DETAILED ACTION
Response to Amendment
Claims 1, 3-11, and 13-20 are pending. Claims 1, 3-11, and 13-20 are amended directly or by dependency on an amended claim.
Response to Arguments
Applicant's arguments filed 24 December, 2026 and interview conducted 22 December, 2025 have been fully considered but they are not persuasive. Applicant’s arguments with respect to claim(s) 1, 11, and 20 have been considered but are moot because the new ground of rejection does not rely on the combination of references applied in the prior rejection of record for any teaching or matter specifically challenged in the argument. In particular, Kubertschak is no longer relied upon and Dharia et al. is now relied upon for the amended portion of the claim, “recognize the visual cue as a visual indication of at least one of the directionality of the temporary traffic lane and the second directionality of the adjacent temporary traffic lane, wherein the directionality of the adjacent temporary traffic lane is different from the second directionality of the temporary traffic lane; and predict the directionality of the temporary traffic lane or the second directionality of the adjacent temporary traffic lane based on the visual cue comprised among the one or more cues”.
The primary reference, Yun et al. upon further consideration does disclose the second and third indication, as the reference can be interpreted as a first indication can be a line painted on a road surface; a second indication can be a person who is giving a hand signal, and a third indication can be a road facility installed on the road.
Examiner notes that while initially the proposed claim language appeared allowable, the phrasing does not sufficiently clarify the concepts of directionality and second directionality and therefore is unclear. Further this lead to finding new art upon further search and consideration.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim 1 (and by dependency claims 4-10) are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. The limitations “recognize the visual cue as a visual indication of at least one of the directionality of the temporary traffic lane and the second directionality of the adjacent temporary traffic lane, wherein the directionality of the adjacent temporary traffic lane is different from the second directionality of the temporary traffic lane; and predict the directionality of the temporary traffic lane or the second directionality of the adjacent temporary traffic lane based on the visual cue comprised among the one or more cues” are unclear in terms of what is meant by “directionality” and “second directionality”. For the purposes of examination, this is interpreted as meaning performing recognition on the sign to determine if it is showing two-way traffic as opposed to one-way traffic. Claims 11 (and by dependency claims 14-19) and 20 are rejected by the same rationale.
Claims 3 and 13 are rejected for the same reason as claim 1 for having the unclear terms “directionality” and “second directionality”. Claim 3 recites “recognizing the visual cue as the visual indication of at least one of the directionality of the temporary traffic lane and the second directionality of the adjacent temporary traffic lane comprises recognizing the visual cue as the visual indication of the second directionality of the adjacent temporary traffic lane, wherein the one or more processors are further configured to: determine a direction that is opposite to the second directionality of the adjacent temporary traffic lane; and predict the directionality of the temporary traffic lane based on the direction that is opposite to the different directionality of the adjacent temporary traffic lane”. As the “visual cue” is coming from the sign, examiner interprets the claim as meaning: recognizing the sign is for two-way traffic, and “predicting” both lane directions based on the “two-way traffic” notation on the sign.
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.
Claim(s) 1, 3-5, 9, 11, 13-15, 18, and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Yun et al. (US 20190019413 A1) in view of Dharia et al. (US 20220392229 A1).
