Patent Publication Number: US-11046321-B2

Title: Adaptive control of automated lane change in vehicle

Description:
The subject disclosure relates to adaptive control of an automated lane change in a vehicle. 
     Vehicles (e.g., automobiles, trucks, construction equipment, farm equipment, automated factory equipment) are increasingly equipped with sensors that provide information about the vehicle and its surroundings. These sensors (e.g., cameras, radar systems, lidar systems) have enabled automation of aspects of vehicle operation or entirely autonomous vehicle operation. Lane change, during which a vehicle transitions between two lanes with traffic travelling in the same direction, is an aspect of vehicle operation that has been automated. Automated lane change may be part of autonomous driving or semi-autonomous driving (e.g., hands-free driving). Accordingly, it is desirable to provide adaptive control of an automated lane change in a vehicle. 
     SUMMARY 
     In one exemplary embodiment, a method of performing adaptive control of an automated lane change in a vehicle includes positioning a target vehicle with a target speed in a target lane at a target distance behind the vehicle. The target speed is greater than a speed of the vehicle, and the vehicle will move into the target lane based on the automated lane change. The method also includes determining a deceleration needed by the target vehicle over a braking distance, which is less than the target distance, to match the speed of the vehicle, and determining whether the deceleration exceeds a threshold deceleration. The automated lane change is prohibited based on the deceleration exceeding the threshold deceleration. 
     In addition to one or more of the features described herein, the method also includes determining the target distance as a maximum detection range of one or more sensors of the vehicle. 
     In addition to one or more of the features described herein, the method also includes determining the target distance as a distance less than a maximum detection range of one or more sensors of the vehicle based on detecting a following vehicle behind the vehicle. 
     In addition to one or more of the features described herein, the method also includes determining the target distance based on a location of the one or more sensors of the vehicle, a distance between the vehicle and the following vehicle, and a width of the following vehicle. 
     In addition to one or more of the features described herein, the method also includes determining the target speed as a fixed value above a posted speed limit for the target lane. 
     In addition to one or more of the features described herein, the method also includes determining a recognition distance as a distance traveled by the target vehicle in a fixed period of time. 
     In addition to one or more of the features described herein, the method also includes determining the braking distance as the recognition distance and a pre-defined buffer distance subtracted from the target distance. 
     In addition to one or more of the features described herein, the determining the deceleration needed by the target vehicle is based on the target speed T being an initial speed, the speed of the vehicle S being a final speed, and a distance for the deceleration being the braking distance D. 
     In addition to one or more of the features described herein, the determining the deceleration needed by the target vehicle includes computing: 
     
       
         
           
             
               
                 
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     In addition to one or more of the features described herein, the method also includes allowing the automated lane change based on the deceleration being less than or equal to the threshold deceleration. 
     In another exemplary embodiment, a system to perform adaptive control of an automated lane change in a vehicle includes one or more sensors to detect objects behind the vehicle, and a processor to position a target vehicle with a target speed in a target lane at a target distance behind the vehicle. The target speed is greater than a speed of the vehicle, and the vehicle will move into the target lane based on the automated lane change. The processor additionally determines a deceleration needed by the target vehicle over a braking distance, which is less than the target distance, to match the speed of the vehicle, determines whether the deceleration exceeds a threshold deceleration, and prohibits the automated lane change based on the deceleration exceeding the threshold deceleration. 
     In addition to one or more of the features described herein, the processor determines the target distance as a maximum detection range of one or more sensors of the vehicle. 
     In addition to one or more of the features described herein, the processor determines the target distance as a distance less than a maximum detection range of one or more sensors of the vehicle based on detecting a following vehicle behind the vehicle. 
     In addition to one or more of the features described herein, the processor determines the target distance based on a location of the one or more sensors of the vehicle, a distance between the vehicle and the following vehicle, and a width of the following vehicle. 
     In addition to one or more of the features described herein, the processor determines the target speed as a fixed value above a posted speed limit for the target lane. 
     In addition to one or more of the features described herein, the processor determines a recognition distance as a distance traveled by the target vehicle in a fixed period of time. 
     In addition to one or more of the features described herein, the processor determines the braking distance as the recognition distance and a pre-defined buffer distance subtracted from the target distance. 
     In addition to one or more of the features described herein, the processor determines the deceleration needed by the target vehicle is based on the target speed T being an initial speed, the speed of the vehicle S being a final speed, and a distance for the deceleration being the braking distance D. 
     In addition to one or more of the features described herein, the processor determines the deceleration needed by the target vehicle based on computing: 
     
