Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-2, 6, 8-9, 13 and 15-16 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by McNew et al (US Pub 2018/0022350 A1), hereafter known as McNew.
For Claim 1, McNew teaches A method for controlling an acceleration rate of a vehicle, comprising:
determining, via one or more sensors associated with the vehicle, that the vehicle is at a first location; ([0038] Moreover, the high traffic environment 176 is dependent on the number of neighboring vehicles 184 on the same roadway 210 as the target vehicle 182. In some embodiments, the adaptive vehicle control system 100 may determine if the target vehicle 182 is located in the high traffic environment 176 based on access to real time traffic information, which may be located on one or more servers or databases communicatively coupled to the network 130 and may be accessed using the network interface hardware 116. In some embodiments, the adaptive vehicle control system 100 may determine if the target vehicle 182 is located in the high traffic environment 176 based on historical traffic data, which may be stored in the one or more memory modules 106 or located on one or more servers or databases communicatively coupled to the network 130. Further, the adaptive vehicle control system 100 may determine if the target vehicle 182 is located in the high traffic environment 176 based on sensor data measured by the proximity sensors 120 and/or based on the frequency of braking by the target vehicle 182. In some embodiments, if the autonomous operation profile 160 corresponding to the high traffic environment 176 is different than the autonomous operation profile 160 for the highway environment 172 or the surface street environment 174, the autonomous operation profile 160 for the high traffic environment 176 may supersede the autonomous operation profiles 160 for the highway environment 172 or the surface street environment 174 such that, in the high traffic environment 176, the autonomous operation profile 160 corresponding to the high traffic environment 176 is implemented.
[0026] In some embodiments, the one or more proximity sensors 120 may be positioned on or in the one or more vehicles 180, for example, the target vehicle 182 and, in operation, may be able to detect the presence of one or more neighboring vehicles 184 and detect the relative distance, relative speed, and/or the relative acceleration between the target vehicle 182 and the one or more neighboring vehicles 184. Further, the one or more proximity sensors 120 may determine the distance between the target vehicle 182 and one or more lane boundaries 213, 215 of one or more lanes 212, as depicted in FIG. 2, such that, in an autonomous operation, the one or more vehicles 180 may perform a lane tracking operation using the one or more proximity sensors 120 to remain between the lane boundaries 213, 215 while traversing an individual lane 212. Moreover, the one or more proximity sensors 120 may determine in which lane 212 each of the one or more neighboring vehicles 184 is positioned. In some embodiments, the adaptive vehicle control system 100 may be able to determine the location of the vehicle 180, for example, the target vehicle 182 based on a proximity signal outputted by the proximity sensor 120 and in embodiments in which the one or more proximity sensors 120 comprise a camera, the adaptive vehicle control system 100 may be able to determine a location of the vehicle 180, for example, the target vehicle 182, by accessing geotagged data.)
reducing an initial target acceleration rate of the vehicle to a first adjusted target acceleration rate in accordance with the location satisfying a first location condition; ([0034] Referring now to FIGS. 3A and 3B, the adaptive vehicle control system 100 may comprise multiple autonomous operation profiles 160, each comprising different vehicle control settings. For example, an aggressive autonomous operation profile 162, a normal autonomous operation profile 164, and a relaxed autonomous operation profile 166. In operation, the aggressive autonomous operation profile 162 comprises vehicle control settings specifying an aggressive acceleration rate and an aggressive deceleration rate, the normal autonomous operation profile 164 comprises vehicle control settings specifying a normal acceleration rate and a normal deceleration rate, and the relaxed autonomous operation profile 166 comprises vehicle control settings specifying a relaxed acceleration rate and a relaxed deceleration rate. As graphically depicted in FIG. 3A, a magnitude of the normal acceleration rate is less than a magnitude of the aggressive acceleration rate and greater than a magnitude of the relaxed acceleration rate. Moreover, as graphically depicted in FIG. 3B, a magnitude of the normal deceleration rate is less than a magnitude of the aggressive deceleration rate and greater than a magnitude of the relaxed deceleration rate.
[0036] Referring now to FIGS. 1-4, the autonomous operation profile 160 may be correlated with the vehicle operating environment 170 of the target vehicle 182. For example, the vehicle operating environment 170 may comprise a highway environment 172, a surface street environment 174, or a high traffic environment 176. In some embodiments, the one or more autonomous operation profiles 160 comprise a first autonomous operation profile corresponding with a first vehicle operating environment and a second autonomous operation profile corresponding with a second vehicle operating environment. As one non-limiting example, when the target vehicle 182 is positioned in the highway environment 172, the automated drive controller 142 may output vehicle control signals according to the aggressive autonomous operation profile 162 and when the target vehicle 182 is positioned in the surface street environment 174, the automated drive controller 142 may output vehicle control signals according to the normal autonomous operation profile 164.
[0037] The highway environment 172 and the surface street environment 174 each depend on the location of the target vehicle 182, e.g., a highway or a surface street. In operation, the adaptive vehicle control system 100 may determine whether the target vehicle 182 is in the highway environment 172 or the surface street environment 174 based on location data, which may be stored in the memory modules 106, determined based on location signals received by the satellite antenna 114, determined based on sensor data measured by the proximity sensors 120, or determined using any other known or yet to be developed location determination methods. Further, it should be understood that the highway environment 172 and the surface street environment 174 are merely example vehicle operating environments 170 and the autonomous operation profile 160 may be correlated with any number of vehicle operating environments 170, for example, urban environments, rural environments, or the like.)
determining, via the one or more sensors, that the vehicle is at a second location; ([0039] Referring still to FIGS. 1-4, the autonomous operation profile 160 may be time specific, for example, the autonomous operation profile 160 may change depending on the specific day, specific time of day, or the like. The time may be determined by the clock 124 communicatively coupled to the automated drive controller 142. For example, the automated drive controller 142 may output vehicle control signals according to a different autonomous operation profile during a workweek (e.g., Monday through Friday) than during a weekend (e.g., Saturday and Sunday). For example, the one or more autonomous operation profiles 160 may comprise a first autonomous operation profile corresponding with a weekend date and a second autonomous operation profile with a weekday date. As one non-limiting example, the autonomous operation profile 160 may comprise the aggressive autonomous operation profile 162 during the workweek and the relaxed autonomous operation profile 166 during the weekend.
[0040] Moreover, the autonomous operation profile 160 may depend on a combination of factors, for example, the time and the vehicle operating environment 170. As one non-limiting example, during the workweek, the autonomous operation profile 160 may be set as the aggressive autonomous operation profile 162 when the target vehicle 182 is positioned in any vehicle operating environment 170 and, during the weekend, the autonomous operation profile 160 may be the aggressive autonomous operation profile 162 when the target vehicle 182 is positioned in the highway environment 172 and may be the relaxed autonomous operation profile 166 when the target vehicle 182 is positioned in the surface street environment 174. It should be understood that any combination of autonomous operation profiles 160 may be implemented based on the locations of the target vehicle 182, the specific operation of the target vehicle 182 (e.g., acceleration or deceleration), the time, as well as weather conditions and other external factors.)
increasing the first adjusted target acceleration rate to a second adjusted target acceleration rate in accordance with determining the vehicle is at the second location. ([0039] Referring still to FIGS. 1-4, the autonomous operation profile 160 may be time specific, for example, the autonomous operation profile 160 may change depending on the specific day, specific time of day, or the like. The time may be determined by the clock 124 communicatively coupled to the automated drive controller 142. For example, the automated drive controller 142 may output vehicle control signals according to a different autonomous operation profile during a workweek (e.g., Monday through Friday) than during a weekend (e.g., Saturday and Sunday). For example, the one or more autonomous operation profiles 160 may comprise a first autonomous operation profile corresponding with a weekend date and a second autonomous operation profile with a weekday date. As one non-limiting example, the autonomous operation profile 160 may comprise the aggressive autonomous operation profile 162 during the workweek and the relaxed autonomous operation profile 166 during the weekend.
