Semi-autonomous reverse following vehicle

Abstract

A system and method for reversing a semi-autonomous following vehicle includes obtaining a speed of a lead vehicle that is ahead of and not connected to the following vehicle while the following vehicle is reversing. A method includes estimating a path of the lead vehicle and determining a path of the following vehicle based on the path of the lead vehicle. Longitudinal motion of the following vehicle is controlled based on the speed of the lead vehicle, and lateral motion of the following vehicle is controlled based on the path of the following vehicle.

Description

Technical Field

[0001] The subject disclosure relates to semi-autonomous backing up of a follower vehicle. Background Art

[0002] In the autonomous vehicle space, platooning refers to a group of vehicles communicating with each other to form a row or group, where the lead vehicle controls the speed and each follower vehicle maintains that speed. This configuration can improve travel time and increase lane capacity, for example. An important step in developing a platoon of autonomous vehicles is a master-slave configuration. Under this arrangement, the lead vehicle, including the driver, drives a semi-autonomous unmanned follower vehicle. Therefore, it is desirable to provide semi-autonomous reversing of the follower vehicles. Summary of the invention

[0003] In one exemplary embodiment, a method for reversing a semi-autonomous following vehicle includes obtaining a speed of a lead vehicle that is in front of the following vehicle that is reversing and is not connected to the following vehicle, and estimating a path of the lead vehicle. The method also includes determining a path of the following vehicle based on the path of the lead vehicle, and controlling longitudinal movement of the following vehicle based on the speed of the lead vehicle, and controlling lateral movement of the following vehicle based on the path of the following vehicle.

[0004] In addition to one or more features described herein, the method further includes obtaining, by a processor of the following vehicle, a wheelbase L of the leading vehicle. L and the steering wheel angle SWA of the leading vehicle L , where the speed of the leading vehicle and the wheelbase L of the leading vehicle are obtained L and the steering wheel angle SWA of the leading vehicle L This is achieved via vehicle-to-vehicle (V2V) communications from the lead vehicle.

[0005] In addition to one or more features described herein, estimating the path of the lead vehicle includes determining a turning radius R as:

[0006] in

[0007] SGR is the steering gear ratio, which is the steering wheel angle SWA L Conversion factor between angular displacement and wheel angle.

[0008] In addition to one or more features described herein, estimating the path of the lead vehicle includes generating the following trajectory in an x,y coordinate system:

[0009] R 2 =x 2 +(yR) 2 .

[0010] In addition to one or more features described herein, the method also includes determining, using a processor of the following vehicle, a position of the following vehicle in an x,y coordinate system as follows:

[0011] and

[0012] y f =d*cos(α+ΔYaw), where

[0013] d is the distance between the leading vehicle and the following vehicle, α is the azimuth angle between the leading vehicle and the following vehicle, L f is the wheelbase of the following vehicle, and ΔYaw is the difference between the yaw of the leading vehicle and the yaw of the following vehicle.

[0014] In addition to one or more features described herein, the method also includes determining, using sensors of the following vehicle, a distance d between the lead vehicle and the following vehicle and an orientation angle α between the lead vehicle and the following vehicle.

[0015] In addition to one or more features described herein, the method also includes obtaining a yaw of the lead vehicle via V2V communication, obtaining a yaw of the following vehicle via a sensor, and determining a difference ΔYaw as subtracting the yaw of the lead vehicle from the yaw of the following vehicle.

[0016] In addition to one or more features described herein, determining the path of the following vehicle includes calculating a steering wheel angle SWA of the following vehicle. F , the calculations include determining a yaw of the lead vehicle at a point in the path of the lead vehicle and determining a distance from the follower vehicle to the point in the path of the lead vehicle.

[0017] In addition to one or more features described herein, determining the yaw of the lead vehicle at the point in the path of the lead vehicle includes determining an angle between the point in the path of the lead vehicle and a line tangent to the path of the lead vehicle at the point.

[0018] In addition to one or more of the features described herein, the steering wheel angle SWA of the following vehicle is calculated F Includes the use of tuning parameters as a function of speed.

