utility vehicle, van, motor home, or any other type of vehicle without departing from the scope of the present disclosure. The mobile device14is preferably a mobile phone, however, the mobile device14may be a mobile computer, laptop, tablet, smart watch, or any other device in wireless communication with the motor vehicle12. The autonomous valet system10runs an autonomous valet method or application, as will be described in greater detail below.

The autonomous valet system10is operable to autonomously park and un-park the motor vehicle12. The autonomous valet system10may have various configurations without departing from the scope of the present disclosure but generally includes a sensor sub-system16and a communication sub-system18each in communication with a controller20. The controller20communicates with a vehicle control system22. The sensor sub-system16includes a plurality of sensors24A-D mounted along the periphery of the motor vehicle12. In the example provided, the sensors24A-D are located at the front, left, right, and rear of the motor vehicle12, respectively, to provide 360 degrees of overlapping coverage. However, it should be appreciated that the sensor sub-system16may have any number of sensors24without departing from the scope of the disclosure. Each of the sensors24A-D is operable to collect or sense information in a predefined area surrounding the motor vehicle12. Information from the sensors24A-D is communicated to the controller20. In a preferred embodiment, the sensors24A-D are Light Detection and Ranging (LiDAR) sensors. However, the sensors24A-D may be cameras, radar or sonar sensors, or any other type of proximity sensors. The communication sub-system18includes a receiver/transmitter operable to receive and/or transmit wireless data to the mobile device14. The wireless data is communicated to the controller20. In addition, the communication sub-system18may communicate with other vehicles (vehicle-to-vehicle communication), infrastructure such as a parking lot (vehicle-to-infrastructure), and may receive GPS data.

The controller20is a non-generalized, electronic control device having a preprogrammed digital computer or processor, memory or non-transitory computer readable medium used to store data such as control logic, instructions, image data, lookup tables, etc., and a plurality of input/output peripherals or ports. The processor is configured to execute the control logic or instructions. The controller20may have additional processors or additional integrated circuits in communication with the processor, such as perception logic circuits for analyzing the sensor data.

The controller20may optionally communicate with a human machine interface (HMI)26. The HMI26is disposed within the cabin of the motor vehicle12and is preferably a touch screen accessible by an operator of the motor vehicle12. However, the HMI26may be any haptic, verbal, or gesture control system without departing from the scope of the present disclosure. The HMI26may be used to activate and control the autonomous valet system10. Additionally, the mobile device14may be used to activate and control the autonomous valet system10.

The vehicle control system22includes any systems that implement the autonomous valet functions which include parking and un-parking the motor vehicle12. For example, the vehicle control system22may include a braking control system, throttle control system, steering control system, body control system, etc. The vehicle control system22may also include any advanced driver assistance system (ADAS) functions that automate, adapt, or enhance vehicle systems in order to increase vehicle safety and/or operator driving performance. For example, the vehicle control system22may include ADAS technologies that alert the driver to potential problems or to avoid collisions by implementing safeguards, such as autonomously controlling the motor vehicle12. The vehicle control system22may also include ADAS features that enhance certain systems, such as automated lighting, adaptive cruise control, automated braking, or improved blind spot elimination using camera technology. Finally, it should be appreciated that the vehicle control system22may be part of the autonomous valet system10without departing from the scope of the present disclosure.

Turning toFIG. 2, an exemplary parking area is indicated by reference number30. The parking area30includes a plurality of parking spots32. It should be appreciated that the parking area30may have any configuration, may be a parking structure, and may have any number of parking spots32without departing from the scope of the present disclosure. The parking area30includes a parking area infrastructure34that may communicate with the motor vehicle12.

With reference toFIG. 3, and continued reference toFIGS. 1 and 2, a method for autonomously parking and un-parking the motor vehicle12in the parking area30is indicated by reference number50. By way of example, the method50illustrates parking the motor vehicle12within the parking area30. However, it should be appreciated that the method50may be used identically when un-parking or retrieving the motor vehicle12from the parking area30. The method50begins at step52where an operator of the motor vehicle12initiates or activates the autonomous valet system10using either the HMI26or the mobile device14. For example, when parking, the operator may use the HMI26while during un-parking the operator may use the mobile device14.

At step54, the motor vehicle12is located within, or relative to, the parking area30. The motor vehicle12may be located in the parking area30by positioning the motor vehicle12in a predefined starting location or parking spot or by GPS coordinates. At step56the motor vehicle12communicates with the parking area infrastructure to receive a map of the parking area30. The map may be defined as a Cartesian coordinate system with x and y coordinates. The motor vehicle12is located on the map using (x,y,Θ) coordinates, where e is a steering angle or a heading of the motor vehicle12. At step58, a destination is set in the parking area30. In the example provided, the destination is a parking spot indicated by reference number59inFIG. 2. The destination may be selected by an operator of the motor vehicle12or may be assigned by the parking area infrastructure34based on open or available parking spots32. Alternatively, in an un-park mode, the destination location may be the location of the mobile device14. It should be appreciated that steps54-58may be done in various orders or simultaneously without departing from the scope of the present disclosure.