Regarding claims 1, 11, and 20, Yun et al. disclose a system comprising: a memory; and one or more processors coupled to the memory, the one or more processors being configured to: and a method comprising: and a non-transitory computer-readable medium having stored thereon instructions which, when executed by one or more processors, cause the one or more processors to: detect, based on sensor data from one or more sensors of a vehicle (object detector 300 may include a camera 310, a radar 320, a lidar 330, an ultrasonic sensor 340, an infrared sensor 350, [0135], camera 310 may be located at an appropriate position outside the vehicle 100 in order to acquire images of the outside of the vehicle, [0137]), a temporary traffic lane on a road configured for use by traffic to navigate the road in lieu of one or more pre-existing traffic lanes on the road (“The lane guidance structure may be a structure which is temporarily installed on the road to guide a lane. For example, the lane guidance structure may be a traffic cone, a reflector attached onto a road surface to indicate a temporary lane, a temporary barrier structure installed on a roadway to stop traffic flows, a temporary sign installed on the road, etc.”, [0323]-[0324]), wherein at least one boundary of the temporary traffic lane is defined by a plurality of objects on the road (“For example, the processor 717 may determine a driving lane based on a plurality of traffic cones set up on the road. In this case, the processor 717 may determine that a region formed in a direction in which the plurality of traffic cones is placed is a driving lane,” [0290], “For example, a path guidance object which is preset to correspond to a construction area may be a reflector attached onto a road surface to indicate a temporary lane, a temporary barrier facility installed on the road, a traffic cone, a person who is giving a hand signal, etc.”, [0350]); detect, based on the sensor data, one or more cues indicating a directionality of the temporary traffic lane based on at least one of a first indication of a direction of travel of a vehicle traveling through the temporary traffic lane or an adjacent temporary traffic lane, a second indication of directionality provided by a human traffic controller in a scene associated with the road, and a third indication of directionality predicted based on one or more objects on the road (a type of an object used by the processor to determine a driving lane includes a line painted on a road surface, a road facility installed on the road, a lane guide structure placed temporarily on the road, a person who is giving a hand signal, a different vehicle, and a traffic sign, [0292], “When the processor 1717 needs to determine a driving lane based on various types of objects, which type of object should be selected as a preferential basis of determining a driving lane comes into question. A priority order used in the present invention is about an order for determining a driving lane based on one or more objects. For example, according to a priority order, a lane may have a first priority, a road facility may have a second priority, and a lane guide structure may have a third priority” [0293]-[0295], For example, when it is determined that the vehicle 100 is entering a construction area or that an accident has occurred ahead of the vehicle 100, the processor 717 may change a priority order, so that a temporary guidance structure installed on the road or a person giving a hand signal becomes a first priority object, [0313], The processor 717 may determine a driving lane preferentially based on the path guidance object which is determined to be a first priority object. In this case, when it is determined, based on object information, that the lane and the path guidance object exist, the processor 717 may determine a driving lane preferentially based on the path guidance object, rather than the lane, [0321]); and predict the directionality of the temporary traffic lane based on the visual cue comprised among the one or more cues (according to a priority order, a lane may have a first priority, a road facility may have a second priority, and a lane guide structure may have a third priority, [0295], “When the hand signal given by the person is determined to guide the vehicle 100 to move rightward, the processor 717 may determine that a driving lane detours to the right side of the person. For example, when the hand signal given by the person is determined to guide the vehicle 100 to move leftward, the processor 717 may determine that a driving lane detours to the left side of the person”, [0329] - [0330]).
Yun et al. further disclose a second indication of the directionality of the temporary traffic lane or a second directionality of the adjacent temporary traffic lane, provided by a human traffic controller in a scene associated with the road (“Based on object information, the processor 717 may determine a hand signal given by a person. When a person giving a hand signal is determined to be a first priority object, the processor 717 may determine a driving lane based on the hand signal. When the hand signal given by the person is determined to guide the vehicle 100 to move rightward, the processor 717 may determine that a driving lane detours to the right side of the person. For example, when the hand signal given by the person is determined to guide the vehicle 100 to move leftward, the processor 717 may determine that a driving lane detours to the left side of the person”, [0327]-[0330], For example, when it is determined that a hand signal given by the person 13, who is determined to be a first object, guides the vehicle 100 to the right, the processor 717 may determine that a path detouring to the right side of the person 13 is a driving lane, [0481]) and a third indication of the directionality of the temporary traffic lane or the second directionality of the adjacent temporary traffic lane, predicted based on one or more objects on the road (a type of an object used by the processor to determine a driving lane includes a line painted on a road surface, a road facility installed on the road, a lane guide structure placed temporarily on the road, a person who is giving a hand signal, a different vehicle, and a traffic sign, [0292], a lane may have a first priority, a road facility may have a second priority, and a lane guide structure may have a third priority” [0293]-[0295]) [Interpretation: the first indication is interpreted as a line painted on a road surface; the second indication is interpreted as a person who is giving a hand signal, and the third indication is interpreted as a road facility installed on the road].