[0019] In another exemplary embodiment, a system for performing semi-autonomous backing includes a lead vehicle to provide a speed of the lead vehicle through vehicle-to-vehicle (V2V) communication. The system also includes a processor of a following vehicle that is not physically coupled to the lead vehicle. The processor estimates a path of the lead vehicle, determines a path of the following vehicle based on the path of the lead vehicle, and controls longitudinal movement of the following vehicle based on the speed of the lead vehicle and controls lateral movement of the following vehicle based on the path of the following vehicle.

[0020] In addition to one or more features described herein, the processor of the following vehicle obtains the wheelbase L of the leading vehicle through vehicle-to-vehicle (V2V) communication from the leading vehicle. L and the steering wheel angle SWA of the lead vehicle L , the processor of the following vehicle is configured to estimate the path of the lead vehicle by determining the turning radius R:

[0021] in

[0022] SGR is the steering gear ratio, which is the steering wheel angle SWA L Conversion factor between angular displacement and wheel angle.

[0023] In addition to one or more features described herein, the processor of the following vehicle is configured to estimate the path of the lead vehicle by generating a trajectory in an x,y coordinate system as follows:

[0024] R 2 =x 2 +(yR) 2

[0025] In addition to one or more features described herein, the processor of the following vehicle is configured to determine the following position of the following vehicle in an x,y coordinate system:

[0026] and

[0027] y f =d*cos(α+ΔYaw), where

[0028] d is the distance between the leading vehicle and the following vehicle, α is the azimuth angle between the leading vehicle and the following vehicle, L f is the wheelbase of the following vehicle, and ΔYaw is the difference between the yaw of the leading vehicle and the yaw of the following vehicle.

[0029] In addition to one or more features described herein, a processor of the following vehicle uses sensors of the following vehicle to determine a distance d between the lead vehicle and the following vehicle and an orientation angle α between the lead vehicle and the following vehicle.

[0030] In addition to one or more features described herein, a processor of the following vehicle obtains the yaw of the lead vehicle via V2V communication, obtains the yaw of the following vehicle via the sensor, and determines a difference ΔYaw as subtracting the yaw of the lead vehicle from the yaw of the following vehicle.

[0031] In addition to one or more features described herein, the processor of the following vehicle calculates the steering wheel angle SWA of the following vehicle. FThe calculation includes determining a yaw of the lead vehicle at a point in the path of the lead vehicle and determining a distance from the follower vehicle to the point in the path of the lead vehicle.

[0032] In addition to one or more features described herein, a processor of the following vehicle determines the yaw of the lead vehicle at the point in the path of the lead vehicle by determining an angle between the point in the path of the lead vehicle and a line tangent to the path of the lead vehicle at the point.

[0033] In addition to one or more features described herein, the processor of the following vehicle calculates the steering wheel angle SWA of the following vehicle by using the tuning parameters as a function of speed. F .

[0034] The above features and advantages and other features and advantages of the present disclosure will become apparent from the following detailed description when taken in conjunction with the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Other features, advantages and details appear by way of example only in the following detailed description, which refers to the accompanying drawings, in which:

[0036] Figure 1 illustrates semi-autonomous backing up of a following vehicle according to one or more embodiments;

[0037] Figure 2 illustrates parameters for performing path planning for semi-autonomous backing up of a following vehicle according to one or more embodiments; and

[0038] Figure 3 is a flow chart of a method of following a vehicle in reverse according to one or more embodiments. DETAILED DESCRIPTION

[0039] The following description is merely exemplary in nature and is not intended to limit the present disclosure, its application, or uses. It should be understood that throughout the drawings, corresponding reference numerals indicate like or corresponding parts and features.

[0040] As previously described, a lead-follow configuration includes a lead vehicle with a driver and a semi-autonomous, unmanned follower vehicle. Embodiments of the systems and methods detailed herein relate to semi-autonomous backing of a follower vehicle. The follower vehicle may be a trailer housing another vehicle (e.g., a boat, other watercraft, an all-terrain vehicle), a travel trailer, or other unmanned platform that may have previously been physically towed by the lead vehicle. When the follower vehicle follows the lead vehicle, the follower vehicle maintains a specified distance behind the lead vehicle and a specified azimuth or lateral deviation on the path created by the lead vehicle. The follower vehicle maintains the necessary distance and path based on the line of sight between the sensors of the lead vehicle and the follower vehicle, without any physical connection between the two.