[0040] Moreover, the autonomous operation profile 160 may depend on a combination of factors, for example, the time and the vehicle operating environment 170. As one non-limiting example, during the workweek, the autonomous operation profile 160 may be set as the aggressive autonomous operation profile 162 when the target vehicle 182 is positioned in any vehicle operating environment 170 and, during the weekend, the autonomous operation profile 160 may be the aggressive autonomous operation profile 162 when the target vehicle 182 is positioned in the highway environment 172 and may be the relaxed autonomous operation profile 166 when the target vehicle 182 is positioned in the surface street environment 174. It should be understood that any combination of autonomous operation profiles 160 may be implemented based on the locations of the target vehicle 182, the specific operation of the target vehicle 182 (e.g., acceleration or deceleration), the time, as well as weather conditions and other external factors.)
For Claim 2, McNew teaches The method of claim 1, wherein the vehicle is at the standstill at the first location. (Figure 3A, [0034] Referring now to FIGS. 3A and 3B, the adaptive vehicle control system 100 may comprise multiple autonomous operation profiles 160, each comprising different vehicle control settings. For example, an aggressive autonomous operation profile 162, a normal autonomous operation profile 164, and a relaxed autonomous operation profile 166. In operation, the aggressive autonomous operation profile 162 comprises vehicle control settings specifying an aggressive acceleration rate and an aggressive deceleration rate, the normal autonomous operation profile 164 comprises vehicle control settings specifying a normal acceleration rate and a normal deceleration rate, and the relaxed autonomous operation profile 166 comprises vehicle control settings specifying a relaxed acceleration rate and a relaxed deceleration rate. As graphically depicted in FIG. 3A, a magnitude of the normal acceleration rate is less than a magnitude of the aggressive acceleration rate and greater than a magnitude of the relaxed acceleration rate. Moreover, as graphically depicted in FIG. 3B, a magnitude of the normal deceleration rate is less than a magnitude of the aggressive deceleration rate and greater than a magnitude of the relaxed deceleration rate.
The chart shows that the profile starts at zero, which would indicate that the vehicle is at a stand still.)
For Claim 6, McNew teaches The method of claim 1, wherein the vehicle operates in an autonomous mode or a semi-autonomous mode. ([0004] In one embodiment, an adaptive vehicle control system includes one or more processors, one or more memory modules communicatively coupled to the one or more processors, and machine readable instructions stored in the one or more memory modules that cause the adaptive vehicle control system to perform at least the following when executed by the one or more processors: determine an autonomous operation profile of a target vehicle positioned in a vehicle operating environment, wherein the vehicle operating environment includes a roadway having one or more lanes, determine an autonomous operation profile of one of more neighboring vehicles positioned within the vehicle operating environment, compare the autonomous operation profile of at least one of the one or more neighboring vehicles with the autonomous operation profile of the target vehicle, and alter a condition of the target vehicle such that the autonomous operation profile of the target vehicle matches an autonomous operation profile of an individual neighboring vehicle of the one or more neighboring vehicles positioned in the same lane as the target vehicle.)
For Claim 8, McNew teaches An apparatus for controlling an acceleration rate of a vehicle, comprising:
at least one processor; and ([0004] In one embodiment, an adaptive vehicle control system includes one or more processors, one or more memory modules communicatively coupled to the one or more processors, and machine readable instructions stored in the one or more memory modules that cause the adaptive vehicle control system to perform at least the following when executed by the one or more processors: determine an autonomous operation profile of a target vehicle positioned in a vehicle operating environment, wherein the vehicle operating environment includes a roadway having one or more lanes, determine an autonomous operation profile of one of more neighboring vehicles positioned within the vehicle operating environment, compare the autonomous operation profile of at least one of the one or more neighboring vehicles with the autonomous operation profile of the target vehicle, and alter a condition of the target vehicle such that the autonomous operation profile of the target vehicle matches an autonomous operation profile of an individual neighboring vehicle of the one or more neighboring vehicles positioned in the same lane as the target vehicle.)
at least one memory coupled with the at least one processor and storing instructions operable, when executed by the at least one processor, to cause the apparatus to: ([0004] In one embodiment, an adaptive vehicle control system includes one or more processors, one or more memory modules communicatively coupled to the one or more processors, and machine readable instructions stored in the one or more memory modules that cause the adaptive vehicle control system to perform at least the following when executed by the one or more processors: determine an autonomous operation profile of a target vehicle positioned in a vehicle operating environment, wherein the vehicle operating environment includes a roadway having one or more lanes, determine an autonomous operation profile of one of more neighboring vehicles positioned within the vehicle operating environment, compare the autonomous operation profile of at least one of the one or more neighboring vehicles with the autonomous operation profile of the target vehicle, and alter a condition of the target vehicle such that the autonomous operation profile of the target vehicle matches an autonomous operation profile of an individual neighboring vehicle of the one or more neighboring vehicles positioned in the same lane as the target vehicle.)
determine, via one or more sensors associated with the vehicle, that the vehicle is at a first location; ([0038] Moreover, the high traffic environment 176 is dependent on the number of neighboring vehicles 184 on the same roadway 210 as the target vehicle 182. In some embodiments, the adaptive vehicle control system 100 may determine if the target vehicle 182 is located in the high traffic environment 176 based on access to real time traffic information, which may be located on one or more servers or databases communicatively coupled to the network 130 and may be accessed using the network interface hardware 116. In some embodiments, the adaptive vehicle control system 100 may determine if the target vehicle 182 is located in the high traffic environment 176 based on historical traffic data, which may be stored in the one or more memory modules 106 or located on one or more servers or databases communicatively coupled to the network 130. Further, the adaptive vehicle control system 100 may determine if the target vehicle 182 is located in the high traffic environment 176 based on sensor data measured by the proximity sensors 120 and/or based on the frequency of braking by the target vehicle 182. In some embodiments, if the autonomous operation profile 160 corresponding to the high traffic environment 176 is different than the autonomous operation profile 160 for the highway environment 172 or the surface street environment 174, the autonomous operation profile 160 for the high traffic environment 176 may supersede the autonomous operation profiles 160 for the highway environment 172 or the surface street environment 174 such that, in the high traffic environment 176, the autonomous operation profile 160 corresponding to the high traffic environment 176 is implemented.
[0026] In some embodiments, the one or more proximity sensors 120 may be positioned on or in the one or more vehicles 180, for example, the target vehicle 182 and, in operation, may be able to detect the presence of one or more neighboring vehicles 184 and detect the relative distance, relative speed, and/or the relative acceleration between the target vehicle 182 and the one or more neighboring vehicles 184. Further, the one or more proximity sensors 120 may determine the distance between the target vehicle 182 and one or more lane boundaries 213, 215 of one or more lanes 212, as depicted in FIG. 2, such that, in an autonomous operation, the one or more vehicles 180 may perform a lane tracking operation using the one or more proximity sensors 120 to remain between the lane boundaries 213, 215 while traversing an individual lane 212. Moreover, the one or more proximity sensors 120 may determine in which lane 212 each of the one or more neighboring vehicles 184 is positioned. In some embodiments, the adaptive vehicle control system 100 may be able to determine the location of the vehicle 180, for example, the target vehicle 182 based on a proximity signal outputted by the proximity sensor 120 and in embodiments in which the one or more proximity sensors 120 comprise a camera, the adaptive vehicle control system 100 may be able to determine a location of the vehicle 180, for example, the target vehicle 182, by accessing geotagged data.)