Yun et al. do not use the word “directionality”. It would have been obvious at the time of filing to one of ordinary skill in the art that Yun et al. is determining directionality, as Yun et al. indicate determining a detour to the left or the right, which can be interpreted as a left or rightward direction (see for instance Fig. 12, in which a direction towards the left is strongly suggested by the scene content including objects in the roadway and hand signals:
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Yun et al. do not explicitly disclose recognize the visual cue as a visual indication of at least one of the directionality of the temporary traffic lane and the second directionality of the adjacent temporary traffic lane, wherein the directionality of the adjacent temporary traffic lane is different from the second directionality of the temporary traffic lane; and predict the directionality of the temporary traffic lane or the second directionality of the adjacent temporary traffic lane based on the visual cue comprised among the one or more cues.
Dharia et al. teach a third indication of the directionality of the temporary traffic lane or the second directionality of the adjacent temporary traffic lane, predicted based on one or more objects on the road (In one example, camera 118, radar 114, and/or lidar 112 can determine that the path ahead (e.g., a current driving lane) is hindered by one or more road primitives (e.g., cones or traffic signs). The AVCS 140 can cause the AV 100 to alter a driving path (e.g., change lanes) based on the detected one or more road primitives (e.g., identifying a spatial relationship between the road primitives, detecting displayed navigational instructions associated with the road primitives). As will be described in further detail below with reference to FIG. 2, the data processing system 120 can determine the status of a lane (e.g., temporary lane closure) based on the detection of the one or more road primitives, [0040]) detect, based on image data in the sensor data, a visual cue in the sign (For example, the perception system 130 can analyze images captured by the cameras 118 and can be capable of detecting traffic light signals, road signs, roadway layouts (e.g., boundaries of traffic lanes, topologies of intersections, designations of parking places, and so on), presence of obstacles, and the like, [0035]) recognize the visual cue as a visual indication of at least one of the directionality of the temporary traffic lane and the second directionality of the adjacent temporary traffic lane, wherein the directionality of the adjacent temporary traffic lane is different from the second directionality of the temporary traffic lane and predict the directionality of the temporary traffic lane or the second directionality of the adjacent temporary traffic lane based on the visual cue comprised among the one or more cues (“In one example, camera 118, radar 114, and/or lidar 112 can determine that the path ahead (e.g., a current driving lane) is hindered by one or more road primitives (e.g., cones or traffic signs). The AVCS 140 can cause the AV 100 to alter a driving path (e.g., change lanes) based on the detected one or more road primitives (e.g., identifying a spatial relationship between the road primitives, detecting displayed navigational instructions associated with the road primitives). As will be described in further detail below with reference to FIG. 2, the data processing system 120 can determine the status of a lane (e.g., temporary lane closure) based on the detection of the one or more road primitives. The AVCS 140 can then output instructions to powertrain, brakes and steering 150 to route the AV through a temporary travel path (e.g., a detour) and return the AV to an original driving path after determining the status of the associated lane has returned to a previous state (e.g., a normal or active lane state). Based on this determination, the AVCS 140 can output instructions to the powertrain, brakes and steering 150 to drive around the candidate object. The data processing system 120 may provide data used to predict the behavior of objects (e.g., vehicles, pedestrians, etc.) in the driving environment of the AV. The AVCS 140 may alter driving behavior of the AV responsive to data indicating future states of objects within the driving environments. The data processing system 120 may detect a construction zone and detect that an oncoming lane shifts or merges into the current lane of the AV. The data processing system 120 may communicate to the AV to choose to yield or nudge accordingly based on the object detection (e.g., oncoming vehicles). For example, the data processing system 120 may determine that a two-way road with two lanes in each direction has a construction zone in which the oncoming traffic lanes are closed and one of the lanes of traffic in the direction of the AV's motion is provided for the oncoming traffic.”, [0040]) [two way traffic interpreted as “directionality” and “second directionality” as two way traffic is necessarily moving in two opposite directions].