[0041] Based on this configuration, during a backing maneuver, the following vehicle actually moves in front of the lead vehicle. Therefore, according to the embodiments detailed herein, the following vehicle must predict and match the movement of the lead vehicle. The following vehicle must match the longitudinal movement (i.e., speed) of the lead vehicle to maintain a minimum distance between the two. According to an exemplary embodiment, this can be achieved through vehicle-to-vehicle (V2V) communication between the lead vehicle and the following vehicle or through the following vehicle's estimate of the speed of the lead vehicle. The following vehicle must also match the lateral movement of the lead vehicle to avoid jackknifing situations (i.e., the lead vehicle and the following vehicle form an acute angle) or other events that cause loss of sight between the sensors of the two vehicles. This can be achieved through V2V communication of the steering angle of the lead vehicle. According to one or more embodiments, the following vehicle uses the steering angle to estimate the path of the lead vehicle and calculates the corresponding path of the following vehicle.

[0042] According to an exemplary embodiment, Figure 1 1 shows a semi-autonomous reverse of a following vehicle 140 according to one or more embodiments. A leading vehicle 100 and a following vehicle 140 are shown. According to an alternative embodiment, Figure 1 The exemplary lead vehicle 100 shown is an automobile 101 , but the lead vehicle 100 may be a truck, agricultural equipment, construction equipment, or any conveyance with a driver. Figure 1 The exemplary following vehicle 140 shown in FIG. 1 is a traveling trailer 141 , but as previously described, the following vehicle 140 may alternatively be any type of unmanned vehicle that may be physically towed prior to a lead-follow configuration.

[0043] The leading vehicle 100 and the following vehicle 140 include sensors 130 that obtain information about the surroundings of the vehicles 100, 140 and provide information about the vehicles 100, 140 themselves. Exemplary sensors 130 include cameras, lidar systems, radio radar systems, ultrasonic sensors, global navigation satellite systems such as global positioning systems, inertial measurement units, gyroscopes, and wheel speed sensors. According to one or more embodiments, the sensors 130 associated with the lateral control of the following vehicle 140, as described in detail, include a yaw sensor in each of the vehicles 100, 140 and a steering wheel angle sensor in at least the vehicle 100. According to an exemplary embodiment, the sensors 130 are indicated on the back of the leading vehicle 100 and at both ends of the following vehicle 140. However, the number and location of the sensors 130 on the leading vehicle 100 or the following vehicle 140 are not limited by the exemplary illustrations. The leading vehicle 100 includes an interface 125 for interacting with the driver. For example, the interface 125 may be part of an infotainment system that includes a display screen and provides a touch screen or other input device to the driver.

[0044] The lead vehicle 100 includes an accelerator pedal 105, a brake pedal 115, and a steering wheel 120, all of which are operated by the driver of the lead vehicle 100. Although the pedals 105, 115 are shown and discussed for purposes of explanation, according to alternative embodiments, knobs, levers, or other control mechanisms may be employed to achieve the same functionality. The lead vehicle 100 includes a controller 110 that controls various aspects of the operation and communications of the lead vehicle 100, either alone or in combination with other processing circuits. For example, the lead vehicle 100 and the following vehicle 140 may perform vehicle-to-vehicle (V2V) communications, exchanging V2V messages 135. As described with reference to Figure 2 As detailed, V2V communications from the lead vehicle 100 may indicate the speed of the lead vehicle 100 and the movement of the steering wheel 120. V2V communications from the following vehicle 140 to the lead vehicle 100 may provide data (e.g., images) obtained using one or more of its sensors 130 (e.g., cameras). For example, images obtained by the lead vehicle 100 from the following vehicle 140 may be displayed to the driver of the lead vehicle 100 by the interface 125 (e.g., an infotainment screen).