reduce an initial target acceleration rate of the vehicle to a first adjusted target acceleration rate in accordance with the location satisfying a first location condition; ([0034] Referring now to FIGS. 3A and 3B, the adaptive vehicle control system 100 may comprise multiple autonomous operation profiles 160, each comprising different vehicle control settings. For example, an aggressive autonomous operation profile 162, a normal autonomous operation profile 164, and a relaxed autonomous operation profile 166. In operation, the aggressive autonomous operation profile 162 comprises vehicle control settings specifying an aggressive acceleration rate and an aggressive deceleration rate, the normal autonomous operation profile 164 comprises vehicle control settings specifying a normal acceleration rate and a normal deceleration rate, and the relaxed autonomous operation profile 166 comprises vehicle control settings specifying a relaxed acceleration rate and a relaxed deceleration rate. As graphically depicted in FIG. 3A, a magnitude of the normal acceleration rate is less than a magnitude of the aggressive acceleration rate and greater than a magnitude of the relaxed acceleration rate. Moreover, as graphically depicted in FIG. 3B, a magnitude of the normal deceleration rate is less than a magnitude of the aggressive deceleration rate and greater than a magnitude of the relaxed deceleration rate.
[0036] Referring now to FIGS. 1-4, the autonomous operation profile 160 may be correlated with the vehicle operating environment 170 of the target vehicle 182. For example, the vehicle operating environment 170 may comprise a highway environment 172, a surface street environment 174, or a high traffic environment 176. In some embodiments, the one or more autonomous operation profiles 160 comprise a first autonomous operation profile corresponding with a first vehicle operating environment and a second autonomous operation profile corresponding with a second vehicle operating environment. As one non-limiting example, when the target vehicle 182 is positioned in the highway environment 172, the automated drive controller 142 may output vehicle control signals according to the aggressive autonomous operation profile 162 and when the target vehicle 182 is positioned in the surface street environment 174, the automated drive controller 142 may output vehicle control signals according to the normal autonomous operation profile 164.
[0037] The highway environment 172 and the surface street environment 174 each depend on the location of the target vehicle 182, e.g., a highway or a surface street. In operation, the adaptive vehicle control system 100 may determine whether the target vehicle 182 is in the highway environment 172 or the surface street environment 174 based on location data, which may be stored in the memory modules 106, determined based on location signals received by the satellite antenna 114, determined based on sensor data measured by the proximity sensors 120, or determined using any other known or yet to be developed location determination methods. Further, it should be understood that the highway environment 172 and the surface street environment 174 are merely example vehicle operating environments 170 and the autonomous operation profile 160 may be correlated with any number of vehicle operating environments 170, for example, urban environments, rural environments, or the like.)
determine, via the one or more sensors, that the vehicle is at a second location; and ([0039] Referring still to FIGS. 1-4, the autonomous operation profile 160 may be time specific, for example, the autonomous operation profile 160 may change depending on the specific day, specific time of day, or the like. The time may be determined by the clock 124 communicatively coupled to the automated drive controller 142. For example, the automated drive controller 142 may output vehicle control signals according to a different autonomous operation profile during a workweek (e.g., Monday through Friday) than during a weekend (e.g., Saturday and Sunday). For example, the one or more autonomous operation profiles 160 may comprise a first autonomous operation profile corresponding with a weekend date and a second autonomous operation profile with a weekday date. As one non-limiting example, the autonomous operation profile 160 may comprise the aggressive autonomous operation profile 162 during the workweek and the relaxed autonomous operation profile 166 during the weekend.
[0040] Moreover, the autonomous operation profile 160 may depend on a combination of factors, for example, the time and the vehicle operating environment 170. As one non-limiting example, during the workweek, the autonomous operation profile 160 may be set as the aggressive autonomous operation profile 162 when the target vehicle 182 is positioned in any vehicle operating environment 170 and, during the weekend, the autonomous operation profile 160 may be the aggressive autonomous operation profile 162 when the target vehicle 182 is positioned in the highway environment 172 and may be the relaxed autonomous operation profile 166 when the target vehicle 182 is positioned in the surface street environment 174. It should be understood that any combination of autonomous operation profiles 160 may be implemented based on the locations of the target vehicle 182, the specific operation of the target vehicle 182 (e.g., acceleration or deceleration), the time, as well as weather conditions and other external factors.)
increase the first adjusted target acceleration rate to a second adjusted target acceleration rate in accordance with determining the vehicle is at the second location. ([0039] Referring still to FIGS. 1-4, the autonomous operation profile 160 may be time specific, for example, the autonomous operation profile 160 may change depending on the specific day, specific time of day, or the like. The time may be determined by the clock 124 communicatively coupled to the automated drive controller 142. For example, the automated drive controller 142 may output vehicle control signals according to a different autonomous operation profile during a workweek (e.g., Monday through Friday) than during a weekend (e.g., Saturday and Sunday). For example, the one or more autonomous operation profiles 160 may comprise a first autonomous operation profile corresponding with a weekend date and a second autonomous operation profile with a weekday date. As one non-limiting example, the autonomous operation profile 160 may comprise the aggressive autonomous operation profile 162 during the workweek and the relaxed autonomous operation profile 166 during the weekend.
[0040] Moreover, the autonomous operation profile 160 may depend on a combination of factors, for example, the time and the vehicle operating environment 170. As one non-limiting example, during the workweek, the autonomous operation profile 160 may be set as the aggressive autonomous operation profile 162 when the target vehicle 182 is positioned in any vehicle operating environment 170 and, during the weekend, the autonomous operation profile 160 may be the aggressive autonomous operation profile 162 when the target vehicle 182 is positioned in the highway environment 172 and may be the relaxed autonomous operation profile 166 when the target vehicle 182 is positioned in the surface street environment 174. It should be understood that any combination of autonomous operation profiles 160 may be implemented based on the locations of the target vehicle 182, the specific operation of the target vehicle 182 (e.g., acceleration or deceleration), the time, as well as weather conditions and other external factors.)
For Claim 9, McNew teaches The apparatus of claim 8, wherein the vehicle is at a standstill at the first location. (Figure 3A, [0034] Referring now to FIGS. 3A and 3B, the adaptive vehicle control system 100 may comprise multiple autonomous operation profiles 160, each comprising different vehicle control settings. For example, an aggressive autonomous operation profile 162, a normal autonomous operation profile 164, and a relaxed autonomous operation profile 166. In operation, the aggressive autonomous operation profile 162 comprises vehicle control settings specifying an aggressive acceleration rate and an aggressive deceleration rate, the normal autonomous operation profile 164 comprises vehicle control settings specifying a normal acceleration rate and a normal deceleration rate, and the relaxed autonomous operation profile 166 comprises vehicle control settings specifying a relaxed acceleration rate and a relaxed deceleration rate. As graphically depicted in FIG. 3A, a magnitude of the normal acceleration rate is less than a magnitude of the aggressive acceleration rate and greater than a magnitude of the relaxed acceleration rate. Moreover, as graphically depicted in FIG. 3B, a magnitude of the normal deceleration rate is less than a magnitude of the aggressive deceleration rate and greater than a magnitude of the relaxed deceleration rate.
The chart shows that the profile starts at zero, which would indicate that the vehicle is at a stand still.)
For Claim 13, McNew teaches The apparatus of claim 8, wherein the vehicle operates in an autonomous mode or a semi-autonomous mode. ([0004] In one embodiment, an adaptive vehicle control system includes one or more processors, one or more memory modules communicatively coupled to the one or more processors, and machine readable instructions stored in the one or more memory modules that cause the adaptive vehicle control system to perform at least the following when executed by the one or more processors: determine an autonomous operation profile of a target vehicle positioned in a vehicle operating environment, wherein the vehicle operating environment includes a roadway having one or more lanes, determine an autonomous operation profile of one of more neighboring vehicles positioned within the vehicle operating environment, compare the autonomous operation profile of at least one of the one or more neighboring vehicles with the autonomous operation profile of the target vehicle, and alter a condition of the target vehicle such that the autonomous operation profile of the target vehicle matches an autonomous operation profile of an individual neighboring vehicle of the one or more neighboring vehicles positioned in the same lane as the target vehicle.)