Yun et al. and Dharia et al. are in the same art of autonomous driving systems and detecting temporary lanes (Yun et al., abstract, [0017], [0313]; Dharia et al., abstract, [0040]). The combination of Dharia et al. with Yun et al. enables detecting a second direction. It would have been obvious at the time of filing to one of ordinary skill in the art to combine the detection of Dharia et al. with the invention of Yun et al. as this was known at the time of filing, the combination would have predictable results, as Dharia et al. indicate “The instant specification generally relates to autonomous vehicles. More specifically, the instant specification relates to autonomous vehicle sensor security, authentication and safety” ([0002]) and “In all such systems, accurate lane estimation can be performed automatically without a driver input or control (e.g., while the vehicle is in motion) and result in improved reliability of vehicle positioning and navigation and the overall safety of autonomous, semi-autonomous, and other driver assistance systems” ([0030]) thereby demonstrating the safety improvement that will result from the combination of inventions.
Regarding claims 3 and 13, Yun et al. and Dharia et al. disclose the system and method of claims 1 and 11. Dharia et al. further indicate recognizing the visual cue as the visual indication of at least one of the directionality of the temporary traffic lane and the second directionality of the adjacent temporary traffic lane comprises recognizing the visual cue as the visual indication of the second directionality of the adjacent temporary traffic lane, wherein the one or more processors are further configured to: determine a direction that is opposite to the second directionality of the adjacent temporary traffic lane; and predict the directionality of the temporary traffic lane based on the direction that is opposite to the different directionality of the adjacent temporary traffic lane (For example, the perception system 130 can analyze images captured by the cameras 118 and can be capable of detecting traffic light signals, road signs, roadway layouts (e.g., boundaries of traffic lanes, topologies of intersections, designations of parking places, and so on), presence of obstacles, and the like, [0035], “In one example, camera 118, radar 114, and/or lidar 112 can determine that the path ahead (e.g., a current driving lane) is hindered by one or more road primitives (e.g., cones or traffic signs). The AVCS 140 can cause the AV 100 to alter a driving path (e.g., change lanes) based on the detected one or more road primitives (e.g., identifying a spatial relationship between the road primitives, detecting displayed navigational instructions associated with the road primitives). As will be described in further detail below with reference to FIG. 2, the data processing system 120 can determine the status of a lane (e.g., temporary lane closure) based on the detection of the one or more road primitives. The AVCS 140 can then output instructions to powertrain, brakes and steering 150 to route the AV through a temporary travel path (e.g., a detour) and return the AV to an original driving path after determining the status of the associated lane has returned to a previous state (e.g., a normal or active lane state). Based on this determination, the AVCS 140 can output instructions to the powertrain, brakes and steering 150 to drive around the candidate object. The data processing system 120 may provide data used to predict the behavior of objects (e.g., vehicles, pedestrians, etc.) in the driving environment of the AV. The AVCS 140 may alter driving behavior of the AV responsive to data indicating future states of objects within the driving environments. The data processing system 120 may detect a construction zone and detect that an oncoming lane shifts or merges into the current lane of the AV. The data processing system 120 may communicate to the AV to choose to yield or nudge accordingly based on the object detection (e.g., oncoming vehicles). For example, the data processing system 120 may determine that a two-way road with two lanes in each direction has a construction zone in which the oncoming traffic lanes are closed and one of the lanes of traffic in the direction of the AV's motion is provided for the oncoming traffic.”, [0040]).
Regarding claims 4 and 14, Yun et al. and Dharia et al. disclose the system and method of claims 1 and 11. Yun et al. further indicate the second indication of directionality provided by the human traffic controller comprises at least one of a gesture of the human traffic controller and a verbal instruction of the human traffic controller (“Based on object information, the processor 717 may determine a hand signal given by a person. When a person giving a hand signal is determined to be a first priority object, the processor 717 may determine a driving lane based on the hand signal. When the hand signal given by the person is determined to guide the vehicle 100 to move rightward, the processor 717 may determine that a driving lane detours to the right side of the person. For example, when the hand signal given by the person is determined to guide the vehicle 100 to move leftward, the processor 717 may determine that a driving lane detours to the left side of the person”, [0327]-[0330], For example, when it is determined that a hand signal given by the person 13, who is determined to be a first object, guides the vehicle 100 to the right, the processor 717 may determine that a path detouring to the right side of the person 13 is a driving lane, [0481]).