[0045] The following vehicle 140 is shown to include a controller 145. The controller 145 of the following vehicle 140 facilitates V2V communication with the lead vehicle 100. The communication may indicate information that the lead vehicle 100 itself cannot readily obtain. For example, because the following vehicle 140 is in front of the lead vehicle 100 in the reverse configuration, the sensors 130 of the following vehicle 140 may detect objects (e.g., pedestrians, other vehicles, walls) that are not yet visible to the sensors 130 of the lead vehicle 100. The following vehicle 140 may warn the lead vehicle 100 through V2V communication that the following vehicle 140 will contact the object if reverse continues. In addition, the following vehicle 140 may warn the lead vehicle 100 of a potential jackknife situation (i.e., the lead vehicle 100 and the following vehicle 140 together form an acute angle). That is, the controller 145 of the following vehicle 140 monitors the angle formed by the combination of the lead vehicle 100 and the following vehicle 140. This monitoring may be based on an estimated path 150 of the lead vehicle 100 and a calculated path 160 of the following vehicle 140 discussed below. If the angle decreases and reaches a predetermined threshold, the following vehicle 140 may issue a warning to the lead vehicle 100 via V2V communication.

[0046] In addition to facilitating V2V communications with the lead vehicle 100, the controller 145 of the following vehicle 140 may also execute and control the reference Figure 2 Implementation of longitudinal control and lateral control discussed (e.g., path planning). Specifically, in addition to obtaining or estimating the speed of the lead vehicle 100, the controller 145 of the following vehicle 140 can estimate the path 150 of the lead vehicle 100 in order to calculate the path 160 of the following vehicle 140. The controller 110 of the lead vehicle 100 and the controller 145 of the following vehicle 140 can both include processing circuitry, which can include application specific integrated circuits (ASICs), electronic circuits, processors (shared, dedicated, or grouped) and memory that executes one or more software or firmware programs, combinational logic circuits, and / or other suitable components that provide the described functionality.

[0047] Figure 2 Parameters for performing path planning for semi-autonomous backing of follower vehicle 140 according to one or more embodiments are shown. Select coordinate system x, y, such as Figure 2 The specific coordinate system may alternatively be that of one of the vehicles 100, 140, at the center of gravity (CoG) of one of the vehicles 100, 140 or elsewhere, or may be selected based on another basis, but the point is to have a common coordinate system when considering all positions, as described below.

[0048] According to an exemplary embodiment, a vehicle bicycle model is generated for the lead vehicle 100 as a lead bicycle model 210 and for the following vehicle 140 as a following bicycle model 220. According to alternative embodiments, other models may be used for determination of the paths 150, 160. The vehicle bicycle model is a known kinematic model representing four wheels, having two wheels, including a steerable front wheel representing two front wheels and a non-steerable rear wheel representing two rear wheels of the vehicle. The wheelbase L, i.e., the distance between the front and rear tires, is used in the bicycle model, but the track width, i.e., the distance between the two front wheels or between the two rear wheels (i.e., the length of the front wheel axle or the rear wheel axle), is typically not part of the model. The steering angle of the front wheel in the bicycle model is the average of the angles between the left and right wheels of an actual vehicle. In the following equation, L L is the wheelbase of the lead vehicle 100, and L F is the wheelbase of the following vehicle 140. The wheelbase value L L and L F Both are provided to the controller 145 of the following vehicle 140 .

[0049] Yaw refers to the deviation of the vehicle direction from the reference orientation (left or right). The yaw angles of the leading vehicle 100 and the following vehicle 140 are Yaw L and Yaw F As previously described, sensors 130 at the lead vehicle 100 and the following vehicle 140 provide the yaw angle. In addition, V2V communication is used to report the yaw angle Yaw of the lead vehicle 100 to the controller 145 of the following vehicle 140. L Yaw L and Yaw F Converted to x, y coordinate system, as shown in the figure. In the exemplary case, the yaw angle of the following vehicle 140 in the x, y coordinate system is 0. The difference ΔYaw is:

[0050] ΔYaw=Yaw F -Yaw L [Equation 1]

[0051] As mentioned above, in addition to the yaw angle Yaw of the leading vehicle 100 L In addition, the steering wheel angle SWA of the leading vehicle 100 L It is also obtained by the controller 145 of the following vehicle 140 via V2V communication. Based on this angle and the wheelbase L of the leading vehicle 100 L , the controller 145 uses the lead bicycle model 210 to determine the turning radius R of the lead vehicle 100 as follows:

[0052]

[0053] In Equation 2, the steering gear ratio (SGR) is the steering wheel angle SWA of the lead vehicle 100 L and the conversion factor between the wheel angle (i.e., the front wheel angle of the leading bicycle model 210). Then, the trajectory of the leading vehicle 100 (i.e., the estimated path 150) is estimated in the x and y coordinate system according to the formula of the circle:

[0054] R 2 =x 2 +(yR) 2 [Equation 3]

[0055] That is, once the steering wheel angle SWA of the leading vehicle 100 is L Once the turning radius R of the leading vehicle 100 is determined, the trajectory of the path 150 can be estimated according to Equation 3. L Likewise, the difference ΔYaw is updated according to Eq. 1.