       
         
           
             
               
                 
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     In addition to one or more of the features described herein, the processor allows the automated lane change based on the deceleration being less than or equal to the threshold deceleration. 
     The above features and advantages, and other features and advantages of the disclosure are readily apparent from the following detailed description when taken in connection with the accompanying drawings. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       Other features, advantages and details appear, by way of example only, in the following detailed description, the detailed description referring to the drawings in which: 
         FIG. 1  is a block diagram of a vehicle that includes adaptive control of an automated lane change; 
         FIG. 2  is a block diagram that illustrates the process of performing adaptive control of an automated lane change according to one or more embodiments; 
         FIG. 3  is a process flow of a method of performing adaptive control of an automated lane change according to one or more embodiments; and 
         FIG. 4  illustrates an exemplary scenario in which adaptive control of an automated lane change is performed according to one or more embodiments. 
     
    
    
     DETAILED DESCRIPTION 
     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. 
     As previously noted, automated lane change operations may be part of autonomous or semi-autonomous operation of a vehicle. Typically, a lane change may be undertaken when the adjacent lane, into which the vehicle will move, is free of obstructions. That is, the position of other vehicles or any objects within the field of view of vehicle sensors (e.g., cameras) is determined. If no other vehicles or other objects are in the path of the lane change, it is undertaken. However, considering only the objects within the field of view to determine whether an automated lane change may be undertaken may be problematic under certain circumstances. For example, for an automated lane change from a first lane into a second lane, even if it is determined that there are no objects in the second lane according to the field of view of the sensors of the vehicle, a fast-moving vehicle may be just outside the field of view. This fast-moving vehicle may be forced to brake excessively (e.g., more than an established threshold amount) in order to avoid a collision based on the lane change. Embodiments of the systems and methods detailed herein relate to adaptive control of an automated lane change in a vehicle. The adaptive control may prevent an automated lane change that may otherwise be undertaken. 
     In accordance with an exemplary embodiment,  FIG. 1  is a block diagram of a vehicle that includes adaptive control of an automated lane change. The exemplary vehicle is an automobile  101  and is referred to as the subject vehicle  100 . The subject vehicle  100  includes several sensors  105 . A radar system  110 , a camera  120 , and a lidar system  130  are shown as rear-facing sensors  105 , which are of interest in the automated lane change scenario according to one or more embodiments. Another radar system  140  is shown as front-facing. According to alternate embodiments, additional sensors  105  may be included, and any of the sensors  105  may be located at different places in or on the subject vehicle  100 . 
     A controller  150  is also shown in the subject vehicle  100 . The controller  150  may obtain raw data or information from one or more sensors  105 , individually or according to conventional sensor fusion schemes. The data or information is used to detect objects  170  in the field of view of the sensors  105 . The exemplary object  170  shown in  FIG. 1  is another vehicle. The maximum detection range  160  is also shown. This maximum detection range  160  may be based on one of the sensors  105  (e.g., radar system  110 ) or may result from fusion of two or more sensors  105  (e.g., radar system  110  and camera  120 ). The lane that the subject vehicle  100  would move into based on the automated lane change is referred to as a target lane  180  for explanatory purposes. The detection of objects  170  by one or more sensors  105  and the determination of maximum detection range  160  are not detailed here. Detection of object  170  by one or a combination of the sensors  105  is well-known, and the embodiments detailed herein relate to an undetected vehicle rather than a detected object  170 . Further, determination of the maximum detection range  160  for any of the exemplary sensors  105  is known and is assumed to be a known parameter for the controller  150 . The modification of the maximum detection range  160  based on a following vehicle  400  ( FIG. 4 ) is discussed with reference to  FIG. 4 . 
     As detailed with reference to  FIG. 3 , the controller  150  assumes that another vehicle, referred to as a target vehicle  200  ( FIG. 2 ) for explanatory purposes, is just beyond the maximum detection range  160  in the target lane  180 . The controller  150  calculates the braking required by this target vehicle  200  to determine if the automated lane change should be prohibited. To perform the functionality discussed herein, the controller  150  may include processing circuitry that may include an application specific integrated circuit (ASIC), an electronic circuit, a processor (shared, dedicated, or group) and memory that executes one or more software or firmware programs, a combinational logic circuit, and/or other suitable components that provide the described functionality. 