Regarding claims 5 and 15, Yun et al. and Dharia et al. disclose the system and method of claims 4 and 14. Yun et al. further indicate the gesture of the human traffic controller comprises pointing in a particular direction in association with at least one of the temporary traffic lane and the adjacent temporary traffic lane, and wherein the one or more processors are further configured to: recognize, based on image data in the sensor data, the gesture as pointing in the particular direction in association with at least one of the temporary traffic lane and the adjacent temporary traffic lane; and predict the directionality of the temporary traffic lane based on the gesture of the human traffic controller pointing in the particular direction in association with at least one of the temporary traffic lane and the adjacent temporary traffic lane (“Based on object information, the processor 717 may determine a hand signal given by a person. When a person giving a hand signal is determined to be a first priority object, the processor 717 may determine a driving lane based on the hand signal. When the hand signal given by the person is determined to guide the vehicle 100 to move rightward, the processor 717 may determine that a driving lane detours to the right side of the person. For example, when the hand signal given by the person is determined to guide the vehicle 100 to move leftward, the processor 717 may determine that a driving lane detours to the left side of the person”, [0327]-[0330], For example, when it is determined that a hand signal given by the person 13, who is determined to be a first object, guides the vehicle 100 to the right, the processor 717 may determine that a path detouring to the right side of the person 13 is a driving lane, [0481]).
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Regarding claims 9 and 18, Yun et al. and Dharia et al. disclose the system and method of claims 1 and 11. Yun et al. further indicate the one or more processors are configured to: determine at least one of a position and an angle of a first set of objects from the one or more objects on the road, wherein the first set of objects are located at an end of the at least one boundary of the temporary traffic lane; determine that vehicles traveling from a pre-existing traffic lane should merge onto the temporary traffic lane based on at least one of the position and the angle of the first set of objects from the one or more objects on the road; and predict the directionality of the temporary traffic lane at least partly based the determination that vehicles traveling from the pre-existing traffic lane should merge onto the temporary traffic lane, wherein the directionality of the temporary traffic lane matches a particular direction of travel associated with the pre-existing traffic lane (When a line 10 is detected from the road surface based on object information, the processor 717 may output, to the windshield display 251c, a detection check image 23 corresponding to a line 10, [0472], For example, based on object information, the processor 717 may determine that a plurality of traffic cones 12 exists in front of the vehicle 100. A traffic cone 12 is one of path guidance objects, [0484], “Based on the path 14a of travel of the preceding vehicle and a shape and a location of a detected object, the processor 717 may determine that an object which was used as the basis of determining a path during travelling of the preceding vehicle 14 is a first priority object. For example, when it is determined, based on the path 14a of travel of the preceding vehicle 14 and a shape and a location of the line 10, that the preceding vehicle 14 is travelling along the line 10 painted on a road surface, the processor 717 may determine that the line 10 is a first priority object. For example, when it is determined, based on the path 14a of travel of the preceding vehicle 14 and positions of a plurality of traffic cones 12, that the preceding vehicle 14 is travelling along the plurality of traffic cones, the processor 717 may determine that each of the traffic cones 12 is the first priority object. In the example of FIG. 13, the processor 717 may determine that the preceding vehicle 14 is travelling along the plurality of traffic cones 12. The processor 717 may determine each of the plurality of traffic cones 12 to be the first priority object. The processor 717 may determine a driving lane preferentially based on the plurality of traffic cones 12. The processor 717 may determine that a region formed in a direction of arrangement of the plurality of traffic cones 12 is a driving lane for the vehicle 100”, [0489]-[0494]).
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Claim(s) 6, 7, 16 and 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Yun et al. (US 20190019413 A1) and Dharia et al. (US 20220392229 A1) as applied to claims 4 and 14 above, further in view of Foster et al. (US 20230140569 A1).
Regarding claims 6 and 16, Yun et al. and Dharia et al. disclose the system and method of claims 4 and 14. Yun et al. and Dharia et al. do not disclose the second indication of directionality provided by the human traffic controller comprises the verbal instruction, and wherein the one or more processors are further configured to: based on recorded audio in the sensor data, recognize, using a speech recognition algorithm, the verbal instruction of the human traffic controller; and predict the directionality of the temporary traffic lane based on the verbal instruction of the human traffic controller.