[0056] As described above, whether reversing or following, the following vehicle 140 maintains a specified distance d from the leading vehicle 100 and a specified azimuth angle or lateral deviation (angle α) from the leading vehicle 100. The following vehicle 140 may use a sensor 130 (e.g., a laser radar system) to determine the distance d and azimuth angle α from the leading vehicle 100. Figure 2 As shown, the azimuth angle α is between the straight line between the front midpoint of the following bicycle model 220 and the rear midpoint of the leading bicycle model 210 and the y-axis ( Figure 2 Based on the distance d and the azimuth angle α, the position of the following vehicle 140 in the x, y coordinate system can be determined as:

[0057]

[0058] y f =d*cos(α+ΔYaw) [Eq. 5]

[0059] exist Figure 2 , the distance d from the rear wheel of the leading bicycle model 210 to the front wheel of the following bicycle model 220 is shown, and the position x of the following bicycle model 220 is shown. f ,y f At the COG of the following bicycle model 220. However, this exemplary embodiment is not intended to be limiting. The position x of the following bicycle model 220 f ,y fThe front wheel or the rear wheel of the following bicycle model 220 may be used instead, and the distance d may be used instead as the distance from different parts of the leading bicycle model 210 to different parts of the following bicycle model 220. The equations according to one or more embodiments will facilitate lateral control of the following vehicle 140 based on any of the alternative embodiments. Typically, sensors 130 (e.g., a lidar system, a camera) on the leading vehicle 100 and the following vehicle 140 facing each other determine the distance d therebetween.

[0060] During the reverse process, the steering wheel angle SWA of the following vehicle 140 controls the lateral movement of the following vehicle 140. F It can be determined as:

[0061]

[0062] In an alternative embodiment, the steering wheel angle of the following vehicle 140 SWAF can be calculated using another known method, such as pure tracking. Equation 6 relates to the speed of the lead vehicle 100, which is provided to the controller 145 of the following vehicle 140 via V2V communication based on the speedometer of the lead vehicle 100, or determined by one or more sensors 130 of the following vehicle 140 according to an alternative embodiment.

[0063] Yaw of path 150 path The yaw of the lead vehicle 100 at a point x', y' on the path 150 as the lead vehicle 100 travels on the path 150. path is obtained as the angle α between the tangent line T and a circle. The circle defines the path 150 according to Equation 3 at the point x', y', which is usually the closest point of the path 150 to the following vehicle 140. For example, it can be obtained from Equation 3 by setting y'=y f Solving for x' to obtain this point x', y' along the path 150 (i.e., placing the lead vehicle 100 further back on the path 150 at the location of the follower vehicle 140). The distance d to the path 150 is path is the position x of the following vehicle 140 f ,y f The distance to the path 150 defined by the circle in Equation 3. That is, to the path 150d path The distance from position x f ,y fThe distance to the point x', y' on the path 150 (i.e., on the circle defined by Equation 3). In Equation 6, k1 and k2 are tuning parameters. Specifically, k1 and k2 are functions of velocity and also depend on the kinematics and dynamics of the following vehicle 140. These values ​​can be determined by testing, for example, to obtain a specific response of the controller 145 of the following vehicle 140 (i.e., correcting the lateral offset error within a predetermined time).

[0064] The steering wheel angle SWA of the following vehicle 140 is obtained according to Equation 6 F The path 160 of the following vehicle 140 based on equations 2 and 3 is provided. That is, the turning radius of the following vehicle 140 is calculated using the wheelbase L of the following vehicle 140. F and the steering wheel angle SWA of the following vehicle 140 F is obtained in Equation 2. Equation 3 can then be used to obtain the equation for path 160.