For Claim 15, McNew teaches A non-transitory computer-readable medium having program code recorded thereon for controlling an acceleration rate of a vehicle, the program code executed by at least one processor and comprising: ([0004] In one embodiment, an adaptive vehicle control system includes one or more processors, one or more memory modules communicatively coupled to the one or more processors, and machine readable instructions stored in the one or more memory modules that cause the adaptive vehicle control system to perform at least the following when executed by the one or more processors: determine an autonomous operation profile of a target vehicle positioned in a vehicle operating environment, wherein the vehicle operating environment includes a roadway having one or more lanes, determine an autonomous operation profile of one of more neighboring vehicles positioned within the vehicle operating environment, compare the autonomous operation profile of at least one of the one or more neighboring vehicles with the autonomous operation profile of the target vehicle, and alter a condition of the target vehicle such that the autonomous operation profile of the target vehicle matches an autonomous operation profile of an individual neighboring vehicle of the one or more neighboring vehicles positioned in the same lane as the target vehicle.)
program code to determine, via one or more sensors associated with the vehicle, that the vehicle is at a first location; (([0038] Moreover, the high traffic environment 176 is dependent on the number of neighboring vehicles 184 on the same roadway 210 as the target vehicle 182. In some embodiments, the adaptive vehicle control system 100 may determine if the target vehicle 182 is located in the high traffic environment 176 based on access to real time traffic information, which may be located on one or more servers or databases communicatively coupled to the network 130 and may be accessed using the network interface hardware 116. In some embodiments, the adaptive vehicle control system 100 may determine if the target vehicle 182 is located in the high traffic environment 176 based on historical traffic data, which may be stored in the one or more memory modules 106 or located on one or more servers or databases communicatively coupled to the network 130. Further, the adaptive vehicle control system 100 may determine if the target vehicle 182 is located in the high traffic environment 176 based on sensor data measured by the proximity sensors 120 and/or based on the frequency of braking by the target vehicle 182. In some embodiments, if the autonomous operation profile 160 corresponding to the high traffic environment 176 is different than the autonomous operation profile 160 for the highway environment 172 or the surface street environment 174, the autonomous operation profile 160 for the high traffic environment 176 may supersede the autonomous operation profiles 160 for the highway environment 172 or the surface street environment 174 such that, in the high traffic environment 176, the autonomous operation profile 160 corresponding to the high traffic environment 176 is implemented.
[0026] In some embodiments, the one or more proximity sensors 120 may be positioned on or in the one or more vehicles 180, for example, the target vehicle 182 and, in operation, may be able to detect the presence of one or more neighboring vehicles 184 and detect the relative distance, relative speed, and/or the relative acceleration between the target vehicle 182 and the one or more neighboring vehicles 184. Further, the one or more proximity sensors 120 may determine the distance between the target vehicle 182 and one or more lane boundaries 213, 215 of one or more lanes 212, as depicted in FIG. 2, such that, in an autonomous operation, the one or more vehicles 180 may perform a lane tracking operation using the one or more proximity sensors 120 to remain between the lane boundaries 213, 215 while traversing an individual lane 212. Moreover, the one or more proximity sensors 120 may determine in which lane 212 each of the one or more neighboring vehicles 184 is positioned. In some embodiments, the adaptive vehicle control system 100 may be able to determine the location of the vehicle 180, for example, the target vehicle 182 based on a proximity signal outputted by the proximity sensor 120 and in embodiments in which the one or more proximity sensors 120 comprise a camera, the adaptive vehicle control system 100 may be able to determine a location of the vehicle 180, for example, the target vehicle 182, by accessing geotagged data.)
program code to reduce an initial target acceleration rate of the vehicle to a first adjusted target acceleration rate in accordance with the location satisfying a first location condition; (([0034] Referring now to FIGS. 3A and 3B, the adaptive vehicle control system 100 may comprise multiple autonomous operation profiles 160, each comprising different vehicle control settings. For example, an aggressive autonomous operation profile 162, a normal autonomous operation profile 164, and a relaxed autonomous operation profile 166. In operation, the aggressive autonomous operation profile 162 comprises vehicle control settings specifying an aggressive acceleration rate and an aggressive deceleration rate, the normal autonomous operation profile 164 comprises vehicle control settings specifying a normal acceleration rate and a normal deceleration rate, and the relaxed autonomous operation profile 166 comprises vehicle control settings specifying a relaxed acceleration rate and a relaxed deceleration rate. As graphically depicted in FIG. 3A, a magnitude of the normal acceleration rate is less than a magnitude of the aggressive acceleration rate and greater than a magnitude of the relaxed acceleration rate. Moreover, as graphically depicted in FIG. 3B, a magnitude of the normal deceleration rate is less than a magnitude of the aggressive deceleration rate and greater than a magnitude of the relaxed deceleration rate.
[0036] Referring now to FIGS. 1-4, the autonomous operation profile 160 may be correlated with the vehicle operating environment 170 of the target vehicle 182. For example, the vehicle operating environment 170 may comprise a highway environment 172, a surface street environment 174, or a high traffic environment 176. In some embodiments, the one or more autonomous operation profiles 160 comprise a first autonomous operation profile corresponding with a first vehicle operating environment and a second autonomous operation profile corresponding with a second vehicle operating environment. As one non-limiting example, when the target vehicle 182 is positioned in the highway environment 172, the automated drive controller 142 may output vehicle control signals according to the aggressive autonomous operation profile 162 and when the target vehicle 182 is positioned in the surface street environment 174, the automated drive controller 142 may output vehicle control signals according to the normal autonomous operation profile 164.
[0037] The highway environment 172 and the surface street environment 174 each depend on the location of the target vehicle 182, e.g., a highway or a surface street. In operation, the adaptive vehicle control system 100 may determine whether the target vehicle 182 is in the highway environment 172 or the surface street environment 174 based on location data, which may be stored in the memory modules 106, determined based on location signals received by the satellite antenna 114, determined based on sensor data measured by the proximity sensors 120, or determined using any other known or yet to be developed location determination methods. Further, it should be understood that the highway environment 172 and the surface street environment 174 are merely example vehicle operating environments 170 and the autonomous operation profile 160 may be correlated with any number of vehicle operating environments 170, for example, urban environments, rural environments, or the like.)
program code to determine, via the one or more sensors, that the vehicle is at a second location; and (([0039] Referring still to FIGS. 1-4, the autonomous operation profile 160 may be time specific, for example, the autonomous operation profile 160 may change depending on the specific day, specific time of day, or the like. The time may be determined by the clock 124 communicatively coupled to the automated drive controller 142. For example, the automated drive controller 142 may output vehicle control signals according to a different autonomous operation profile during a workweek (e.g., Monday through Friday) than during a weekend (e.g., Saturday and Sunday). For example, the one or more autonomous operation profiles 160 may comprise a first autonomous operation profile corresponding with a weekend date and a second autonomous operation profile with a weekday date. As one non-limiting example, the autonomous operation profile 160 may comprise the aggressive autonomous operation profile 162 during the workweek and the relaxed autonomous operation profile 166 during the weekend.