Foster et al. teach a second indication of directionality provided by the human traffic controller comprises the verbal instruction, and wherein the one or more processors are further configured to: based on recorded audio in the sensor data, recognize, using a speech recognition algorithm, the verbal instruction of the human traffic controller (“A sound detection array, such as a microphone or array of microphones, may be included in the vehicle sensor subsystem 144. The microphones of the sound detection array are configured to receive audio indications of the presence of, or instructions from, authorities, including sirens and command such as “Pull over.” These microphones are mounted, or located, on the external portion of the vehicle, specifically on the outside of the tractor portion of an autonomous truck 105. Microphones used may be any suitable type, mounted such that they are effective both when the autonomous truck 105 is at rest, as well as when it is moving at normal driving speeds”, [0337]).
Yun et al. and Foster et al. together teach predict the directionality of the temporary traffic lane based on the verbal instruction of the human traffic controller (Yun et al., predict the directionality of the temporary traffic lane based on the instruction of the human traffic controller, [0327]-[0330]; Foster et al., verbal instruction of the human traffic controller).
Yun et al. and Foster et al. are in the same art of autonomous driving systems and detecting temporary lanes (Yun et al., abstract, [0017], [0313]; Foster et al., abstract, [0529]). The combination of Foster et al. with Yun et al. and Dharia et al. enables using verbal instructions. It would have been obvious at the time of filing to one of ordinary skill in the art to combine the verbal detection of Foster et al. with the invention of Yun et al. as this was known at the time of filing, the combination would have predictable results, as verbal instructions are one of a limited number of possible sensor inputs to be considered, and as Foster et al. indicate “One aim of autonomous vehicle technologies is to provide vehicles that can safely navigate towards a destination with limited or no driver assistance. The safe navigation of an autonomous vehicle (AV) from one point to another may include the ability to signal other vehicles, navigating around other vehicles in shoulders or emergency lanes, changing lanes, biasing appropriately in a lane, and navigate all portions or types of highway lanes. Autonomous vehicle technologies may enable an AV to operate without requiring extensive learning or training by surrounding drivers, by ensuring that the AV can operate safely, in a way that is evident, logical, or familiar to surrounding drivers and pedestrians. Systems and methods are described herein that allow an autonomous vehicle (AV) to navigate from a first point to a second point without a human driver present in the AV and to comply with instructions for safe and lawful operation” ([0003]-[0004]), providing a user benefit of requiring minimal to no user interaction and an improvement to convenience and safety when inventions are combined.
Regarding claims 7 and 17, Yun et al. and Dharia et al. disclose the system and method of claims 1 and 11. Yun et al. do not disclose the first indication of the direction of travel of the vehicle traveling through the temporary traffic lane or the adjacent temporary traffic lane indicates the direction of travel of the vehicle through the temporary traffic lane, and wherein predicting the directionality of the temporary traffic lane comprises predicting the directionality of the temporary traffic lane at least partly based on the direction of travel of the vehicle through the temporary traffic lane.
Foster et al. teach the first indication of the direction of travel of the vehicle traveling through the temporary traffic lane or the adjacent temporary traffic lane indicates the direction of travel of the vehicle through the temporary traffic lane, and wherein predicting the directionality of the temporary traffic lane comprises predicting the directionality of the temporary traffic lane at least partly based on the direction of travel of the vehicle through the temporary traffic lane (FIG. 8AW is a schematic showing a construction zone flagger using a “proceed road users” hand signal to allow oncoming vehicles to move forward, [0268], As an example, if localization accuracy of the received GPS signal degrades on a highway, the autonomous vehicle 105 may plan to drive straight. In other words, the autonomous vehicle 105 may continue driving in the current lane using lane markers detected by the equipped sensors until it regains localization of the GPS signal, [0482], To allow the stopped traffic to proceed, officers may point towards the first stopped vehicle, and then use the other hand to motion the driver to proceed. The autonomous vehicle 105 may follow the guidance from law enforcement authorities to stop or navigate through accident areas, [0511]).