[0065] Figure 3 1 is a flow chart of a method 300 for reversing a following vehicle 140 according to one or more embodiments. In block 310, the controller 145 of the following vehicle 140 obtains information about the leading vehicle 100. For example, the information may be obtained through V2V communication. The information may include the speed, yaw, and L , the wheelbase L of the leading vehicle 100 L and the steering wheel angle SWA of the leading vehicle 100 L At block 320 , the following vehicle 140 determines a distance d from the leading vehicle 100 and an angle α from the leading vehicle 100 . For example, this determination may be repeated periodically. As previously described, this information may be obtained by sensors 130 (eg, a lidar system) of the following vehicle 140 .

[0066] At block 330 , the turning radius R is calculated according to equations 2 and 3 and a formula for the path 150 of the lead vehicle 100 is obtained. At block 340 , the position x of the following vehicle 140 is determined. f ,y f This is done in the same coordinate system x,y used to determine the path 150 of the lead vehicle 100. This determination uses equations 4 and 5. At block 350, the steering wheel angle SWA of the following vehicle 140 is determined according to equation 6 F In block 360 , the following vehicle 140 is controlled during the reverse process based on the speed of the leading vehicle 100 and the steering wheel angle SWA of the following vehicle 140 FThe speed of the following vehicle 140 will be set to closely match the speed of the leading vehicle 100. Specifically, for example, the speed of the following vehicle 140 may be set to be a predetermined amount lower than the speed of the leading vehicle 100, or may be maintained within a threshold range of the speed of the leading vehicle 100.

[0067] Figure 3 The method 300 detailed in FIG. 3 represents a semi-autonomous backing process because the controller 145 of the following vehicle 100 uses information from the lead vehicle 100 to ultimately back up the following vehicle 140. During the process of backing up the lead vehicle 100 and the following vehicle 140, the processes 310 to 360 are repeated. According to alternative embodiments, such repetitions may be event-based or periodic. For example, a change in one of the values ​​(e.g., a V2V message from the lead vehicle 100 reporting a different steering wheel angle SWA of the lead vehicle 100) may cause the controller 145 of the following vehicle 100 to use information from the lead vehicle 100 to ultimately back up the following vehicle 140. L , determine different distances d) can trigger Figure 3 Re-execution of the process shown. Alternatively, all values ​​at blocks 310 and 320 may be obtained and these determinations may be repeated periodically.

[0068] Although the above disclosure has been described with reference to exemplary embodiments, it will be appreciated by those skilled in the art that various changes may be made and equivalents may be substituted for its elements without departing from the scope of the present invention. In addition, many modifications may be made to adapt specific circumstances or materials to the teachings of the present disclosure without departing from the basic scope of the present disclosure. Therefore, it is intended that the present disclosure is not limited to the specific embodiments disclosed, but will include all embodiments falling within its scope.

Claims

1. A method for reversing a semi-autonomous following vehicle, the method comprising: obtaining, by a processor of the following vehicle, a speed of a lead vehicle that is in front of the following vehicle that is reversing and is not connected to the following vehicle; estimating, by a processor of the following vehicle, a path of the lead vehicle; determining, by a processor of the following vehicle, a path of the following vehicle based on the path of the lead vehicle; and controlling, via a processor of the following vehicle, longitudinal movement of the following vehicle based on a speed of the lead vehicle and lateral movement of the following vehicle based on a path of the following vehicle; The wheelbase L of the leading vehicle is obtained by the processor of the following vehicle L and the steering wheel angle SWA of the leading vehicle L , where the speed of the leading vehicle and the wheelbase L of the leading vehicle are obtained L and the steering wheel angle SWA of the leading vehicle L The method is accomplished via vehicle-to-vehicle (V2V) communications from a lead vehicle, wherein estimating the path of the lead vehicle includes determining a turning radius R and generating a trajectory in an x,y coordinate system, wherein the method further includes determining a position of the follower vehicle in the x,y coordinate system using a processor of the follower vehicle.