       FIG. 2  is a block diagram that illustrates the process of performing adaptive control of an automated lane change according to one or more embodiments. The subject vehicle  100  is shown with a detected object  170  (another vehicle) in front of it. There are no detected objects  170  in the target lane  180 . Beyond the maximum detection range  160  behind the subject vehicle  100 , the controller  150  assumes the presence of a target vehicle  200 . As previously noted, the target vehicle  200  is not a detected object  170  but is an assumed object for purposes of determining whether an automated lane change should proceed. The controller  150  assumes that the speed at which the target vehicle  200  is travelling is a value Δ above the speed limit (speed=speed limit+Δ). The factors used to determine the value Δ are further discussed with reference to  FIG. 3 . Three zones  210 ,  220 ,  230  are indicated in  FIG. 2 . 
     The recognition zone  210  is a distance that the target vehicle  200  will travel in a defined length of time (e.g., 1 second). This defined length of time is referred to as the recognition time and is the duration assumed for the driver of the target vehicle  200  to recognize that the subject vehicle  100  is changing lanes. The buffer zone  230  is a specific distance from the rear of the subject vehicle  100 . The buffer zone  230  distance is set based on the speed of the vehicle  100 . For example, the buffer zone may be on the order of 2 meters for a relatively low speed and on the order of 20 meters for a relatively high speed of the vehicle  100 . The initial setting or subsequent refinement of the buffer zone  230  distance may be based on experimentation or experience. 
     The braking zone  220  is the remaining distance. That is, the controller  150  knows the maximum detection range  160 , as noted previously. Thus, the controller  150  can determine the braking zone  220  by subtracting the recognition zone  210 , which is determined based on the assumed speed of the target vehicle  200 , and the buffer zone  230  from the maximum detection range  160 . This braking zone  220  is the distance within which the target vehicle  200  must reduce its speed to match the speed of the subject vehicle  100 , which is known to the controller  150 . The controller  150  determines if the deceleration that must occur within the braking zone  220  is greater than a threshold deceleration. That is, the controller  150  determines if the target vehicle  200  must brake too hard (according to the predetermined threshold) in order to match the speed of the subject vehicle  100  before it reaches the buffer zone  230 . If so, then the controller  150  determines that the automated lane change should not be implemented. 
       FIG. 3  is a process flow  300  of a method of performing adaptive control of an automated lane change according to one or more embodiments. The processes detailed for the process flow  300  may be performed by the controller  150 . The process flow  300  may be initiated when an automated lane change is suggested by an existing autonomous or semi-autonomous driving system. In alternate embodiments, the processes at blocks  310  and  320  may be performed regularly on a periodic basis or on an event-based basis (e.g., every time the speed of the subject vehicle  100  changes). At block  310 , determining maximum detection range  160  is based on which sensors  105  are used (e.g., one or more radar systems  110 ) and the speed of the subject vehicle  100 . As further discussed with reference to  FIG. 4 , the known value of maximum detection range  160  for a given sensor  105  may be modified when the field of view of the sensor  105  is affected (e.g., by following vehicle  400  in  FIG. 4 ). When an automated lane change is under consideration (i.e., it has been suggested by an autonomous or semi-autonomous driving system), then the determination of maximum detection range  160  is also the determination of the distance to a target vehicle  200 , which is an undetected vehicle that is assumed to be just outside the field of view of the sensors  105  being used. 
     At block  320 , determining a speed for the target vehicle  200  may be based on the speed limit, as previously noted. For example, the speed of the target vehicle  200  may be assumed as (speed limit+Δ), and Δ may be selected as 15 miles per hour, for example. The value of Δ may be adjusted based on weather conditions or other factors, for example. At block  330 , the process flow  300  includes computing the deceleration needed by the target vehicle  200  in the braking zone  220 . As discussed above, the length of the braking zone  220  is determined by subtracting the lengths of the recognition zone  210  and the buffer zone  230  from the maximum detection range  160 . The target vehicle must decelerate from the determined speed of the target vehicle  200  (from block  320 ) T to the speed of the subject vehicle  100  S over the length of the braking zone  220  D. Thus, the deceleration is given by: 
     