Next, at step60, a node tree path planner is generated from the location of the motor vehicle12to the destination location59. From the node tree path planner a lowest cost path is selected, as shown by reference number61inFIG. 2. The lowest cost path61operates as a path for the motor vehicle12to take from the starting location to the destination location59. Finally, at step62, the autonomous valet system10drives the mover vehicle along the lowest cost path61using the vehicle control system22. The sensor sub-system16may be used during autonomous driving to avoid obstacles not located in the predefined parking area map, such as pedestrians, other vehicles, etc.

Turning now toFIG. 4, the method of generating the node tree path planner will now be described in greater detail. The node tree path planner begins by generating a first set of nodes, or parent nodes, a1, a2, a3, a4, a5. . . anfrom the starting location Lsof the motor vehicle12. Each node is generated a distance ‘d’ from the starting location Lsat a predefined turn angle φ. It should be appreciated that any number of nodes may be generated however, in a preferred embodiment, nine forward nodes are generated and nine reverse nodes are generated. The distance d may have various values but is preferably approximately 2 meters. The turn angle φ may also have various values but preferably equally divides the nodes from straight ahead to a full right turn and a full left turn. Each of the nodes is defined by (x,y,Θ) coordinates. Next, any nodes that are blocked by the parking area map are removed.

Once the first set of nodes are generated, the node tree path planner assigns a cost to each of the nodes. The cost for each node in the first set is equal to a base cost plus a turning cost. The base cost is a function of the distance from the node to the destination location Ld. Thus, the closer the node is to the destination location Ld, the lower the base cost. The turning cost increases with an increase in the steering angle Θ. In other words, the larger the turn required to reach the node, the greater the cost. If the node is a reverse node that would require the motor vehicle to change gears, an additional reverse cost is added to the node.

Once the nodes have been assigned a cost, the node tree path planner selects the lowest cost node, such as node a5in the example provided, and generates another set of nodes, or child nodes, b1, b2, b3, b4. . . bnfrom the selected lowest cost node. Each of the child nodes are generated at a distance d from the selected lowest cost node (a5) at turn angles φ. Any nodes previously generated nodes are not generated again.

Next, any newly generated nodes are compared to the parking area map or a list of obstructed areas. Any nodes located in areas designated as obstructed by the parking area map are not generated. Moreover, any nodes within a certain distance, or safety factor, from the obstructed areas are not generated. For example, a safety factor of six inches may be used. Thus, the motor vehicle will not be parked or drive too close to obstructed areas. The safety factor may be a function of the type of obstructed area. For example, where the obstructed area is a car, the safety factor may be increased to account for opening doors. Where the obstructed area is a curb, the safety factor may be reduced. Where the obstructed area is simply a boundary line with no real obstructions, the safety factor may be reduced to zero.

Next, costs are assigned to each child node b1, b2, b3, b4. . . bn. The cost of a child node is equal to an inherited cost plus a base cost and a change cost. The inherited cost is the cost of the parent node (a5in the example provided). Thus, the child node inherits the costs of any previously generated nodes linked to the child node. The base cost is a function of the distance from the child node and parent node to the destination location Ld. The change cost is a function of the characteristics of the parent node compared to the child node. For example, the change cost may include a turning cost and a direction cost. In order to discourage serpentine paths or zig-zagging, the turning cost of the child node is increased if a difference between the heading of the parent node and the child node is greater than a predetermined amount. To favor paths that are straight, the turning cost is zero if the child node has the same heading as the parent node. To avoid too many gear changes, the direction cost is used if the parent node required a gear change between forward and reverse and the child node also requires a gear change between forward and reverse. An exemplary cost equation is provided below:
Cchild=Cparent+Dchild−Dparent+Cj[1]

In equation [1], Cchild is the cost of the child node, Cparent is the cost of the parent node, Dchild is a distance from the child node to the destination location Ld, Dparent is a distance from the parent node to the destination location Ld, and Cj is the change cost. The change cost Cj is defined as follows:
Cj=5.0 if gear of child node does not equal gear of parent node  [2]
Cj=1.5 if gear of child node is equal to gear of parent node and heading of child node does not equal heading of parent node  [3]
Cj=1.0 otherwise  [4]

The distance between the child node and the target destination Ldis determined by the following equation:
Dchild=√{square root over ((xchild−xtarget)2+(ychild−ytarget)2)}  [5]

In equation [5], xchild is the x coordinate of the child node, ychild is the y coordinate of the child node, xtarget is the x coordinate of the destination location Ld, and ytarget is the y coordinate of the destination location Ld. The distance between the parent node and the target destination Ld, Dparent, is found in substantially the same way.

In one embodiment, the base cost also includes a generation cost which is a function of which generation the node is from the starting location node. The tree node path planner then selects the lowest cost node from all of the nodes generated thus far and repeats the method until a newly generated node is at the destination location Ld.

Once a node is at the location Ld, the node tree path planner traces the path back to the starting location Lsand sets the path61. Thus, the path61is the lowest cost path with optimized driving characteristics, e.g., reduced turning, gear changes, proximity to other objects, etc. The motor vehicle12may be driven from node to node along the path or may be driven along an average or weighted curve along the path.