Yun et al. and Foster et al. are in the same art of autonomous driving systems and detecting temporary lanes (Yun et al., abstract, [0017], [0313]; Foster et al., abstract, [0529]). The combination of Foster et al. with Yun et al. and Dharia et al. enables predicting the directionality of the temporary traffic lane comprises predicting the directionality of the temporary traffic lane at least partly based on the direction of travel of the vehicle. It would have been obvious at the time of filing to one of ordinary skill in the art to combine the predicting of Foster et al. with the invention of Yun et al. and Dharia et al. as this was known at the time of filing, the combination would have predictable results, and as Foster et al. indicate “One aim of autonomous vehicle technologies is to provide vehicles that can safely navigate towards a destination with limited or no driver assistance. The safe navigation of an autonomous vehicle (AV) from one point to another may include the ability to signal other vehicles, navigating around other vehicles in shoulders or emergency lanes, changing lanes, biasing appropriately in a lane, and navigate all portions or types of highway lanes. Autonomous vehicle technologies may enable an AV to operate without requiring extensive learning or training by surrounding drivers, by ensuring that the AV can operate safely, in a way that is evident, logical, or familiar to surrounding drivers and pedestrians. Systems and methods are described herein that allow an autonomous vehicle (AV) to navigate from a first point to a second point without a human driver present in the AV and to comply with instructions for safe and lawful operation” ([0003]-[0004]) and “In some embodiments, the instructions further cause the processor to cause the autonomous vehicle to stay within its lane when executing an evasive maneuver unless evasive braking alone is not enough to prevent a collision” ([0018]), providing a user benefit of requiring minimal to no user interaction and an improvement to convenience and safety when inventions are combined.
Claim(s) 8 is/are rejected under 35 U.S.C. 103 as being unpatentable over Yun et al. (US 20190019413 A1) and Dharia et al. (US 20220392229 A1) as applied to claim 4 above, further in view of Ebrahimi Afrouzi et al. (US 20220066456 A1).
Regarding claim 8, Yun et al. and Dharia et al. disclose the system of claim 1. Yun et al. further indicate “The lane OB10 may be a lane in which the vehicle 100 is traveling, a lane next to the lane in which the vehicle 100 is travelling, or a lane in which a different vehicle is travelling in the opposite direction ([0125]) but do not disclose the first indication of the direction of travel of the vehicle traveling through the temporary traffic lane or the adjacent temporary traffic lane indicates the direction of travel of the vehicle through the adjacent temporary traffic lane, and wherein predicting the directionality of the temporary traffic lane comprises: determining a direction that is opposite to the direction of travel of the vehicle through the adjacent temporary traffic lane; and predicting the directionality of the temporary traffic lane at least partly based on the direction that is opposite to the direction of travel of the vehicle through the adjacent temporary traffic lane.
Ebrahimi Afrouzi et al. teach the first indication of the direction of travel of the vehicle traveling through the temporary traffic lane or the adjacent temporary traffic lane indicates the direction of travel of the vehicle through the adjacent temporary traffic lane, and wherein predicting the directionality of the temporary traffic lane comprises: determining a direction that is opposite to the direction of travel of the vehicle through the adjacent temporary traffic lane; and predicting the directionality of the temporary traffic lane at least partly based on the direction that is opposite to the direction of travel of the vehicle through the adjacent temporary traffic lane (The prediction of the map of the surroundings may further enhance navigation decisions. For example, in a two way street a processor of a vehicle may not only localize the vehicle against its surroundings but may localize other cars, including those driving in an opposite direction, and create an assumed map of the surrounding and plan the motion of the vehicle by predicting a next move of the other vehicles, rather than waiting to see what the other vehicles do and then reacting, [0480]).
Yun et al. and Ebrahimi Afrouzi et al. are in the same art of autonomous driving systems and detecting temporary lanes (Yun et al., abstract, [0017]; Ebrahimi Afrouzi et al., [0004]). The combination of Ebrahimi Afrouzi et al. with Yun et al. and Dharia et al. enables predicting the directionality based on an opposite direction. It would have been obvious at the time of filing to one of ordinary skill in the art to combine the opposite direction detection of Ebrahimi Afrouzi et al. with the invention of Yun et al. and Dharia et al. as this was known at the time of filing, the combination would have predictable results, and as Ebrahimi Afrouzi et al. indicate “In embodiments, deep learning may be used to improve perception, improve trajectory such that it follows the planned path more accurately, improve coverage, improve obstacle detection and collision prevention, improve decision making such that it is more human-like, improve decision making in situation wherein some data is missing, etc.” ([0307]) providing an improved collision prevention and increased safety when the inventions are combined.