[0040] Moreover, the autonomous operation profile 160 may depend on a combination of factors, for example, the time and the vehicle operating environment 170. As one non-limiting example, during the workweek, the autonomous operation profile 160 may be set as the aggressive autonomous operation profile 162 when the target vehicle 182 is positioned in any vehicle operating environment 170 and, during the weekend, the autonomous operation profile 160 may be the aggressive autonomous operation profile 162 when the target vehicle 182 is positioned in the highway environment 172 and may be the relaxed autonomous operation profile 166 when the target vehicle 182 is positioned in the surface street environment 174. It should be understood that any combination of autonomous operation profiles 160 may be implemented based on the locations of the target vehicle 182, the specific operation of the target vehicle 182 (e.g., acceleration or deceleration), the time, as well as weather conditions and other external factors.)
program code to increase the first adjusted target acceleration rate to a second adjusted target acceleration rate in accordance with determining the vehicle is at the second location. (([0039] Referring still to FIGS. 1-4, the autonomous operation profile 160 may be time specific, for example, the autonomous operation profile 160 may change depending on the specific day, specific time of day, or the like. The time may be determined by the clock 124 communicatively coupled to the automated drive controller 142. For example, the automated drive controller 142 may output vehicle control signals according to a different autonomous operation profile during a workweek (e.g., Monday through Friday) than during a weekend (e.g., Saturday and Sunday). For example, the one or more autonomous operation profiles 160 may comprise a first autonomous operation profile corresponding with a weekend date and a second autonomous operation profile with a weekday date. As one non-limiting example, the autonomous operation profile 160 may comprise the aggressive autonomous operation profile 162 during the workweek and the relaxed autonomous operation profile 166 during the weekend.
[0040] Moreover, the autonomous operation profile 160 may depend on a combination of factors, for example, the time and the vehicle operating environment 170. As one non-limiting example, during the workweek, the autonomous operation profile 160 may be set as the aggressive autonomous operation profile 162 when the target vehicle 182 is positioned in any vehicle operating environment 170 and, during the weekend, the autonomous operation profile 160 may be the aggressive autonomous operation profile 162 when the target vehicle 182 is positioned in the highway environment 172 and may be the relaxed autonomous operation profile 166 when the target vehicle 182 is positioned in the surface street environment 174. It should be understood that any combination of autonomous operation profiles 160 may be implemented based on the locations of the target vehicle 182, the specific operation of the target vehicle 182 (e.g., acceleration or deceleration), the time, as well as weather conditions and other external factors.)
For Claim 16, McNew teaches The non-transitory computer-readable medium of claim 15, wherein the vehicle is at a standstill at the first location. (Figure 3A, [0034] Referring now to FIGS. 3A and 3B, the adaptive vehicle control system 100 may comprise multiple autonomous operation profiles 160, each comprising different vehicle control settings. For example, an aggressive autonomous operation profile 162, a normal autonomous operation profile 164, and a relaxed autonomous operation profile 166. In operation, the aggressive autonomous operation profile 162 comprises vehicle control settings specifying an aggressive acceleration rate and an aggressive deceleration rate, the normal autonomous operation profile 164 comprises vehicle control settings specifying a normal acceleration rate and a normal deceleration rate, and the relaxed autonomous operation profile 166 comprises vehicle control settings specifying a relaxed acceleration rate and a relaxed deceleration rate. As graphically depicted in FIG. 3A, a magnitude of the normal acceleration rate is less than a magnitude of the aggressive acceleration rate and greater than a magnitude of the relaxed acceleration rate. Moreover, as graphically depicted in FIG. 3B, a magnitude of the normal deceleration rate is less than a magnitude of the aggressive deceleration rate and greater than a magnitude of the relaxed deceleration rate.
The chart shows that the profile starts at zero, which would indicate that the vehicle is at a stand still.)
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 3-5, 10-12, 17-19 are rejected under 35 U.S.C. 103 as being unpatentable over McNew in light of Raghu et al (US Pub 2017/0261991 A1), hereafter known as Raghu.
For Claim 3, McNew teaches The method of claim 2,
McNew does not teach further comprising controlling the vehicle to decelerate and come to the standstill based on detecting a stop condition associated with the first location.
Raghu, however, does teach further comprising controlling the vehicle to decelerate and come to the standstill based on detecting a stop condition associated with the first location. ([0038] The present disclosure includes devices, systems, and methodologies for improvements in comparison to existing and basic implementations of technology that involve the following: after stopping at the stop sign for intersection, a self-driving vehicle accelerates gradually until it reaches the posted speed limit of 35 mph. As soon as it detects the next stop sign near B, it will begin to decelerate by braking, until the vehicle comes to a full rest. This manner of operation causes unnecessary acceleration up to the speed limit, even though the vehicle is going to brake imminently and begin decelerating. This manner of operation can create unnecessary fuel consumption and/or unnecessary CO.sub.2 and other exhaust emissions.)
Therefore, it would be obvious to one of ordinary skill in the art prior to the effective date to modify McNew in light of Raghu such that the vehicle is controlled to slow and stop based on detecting a stop condition because if there is a stop condition such as a stop sign, a red light, or an obstacle in front of the vehicle, it would prevent collisions and dangerous situations by slowing and stopping at the stop condition.
For Claim 4, McNew teaches The method of claim 3,
McNew does not teach wherein the stop condition is detected prior to the vehicle arriving at the first location.
Raghu, however, does teach wherein the stop condition is detected prior to the vehicle arriving at the first location. ([0038] The present disclosure includes devices, systems, and methodologies for improvements in comparison to existing and basic implementations of technology that involve the following: after stopping at the stop sign for intersection, a self-driving vehicle accelerates gradually until it reaches the posted speed limit of 35 mph. As soon as it detects the next stop sign near B, it will begin to decelerate by braking, until the vehicle comes to a full rest. This manner of operation causes unnecessary acceleration up to the speed limit, even though the vehicle is going to brake imminently and begin decelerating. This manner of operation can create unnecessary fuel consumption and/or unnecessary CO.sub.2 and other exhaust emissions.
[0041] The present disclosure includes illustratively uses vehicle speed, GPS, navigation database, camera or other sensing technology, to determine that the vehicle is at an intersection currently. Illustratively using GPS, navigation database, camera or other sensing technology to determine that there is a reason to stop the vehicle shortly, such as upcoming stop sign, upcoming intersection, upcoming traffic jam, nearing intended destination etc. Illustratively, an upcoming curve, turn, construction may also be a reason to stop or slow down.)
Therefore, it would be obvious to one of ordinary skill in the art prior to the effective filing date to modify McNew in light of Raghu such that the stop condition is detected before reaching the location because being aware that the vehicle must stop before it must stop gives the vehicle time to plan an appropriate stop and deceleration profile. Otherwise the vehicle might have to stop too suddenly, and it may create dangerous situations.
For Claim 5, McNew teaches The method of claim 1, wherein:
the first location is a street environment; ([0036] Referring now to FIGS. 1-4, the autonomous operation profile 160 may be correlated with the vehicle operating environment 170 of the target vehicle 182. For example, the vehicle operating environment 170 may comprise a highway environment 172, a surface street environment 174, or a high traffic environment 176. In some embodiments, the one or more autonomous operation profiles 160 comprise a first autonomous operation profile corresponding with a first vehicle operating environment and a second autonomous operation profile corresponding with a second vehicle operating environment. As one non-limiting example, when the target vehicle 182 is positioned in the highway environment 172, the automated drive controller 142 may output vehicle control signals according to the aggressive autonomous operation profile 162 and when the target vehicle 182 is positioned in the surface street environment 174, the automated drive controller 142 may output vehicle control signals according to the normal autonomous operation profile 164.