       
         
           
             
               
                 
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     At block  340 , a check is done of whether the deceleration computed with EQ. 1 is greater than a threshold deceleration. The threshold deceleration may be selected as 0.2 g, for example (g=9.81 meters/seconds 2 ). If the deceleration required of the (hypothetical) target vehicle  200  in the braking zone  220  is less than or equal to the threshold value (according to the check at block  340 ), then the process flow  300  includes proceeding with the automated lane change, at block  350 . If, instead, the deceleration determined at block  330  exceeds the threshold (at block  340 ), then the process flow  300  includes prohibiting the planned automated lane change, at block  360 . 
       FIG. 4  illustrates an exemplary scenario for which the maximum detection range  160  (at block  310 ,  FIG. 3 ) is modified to perform adaptive control of an automated lane change according to one or more embodiments.  FIG. 4  indicates the maximum detection range  160  according to the sensor  105  (at the center of the rear of the subject vehicle  100 ) being used for the purpose of automated lane change. If there were no following vehicle  400  within the maximum detection range  160  behind the subject vehicle  100 , this maximum detection range  160  would be used at block  310 ,  FIG. 3 . However, when, as in the exemplary scenario shown in  FIG. 4 , there is a following vehicle  400  behind the subject vehicle  100 , the maximum detection range  160  is reduced to distance MD as part of the processing at block  310 . 
     Factors that affect the distance MD (i.e., the modified maximum detection range  160 ) include the distance between the subject vehicle  100  and the following vehicle  400 , the width W of the following vehicle  400 , and the location of the one or more sensors  105  of the subject vehicle  100  that are used to detect objects behind the subject vehicle  100 . In the exemplary scenario, the subject vehicle  100  and the following vehicle  400  are assumed to both be centered in the lane for explanatory purposes. Thus, the distance from the center of the subject vehicle  100 , where the sensor  105  is assumed to be located, to the corner of interest of the target vehicle  200  is given by (L+W/2). The corner of interest is the left corner of the target vehicle  200  when the target lane  180  is to the left of the subject vehicle  100 , and the corner of interest is the right corner of the target vehicle  200  when the target lane is to the right of the subject vehicle  100 . The value of L is based on knowledge of the lane width and an assumed width for the target vehicle  200  (e.g., the target vehicle  200  may be assumed to be in the center of the target lane  180 ). 
     As  FIG. 4  indicates, the value of the distance MD may be determined from equations pertaining to a right triangle based on the angle α and the distance between the sensor  105  and the corner of interest of the target vehicle  200 . Thus, the distance MD may be given by (L+W/2)(tan α). As the distance between the subject vehicle  100  and the following vehicle  400  increases, the value of the angle α increases. Thus, with all other things being equal, the distance MD will increase. As the width W of the following vehicle  400  increases, the value of the angle α decreases. Thus, with all other things being equal, the distance MD will decrease. If the sensor  105  is moved to the left rear bumper of the subject vehicle  100  from the center where it is shown, then the angle α increases. Further, (L+W/2) would be reduced by the distance R between the center of the subject vehicle  100  and the left rear bumper. Thus, the distance MD increases as (L+W/2−R)*(tan α). On the other hand, in the exemplary scenario shown in  FIG. 4 , if the sensor  105  were moved to the right rear bumper of the subject vehicle  100 , the following vehicle  400  would block even more of the field of view of the sensor  105 , and the distance MD would be much-reduced. 
     While the above disclosure has been described with reference to exemplary embodiments, it will be understood by those skilled in the art that various changes may be made and equivalents may be substituted for elements thereof without departing from its scope. In addition, many modifications may be made to adapt a particular situation or material to the teachings of the disclosure without departing from the essential scope thereof. Therefore, it is intended that the present disclosure not be limited to the particular embodiments disclosed, but will include all embodiments falling within the scope thereof.