2. The method of claim 1 , further comprising, wherein estimating the path of the lead vehicle comprises determining the turning radius R: in SGR is the steering gear ratio, which is the steering wheel angle SWA L and a conversion factor between the wheel angle, estimating the path of the lead vehicle comprises generating the trajectory in the x, y coordinate system according to the following equation: R 2 =x 2 +(yR) 2 ,and The method includes determining, using a processor of the following vehicle, the position of the following vehicle in the x,y coordinate system according to the following equation: and y f =d*cos(α+ΔYaw), where d is the distance between the leading vehicle and the following vehicle, α is the azimuth angle between the leading vehicle and the following vehicle, L f is the wheelbase of the following vehicle, and ΔYaw is the difference between the yaw of the leading vehicle and the yaw of the following vehicle. 3 . The method of claim 2 , further comprising determining a distance d between the lead vehicle and the following vehicle and an azimuth angle α between the lead vehicle and the following vehicle using sensors of the following vehicle.

4. The method of claim 2, further comprising obtaining a yaw of the lead vehicle through V2V communication, obtaining a yaw of the following vehicle through a sensor, and determining the difference ΔYaw as subtracting the yaw of the lead vehicle from the yaw of the following vehicle.

5. The method of claim 2, wherein determining the path of the following vehicle comprises calculating a steering wheel angle SWA of the following vehicle. F The calculation includes determining the yaw of the lead vehicle at a point in the path of the lead vehicle and determining the distance from the following vehicle to the point in the path of the lead vehicle, wherein determining the yaw of the lead vehicle at the point in the path of the lead vehicle includes determining: an angle between the path of the lead vehicle and a line tangent to the path of the lead vehicle at the point in the path, and calculating a steering wheel angle SWA of the following vehicle F Includes the use of tuning parameters as a function of speed.

6. A system for performing semi-autonomous reversing, the system comprising: a lead vehicle configured to provide a speed of the lead vehicle via vehicle-to-vehicle (V2V) communications; and a processor of the following vehicle that is not physically coupled to the lead vehicle and is configured to estimate a path of the lead vehicle, determine a path of the following vehicle based on the path of the lead vehicle, and control longitudinal movement of the following vehicle based on a speed of the lead vehicle and control lateral movement of the following vehicle based on the path of the following vehicle; The processor of the following vehicle is configured to obtain the wheelbase L of the leading vehicle via vehicle-to-vehicle (V2V) communication from the leading vehicle. L and the steering wheel angle SWA of the lead vehicle L , to estimate the path of the lead vehicle by the turning radius R, to estimate the path of the lead vehicle by generating a trajectory in an x,y coordinate system, and to determine the position of the following vehicle in the x,y coordinate system.

7. The system according to claim 6, wherein: The processor of the following vehicle is configured to estimate the path of the leading vehicle by determining the turning radius R according to the following formula: in SGR is the steering gear ratio, which is the steering wheel angle SWA L and a conversion factor between the wheel angles, the processor of the following vehicle is configured to estimate the path of the leading vehicle by generating the trajectory in the x,y coordinate system according to the following formula, wherein: R 2 =x 2 +(yR) 2 ,and The processor of the following vehicle is configured to determine the position of the following vehicle in the x, y coordinate system according to the following formula: and y f =d*cos(α+ΔYaw), where d is the distance between the leading vehicle and the following vehicle, α is the azimuth angle between the leading vehicle and the following vehicle, L f is the wheelbase of the following vehicle, and ΔYaw is the difference between the yaw of the leading vehicle and the yaw of the following vehicle.

8. The system according to claim 7, wherein: The processor of the following vehicle is configured to determine a distance d between the lead vehicle and the following vehicle and an orientation angle α between the lead vehicle and the following vehicle using sensors of the following vehicle.

9. The system according to claim 7, wherein: The processor of the following vehicle is configured to obtain the yaw of the lead vehicle via V2V communication, obtain the yaw of the following vehicle via the sensor, and determine the difference ΔYaw as subtracting the yaw of the lead vehicle from the yaw of the following vehicle.

10. The system according to claim 7, wherein: The processor of the following vehicle is configured to calculate the steering wheel angle SWA of the following vehicle F The calculation includes determining a yaw of the lead vehicle at a point in the path of the lead vehicle and determining a distance from the follower vehicle to the point in the path of the lead vehicle, the processor of the follower vehicle being configured to determine the yaw of the lead vehicle at the point in the path of the lead vehicle by determining an angle between the point in the path of the lead vehicle and a line tangent to the path of the lead vehicle at the point, and the processor of the follower vehicle being configured to calculate a steering wheel angle SWA of the follower vehicle by using a tuning parameter as a function of speed. F .

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