[0037] The highway environment 172 and the surface street environment 174 each depend on the location of the target vehicle 182, e.g., a highway or a surface street. In operation, the adaptive vehicle control system 100 may determine whether the target vehicle 182 is in the highway environment 172 or the surface street environment 174 based on location data, which may be stored in the memory modules 106, determined based on location signals received by the satellite antenna 114, determined based on sensor data measured by the proximity sensors 120, or determined using any other known or yet to be developed location determination methods. Further, it should be understood that the highway environment 172 and the surface street environment 174 are merely example vehicle operating environments 170 and the autonomous operation profile 160 may be correlated with any number of vehicle operating environments 170, for example, urban environments, rural environments, or the like.)
the second location is a location that is away from the street environment. ([0036-0037])
Raghu, however, does teach that a stop situation is a crosswalk or the intersection. ([0038] The present disclosure includes devices, systems, and methodologies for improvements in comparison to existing and basic implementations of technology that involve the following: after stopping at the stop sign for intersection, a self-driving vehicle accelerates gradually until it reaches the posted speed limit of 35 mph. As soon as it detects the next stop sign near B, it will begin to decelerate by braking, until the vehicle comes to a full rest. This manner of operation causes unnecessary acceleration up to the speed limit, even though the vehicle is going to brake imminently and begin decelerating. This manner of operation can create unnecessary fuel consumption and/or unnecessary CO.sub.2 and other exhaust emissions.
[0041] The present disclosure includes illustratively uses vehicle speed, GPS, navigation database, camera or other sensing technology, to determine that the vehicle is at an intersection currently. Illustratively using GPS, navigation database, camera or other sensing technology to determine that there is a reason to stop the vehicle shortly, such as upcoming stop sign, upcoming intersection, upcoming traffic jam, nearing intended destination etc. Illustratively, an upcoming curve, turn, construction may also be a reason to stop or slow down.
Therefore, it would be obvious to one of ordinary skill in the art prior to the effective filing date to modify McNew in light of Raghu such that the first location is a crosswalk or an intersection;
the second location is a location that is away from the crosswalk or the intersection.
It would be obvious to one of ordinary skill in the art prior to the effective filing date to modify McNew in light of Raghu in this way because crosswalks and intersections are likely to be areas that will have cross traffic, whether vehicles or pedestrians. This creates situations in which collisions are more likely to occur. McNew establishes that in surface street environments, which would have intersections and cross traffic, relaxed acceleration can be used. In highway situations, aggressive acceleration can be used. Using a more relaxed acceleration means that the vehicle will be slower, giving itself and other vehicles and pedestrians more time to react if a collision becomes likely. This would be obvious to use at a crosswalk or intersection because these are places in which other vehicles or pedestrians are likely to be found traveling in a cross direction.
For Claim 10, McNew teaches The apparatus of claim 9
McNew does not teach wherein execution of the instructions further cause the apparatus to control the vehicle to decelerate and come to the standstill based on detecting a stop condition associated with the first location.
Raghu, however, does teach wherein execution of the instructions further cause the apparatus to control the vehicle to decelerate and come to the standstill based on detecting a stop condition associated with the first location. ([0038] The present disclosure includes devices, systems, and methodologies for improvements in comparison to existing and basic implementations of technology that involve the following: after stopping at the stop sign for intersection, a self-driving vehicle accelerates gradually until it reaches the posted speed limit of 35 mph. As soon as it detects the next stop sign near B, it will begin to decelerate by braking, until the vehicle comes to a full rest. This manner of operation causes unnecessary acceleration up to the speed limit, even though the vehicle is going to brake imminently and begin decelerating. This manner of operation can create unnecessary fuel consumption and/or unnecessary CO.sub.2 and other exhaust emissions.)
Therefore, it would be obvious to one of ordinary skill in the art prior to the effective date to modify McNew in light of Raghu such that the vehicle is controlled to slow and stop based on detecting a stop condition because if there is a stop condition such as a stop sign, a red light, or an obstacle in front of the vehicle, it would prevent collisions and dangerous situations by slowing and stopping at the stop condition.
For Claim 11, McNew teaches The apparatus of claim 10,
McNew does not teach wherein the stop condition is detected prior to the vehicle arriving at the first location.
Raghu, however, does teach wherein the stop condition is detected prior to the vehicle arriving at the first location. ([0038] The present disclosure includes devices, systems, and methodologies for improvements in comparison to existing and basic implementations of technology that involve the following: after stopping at the stop sign for intersection, a self-driving vehicle accelerates gradually until it reaches the posted speed limit of 35 mph. As soon as it detects the next stop sign near B, it will begin to decelerate by braking, until the vehicle comes to a full rest. This manner of operation causes unnecessary acceleration up to the speed limit, even though the vehicle is going to brake imminently and begin decelerating. This manner of operation can create unnecessary fuel consumption and/or unnecessary CO.sub.2 and other exhaust emissions.
[0041] The present disclosure includes illustratively uses vehicle speed, GPS, navigation database, camera or other sensing technology, to determine that the vehicle is at an intersection currently. Illustratively using GPS, navigation database, camera or other sensing technology to determine that there is a reason to stop the vehicle shortly, such as upcoming stop sign, upcoming intersection, upcoming traffic jam, nearing intended destination etc. Illustratively, an upcoming curve, turn, construction may also be a reason to stop or slow down.)
Therefore, it would be obvious to one of ordinary skill in the art prior to the effective filing date to modify McNew in light of Raghu such that the stop condition is detected before reaching the location because being aware that the vehicle must stop before it must stop gives the vehicle time to plan an appropriate stop and deceleration profile. Otherwise the vehicle might have to stop too suddenly, and it may create dangerous situations.
For Claim 12, McNew teaches The apparatus of claim 8, wherein:
the first location is a street environment; ([0036] Referring now to FIGS. 1-4, the autonomous operation profile 160 may be correlated with the vehicle operating environment 170 of the target vehicle 182. For example, the vehicle operating environment 170 may comprise a highway environment 172, a surface street environment 174, or a high traffic environment 176. In some embodiments, the one or more autonomous operation profiles 160 comprise a first autonomous operation profile corresponding with a first vehicle operating environment and a second autonomous operation profile corresponding with a second vehicle operating environment. As one non-limiting example, when the target vehicle 182 is positioned in the highway environment 172, the automated drive controller 142 may output vehicle control signals according to the aggressive autonomous operation profile 162 and when the target vehicle 182 is positioned in the surface street environment 174, the automated drive controller 142 may output vehicle control signals according to the normal autonomous operation profile 164.
[0037] The highway environment 172 and the surface street environment 174 each depend on the location of the target vehicle 182, e.g., a highway or a surface street. In operation, the adaptive vehicle control system 100 may determine whether the target vehicle 182 is in the highway environment 172 or the surface street environment 174 based on location data, which may be stored in the memory modules 106, determined based on location signals received by the satellite antenna 114, determined based on sensor data measured by the proximity sensors 120, or determined using any other known or yet to be developed location determination methods. Further, it should be understood that the highway environment 172 and the surface street environment 174 are merely example vehicle operating environments 170 and the autonomous operation profile 160 may be correlated with any number of vehicle operating environments 170, for example, urban environments, rural environments, or the like.)
the second location is a location that is away from the street environment. ([0036-0037])
Raghu, however, does teach that a stop situation is a crosswalk or the intersection. ([0038] The present disclosure includes devices, systems, and methodologies for improvements in comparison to existing and basic implementations of technology that involve the following: after stopping at the stop sign for intersection, a self-driving vehicle accelerates gradually until it reaches the posted speed limit of 35 mph. As soon as it detects the next stop sign near B, it will begin to decelerate by braking, until the vehicle comes to a full rest. This manner of operation causes unnecessary acceleration up to the speed limit, even though the vehicle is going to brake imminently and begin decelerating. This manner of operation can create unnecessary fuel consumption and/or unnecessary CO.sub.2 and other exhaust emissions.