Claim(s) 10 and 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Yun et al. (US 20190019413 A1) and Dharia et al. (US 20220392229 A1) as applied to claims 1 and 11 above, further in view of Chia et al. (US 20170160744 A1).
Regarding claims 10 and 19, Yun et al. and Dharia et al. disclose the system and method of claims 1 and 11. Yun et al. partly indicate the one or more processors are configured to: assign respective weights to the one or more cues, each cue being assigned a respective weight, wherein each respective weight is indicative of a confidence level of a reliability of directionality information determined from the cue associated with the respective weight; and predict the directionality of the temporary traffic lane based on the respective weights and directionality information associated with the one or more cues, wherein the sensor data comprises at least one of data from a light detection and ranging sensor, data from a radio detection and ranging sensor, image data from a camera sensor, data from a time-of-flight sensor, data from an infrared sensor, and data from an acoustic sensor (determine a driving lane for the vehicle based on a preset priority order and the object information, and when it is determined that a preset event has occurred, change the priority order based on the object information, [0013], The detection processor 370 may generate object information based on at least one of the following: an image acquired using the camera 310, a reflected electromagnetic wave received using the RADAR 320, a reflected laser beam received using the LIDAR 330, a reflected ultrasonic wave received using the ultrasonic sensor 340, and a reflected infrared light received using the infrared sensor 350, [0159]) however another reference is added to make this more explicit.
Chia et al. assign respective weights to the one or more cues, each cue being assigned a respective weight, wherein each respective weight is indicative of a confidence level of a reliability of directionality information determined from the cue associated with the respective weight; and predict the directionality of the temporary traffic lane based on the respective weights and directionality information associated with the one or more cues, wherein the sensor data comprises at least one of data from a light detection and ranging sensor, data from a radio detection and ranging sensor, image data from a camera sensor, data from a time-of-flight sensor, data from an infrared sensor, and data from an acoustic sensor (“Camera detects and measures lane markers providing data to controller; Radar/Lidar scans environment around vehicle providing a detection map; Mature higher confidence radar detection points are collected on a radar map; Processing is performed on radar/lidar detection map to generate contours parallel to a travel-path or travel-lane of the host-vehicle; Plausible candidate contours that meet criteria are submitted to controller; When both vision and ranging sensor data are available together, correlation and similarity measures are formed to establish positional relationships indicated by the data; Relative position and distances between vision and radar/lidar measurements are stored; If correlation no longer holds, vision and radar/lidar data is decoupled; When both camera and radar/lidar data are present with high confidence, automatic lane control steering is weighted towards use of camera detected data; and When radar/lidar data is only available (camera low or no confidence), automatic lane control shifts to use of radar/lidar data adjusted accordingly to the positional relationships noted previously”, [0008]-[0017]).
Yun et al. and Chia et al. are in the same art of autonomous driving systems and detecting temporary lanes (Yun et al., abstract, [0017]; Chia et al., [0025]). The combination of Chia et al. with Yun et al. and Dharia et al. enables assigning weights according to sensor reliability. It would have been obvious at the time of filing to one of ordinary skill in the art to combine the weighting of Chia et al. with the invention of Yun et al. and Dharia et al. as this was known at the time of filing, the combination would have predictable results, and as Chia et al. indicate “The problem of not having sufficient vision information to operate a lateral control application can be solved by using frontal, side, and/or rear ranging-sensors. The system describe herein may be economically advantageous as these sensor are often already present for other sensing systems. Ranging sensors can include radars or lidars. These sensors can be employed to indicate distance to stationary or moving objects around the vehicle which can include curbs, barriers, walls, foliage, vegetation, terrain features, cars, trucks, and other roadway objects. For example, radars may already be installed on the vehicle for adaptive cruise control, crash avoidance and mitigation, blind spot warning or parking assistance. The combined use of vision and ranging sensor for identifying the scene around the host vehicle can provide a viable means to extend lane following control availability when vision data is temporarily unavailable” ([0003]) thereby providing a safety benefit to the combination of inventions.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/MICHELLE M ENTEZARI HAUSMANN/Primary Examiner, Art Unit 2671
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