[0041] The present disclosure includes illustratively uses vehicle speed, GPS, navigation database, camera or other sensing technology, to determine that the vehicle is at an intersection currently. Illustratively using GPS, navigation database, camera or other sensing technology to determine that there is a reason to stop the vehicle shortly, such as upcoming stop sign, upcoming intersection, upcoming traffic jam, nearing intended destination etc. Illustratively, an upcoming curve, turn, construction may also be a reason to stop or slow down.
Therefore, it would be obvious to one of ordinary skill in the art prior to the effective filing date to modify McNew in light of Raghu such that the first location is a crosswalk or an intersection;
the second location is a location that is away from the crosswalk or the intersection.
It would be obvious to one of ordinary skill in the art prior to the effective filing date to modify McNew in light of Raghu in this way because crosswalks and intersections are likely to be areas that will have cross traffic, whether vehicles or pedestrians. This creates situations in which collisions are more likely to occur. McNew establishes that in surface street environments, which would have intersections and cross traffic, relaxed acceleration can be used. In highway situations, aggressive acceleration can be used. Using a more relaxed acceleration means that the vehicle will be slower, giving itself and other vehicles and pedestrians more time to react if a collision becomes likely. This would be obvious to use at a crosswalk or intersection because these are places in which other vehicles or pedestrians are likely to be found traveling in a cross direction.
For Claim 17, McNew teaches The non-transitory computer-readable medium of claim 16,
McNew does not teach wherein program code further comprises program code to control the vehicle to decelerate and come to the standstill based on detecting a stop condition associated with the first location.
Raghu, however, does teach wherein program code further comprises program code to control the vehicle to decelerate and come to the standstill based on detecting a stop condition associated with the first location. ([0038] The present disclosure includes devices, systems, and methodologies for improvements in comparison to existing and basic implementations of technology that involve the following: after stopping at the stop sign for intersection, a self-driving vehicle accelerates gradually until it reaches the posted speed limit of 35 mph. As soon as it detects the next stop sign near B, it will begin to decelerate by braking, until the vehicle comes to a full rest. This manner of operation causes unnecessary acceleration up to the speed limit, even though the vehicle is going to brake imminently and begin decelerating. This manner of operation can create unnecessary fuel consumption and/or unnecessary CO.sub.2 and other exhaust emissions.)
Therefore, it would be obvious to one of ordinary skill in the art prior to the effective date to modify McNew in light of Raghu such that the vehicle is controlled to slow and stop based on detecting a stop condition because if there is a stop condition such as a stop sign, a red light, or an obstacle in front of the vehicle, it would prevent collisions and dangerous situations by slowing and stopping at the stop condition.
For Claim 18, McNew teaches The non-transitory computer-readable medium of claim 17,
McNew does not teach wherein the stop condition is detected prior to the vehicle arriving at the first location.
Raghu, however, does teach wherein the stop condition is detected prior to the vehicle arriving at the first location. ([0038] The present disclosure includes devices, systems, and methodologies for improvements in comparison to existing and basic implementations of technology that involve the following: after stopping at the stop sign for intersection, a self-driving vehicle accelerates gradually until it reaches the posted speed limit of 35 mph. As soon as it detects the next stop sign near B, it will begin to decelerate by braking, until the vehicle comes to a full rest. This manner of operation causes unnecessary acceleration up to the speed limit, even though the vehicle is going to brake imminently and begin decelerating. This manner of operation can create unnecessary fuel consumption and/or unnecessary CO.sub.2 and other exhaust emissions.
[0041] The present disclosure includes illustratively uses vehicle speed, GPS, navigation database, camera or other sensing technology, to determine that the vehicle is at an intersection currently. Illustratively using GPS, navigation database, camera or other sensing technology to determine that there is a reason to stop the vehicle shortly, such as upcoming stop sign, upcoming intersection, upcoming traffic jam, nearing intended destination etc. Illustratively, an upcoming curve, turn, construction may also be a reason to stop or slow down.)
Therefore, it would be obvious to one of ordinary skill in the art prior to the effective filing date to modify McNew in light of Raghu such that the stop condition is detected before reaching the location because being aware that the vehicle must stop before it must stop gives the vehicle time to plan an appropriate stop and deceleration profile. Otherwise the vehicle might have to stop too suddenly, and it may create dangerous situations.
For Claim 19, McNew teaches The non-transitory computer-readable medium of claim 15, wherein:
the first location is a street environment; ([0036] Referring now to FIGS. 1-4, the autonomous operation profile 160 may be correlated with the vehicle operating environment 170 of the target vehicle 182. For example, the vehicle operating environment 170 may comprise a highway environment 172, a surface street environment 174, or a high traffic environment 176. In some embodiments, the one or more autonomous operation profiles 160 comprise a first autonomous operation profile corresponding with a first vehicle operating environment and a second autonomous operation profile corresponding with a second vehicle operating environment. As one non-limiting example, when the target vehicle 182 is positioned in the highway environment 172, the automated drive controller 142 may output vehicle control signals according to the aggressive autonomous operation profile 162 and when the target vehicle 182 is positioned in the surface street environment 174, the automated drive controller 142 may output vehicle control signals according to the normal autonomous operation profile 164.
[0037] The highway environment 172 and the surface street environment 174 each depend on the location of the target vehicle 182, e.g., a highway or a surface street. In operation, the adaptive vehicle control system 100 may determine whether the target vehicle 182 is in the highway environment 172 or the surface street environment 174 based on location data, which may be stored in the memory modules 106, determined based on location signals received by the satellite antenna 114, determined based on sensor data measured by the proximity sensors 120, or determined using any other known or yet to be developed location determination methods. Further, it should be understood that the highway environment 172 and the surface street environment 174 are merely example vehicle operating environments 170 and the autonomous operation profile 160 may be correlated with any number of vehicle operating environments 170, for example, urban environments, rural environments, or the like.)
the second location is a location that is away from the street environment. ([0036-0037])
Raghu, however, does teach that a stop situation is a crosswalk or the intersection. ([0038] The present disclosure includes devices, systems, and methodologies for improvements in comparison to existing and basic implementations of technology that involve the following: after stopping at the stop sign for intersection, a self-driving vehicle accelerates gradually until it reaches the posted speed limit of 35 mph. As soon as it detects the next stop sign near B, it will begin to decelerate by braking, until the vehicle comes to a full rest. This manner of operation causes unnecessary acceleration up to the speed limit, even though the vehicle is going to brake imminently and begin decelerating. This manner of operation can create unnecessary fuel consumption and/or unnecessary CO.sub.2 and other exhaust emissions.
[0041] The present disclosure includes illustratively uses vehicle speed, GPS, navigation database, camera or other sensing technology, to determine that the vehicle is at an intersection currently. Illustratively using GPS, navigation database, camera or other sensing technology to determine that there is a reason to stop the vehicle shortly, such as upcoming stop sign, upcoming intersection, upcoming traffic jam, nearing intended destination etc. Illustratively, an upcoming curve, turn, construction may also be a reason to stop or slow down.
Therefore, it would be obvious to one of ordinary skill in the art prior to the effective filing date to modify McNew in light of Raghu such that the first location is a crosswalk or an intersection;
the second location is a location that is away from the crosswalk or the intersection.
It would be obvious to one of ordinary skill in the art prior to the effective filing date to modify McNew in light of Raghu in this way because crosswalks and intersections are likely to be areas that will have cross traffic, whether vehicles or pedestrians. This creates situations in which collisions are more likely to occur. McNew establishes that in surface street environments, which would have intersections and cross traffic, relaxed acceleration can be used. In highway situations, aggressive acceleration can be used. Using a more relaxed acceleration means that the vehicle will be slower, giving itself and other vehicles and pedestrians more time to react if a collision becomes likely. This would be obvious to use at a crosswalk or intersection because these are places in which other vehicles or pedestrians are likely to be found traveling in a cross direction.
Claims 7, 14, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over McNew et al in light of Paris et al (US Pub 2018/0326982 A1), hereafter known as Paris.
For Claim 7, McNew teaches The method of claim 1,
McNew does not teach further comprising controlling the vehicle to move from the first location to the second location in accordance with detecting, while at the first location, that one or more pedestrians are not within a distance threshold of the vehicle.
Paris, however, does teach further comprising controlling the vehicle to move from the first location to the second location in accordance with detecting, while at the first location, that one or more pedestrians are not within a distance threshold of the planned path of the vehicle. ([0008] As shown in FIG. 1, one variation of the method S100 includes: approaching the road surface in Block S110; over a first period of time, detecting a pedestrian proximal the road surface in Block S120; predicting an initial intent of the pedestrian based on actions of the pedestrian during the first period of time in Block S130; and calculating an initial confidence score for the initial intent of the pedestrian based on motion characteristics of the pedestrian during the first period of time in Block S140. This variation of the method S100 also includes, in response to the initial confidence score for the initial intent of the pedestrian falling below a threshold confidence: replaying an audio track audible to the pedestrian in Block S150; tracking the pedestrian following replay of the audio track in Block S122; calculating a revised intent of the pedestrian based on actions of the pedestrian following replay of the audio track in Block S132; and calculating a revised confidence score for the revised intent of the pedestrian based on motion characteristics of the pedestrian following replay of the audio track in Block S142. Furthermore, this variation of the method S100 includes, in response to a location of the pedestrian falling outside of a threshold distance of a planned route of the autonomous vehicle and in response to the revised confidence score exceeding the threshold confidence, autonomously navigating across the road surface according to the planned route in Block S160.)
Therefore, it would be obvious to one of ordinary skill in the art prior to the effective filing date to modify McNew in light of Paris such that further comprising controlling the vehicle to move from the first location to the second location in accordance with detecting, while at the first location, that one or more pedestrians are not within a distance threshold of the vehicle because if there are pedestrians within certain thresholds of the vehicle, then it might not be safe for the vehicle to move forward. Oftentimes vehicles want to maintain a distance threshold between itself and other obstacles so that it does not collide with those obstacles. By not continuing from the first location to the second location (waiting) until a pedestrian has moved on, it can help prevent collision. While Paris teaches waiting for them to be out of a distance of the path, the path of the vehicle would also include the current location of the vehicle.
For Claim 14, McNew teaches The apparatus of claim 8,
McNew does not teach wherein execution of the instructions further cause the apparatus to control the vehicle to move from the first location to the second location in accordance with detecting, while at the first location, that one or more pedestrians are not within a distance threshold of the vehicle.
Paris, however, does teach wherein execution of the instructions further cause the apparatus to control the vehicle to move from the first location to the second location in accordance with detecting, while at the first location, that one or more pedestrians are not within a distance threshold of the planned path of the vehicle. ([0008] As shown in FIG. 1, one variation of the method S100 includes: approaching the road surface in Block S110; over a first period of time, detecting a pedestrian proximal the road surface in Block S120; predicting an initial intent of the pedestrian based on actions of the pedestrian during the first period of time in Block S130; and calculating an initial confidence score for the initial intent of the pedestrian based on motion characteristics of the pedestrian during the first period of time in Block S140. This variation of the method S100 also includes, in response to the initial confidence score for the initial intent of the pedestrian falling below a threshold confidence: replaying an audio track audible to the pedestrian in Block S150; tracking the pedestrian following replay of the audio track in Block S122; calculating a revised intent of the pedestrian based on actions of the pedestrian following replay of the audio track in Block S132; and calculating a revised confidence score for the revised intent of the pedestrian based on motion characteristics of the pedestrian following replay of the audio track in Block S142. Furthermore, this variation of the method S100 includes, in response to a location of the pedestrian falling outside of a threshold distance of a planned route of the autonomous vehicle and in response to the revised confidence score exceeding the threshold confidence, autonomously navigating across the road surface according to the planned route in Block S160.)
Therefore, it would be obvious to one of ordinary skill in the art prior to the effective filing date to modify McNew in light of Paris such that wherein execution of the instructions further cause the apparatus to control the vehicle to move from the first location to the second location in accordance with detecting, while at the first location, that one or more pedestrians are not within a distance threshold of the vehicle because if there are pedestrians within certain thresholds of the vehicle, then it might not be safe for the vehicle to move forward. Oftentimes vehicles want to maintain a distance threshold between itself and other obstacles so that it does not collide with those obstacles. By not continuing from the first location to the second location (waiting) until a pedestrian has moved on, it can help prevent collision. While Paris teaches waiting for them to be out of a distance of the path, the path of the vehicle would also include the current location of the vehicle.
For Claim 20, McNew teaches The non-transitory computer-readable medium of claim 15,
McNew does not teach wherein program code further comprises program code to control the vehicle to move from the first location to the second location in accordance with detecting, while at the first location, that one or more pedestrians are not within a distance threshold of the vehicle.
McNew does not teach wherein program code further comprises program code to control the vehicle to move from the first location to the second location in accordance with detecting, while at the first location, that one or more pedestrians are not within a distance threshold of the vehicle.
Paris, however, does teach wherein program code further comprises program code to control the vehicle to move from the first location to the second location in accordance with detecting, while at the first location, that one or more pedestrians are not within a distance threshold of the vehicle’s path. ([0008] As shown in FIG. 1, one variation of the method S100 includes: approaching the road surface in Block S110; over a first period of time, detecting a pedestrian proximal the road surface in Block S120; predicting an initial intent of the pedestrian based on actions of the pedestrian during the first period of time in Block S130; and calculating an initial confidence score for the initial intent of the pedestrian based on motion characteristics of the pedestrian during the first period of time in Block S140. This variation of the method S100 also includes, in response to the initial confidence score for the initial intent of the pedestrian falling below a threshold confidence: replaying an audio track audible to the pedestrian in Block S150; tracking the pedestrian following replay of the audio track in Block S122; calculating a revised intent of the pedestrian based on actions of the pedestrian following replay of the audio track in Block S132; and calculating a revised confidence score for the revised intent of the pedestrian based on motion characteristics of the pedestrian following replay of the audio track in Block S142. Furthermore, this variation of the method S100 includes, in response to a location of the pedestrian falling outside of a threshold distance of a planned route of the autonomous vehicle and in response to the revised confidence score exceeding the threshold confidence, autonomously navigating across the road surface according to the planned route in Block S160.)
Therefore, it would be obvious to one of ordinary skill in the art prior to the effective filing date to modify McNew in light of Paris such that wherein program code further comprises program code to control the vehicle to move from the first location to the second location in accordance with detecting, while at the first location, that one or more pedestrians are not within a distance threshold of the vehicle because if there are pedestrians within certain thresholds of the vehicle, then it might not be safe for the vehicle to move forward. Oftentimes vehicles want to maintain a distance threshold between itself and other obstacles so that it does not collide with those obstacles. By not continuing from the first location to the second location (waiting) until a pedestrian has moved on, it can help prevent collision. While Paris teaches waiting for them to be out of a distance of the path, the path of the vehicle would also include the current location of the vehicle.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Sauter et al (US Pub 2010/0250087 A1) relates to vehicle acceleration control.
Hayakawa et al (US Pub 2015/0284000 A1) relates to acceleration suppression in certain situations.
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/T.J.G./Examiner, Art Unit 3656 /KHOI H TRAN/Supervisory Patent Examiner, Art Unit 3656