DETAILED ACTION
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 .
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Response to Arguments
Applicant’s arguments, see Pg. 7, filed 07/03/2025, with respect to the 35 USC 112(b) rejection of claims 1-5 have been fully considered and are persuasive.
The Examiner is in agreement that the amendments to the claims correct the previously-raised indefiniteness concerns. Accordingly, the 35 USC 112(b) rejection of claims 1-5 has been withdrawn.
Applicant’s arguments, see Pg. 7, filed 07/03/2025, with respect to the 35 USC 101 rejection of claims 1-5 have been fully considered and are persuasive.
The Examiner is in agreement that the amendments to independent claims 1, 4, and 5 now satisfy the requirements of 35 USC 101, as each of the independent claims now include performing autonomous driving along the travel route based on the detection of the pedestrian and the pause-by object, thereby incorporating the judicial exception(s) into a practical application. Accordingly, the 35 USC 101 rejection of claims 1-5 has been withdrawn.
Applicant’s arguments, see Pgs. 7-8, filed 07/03/2025, with respect to the 35 USC 103 rejection of independent claims 1 and 4-5 and their respective dependent claims have been fully considered and are partially persuasive.
Applicant argues that Tanaka and Sakamoto fail to teach or suggest “the vicinity being within a predetermined distance threshold relative to the identified position of the pause-by object and the pedestrian, perform autonomous driving along the travel route in response to determining that the pedestrian is detected and based on the identified position of the pause-by object being in the vicinity of the pedestrian, and set one or more points on a center of a pair of lane lines, wherein a first travel route is created, as the travel route, passing through a first center point between the pedestrian and one of the pair of lane lines when the pedestrian will enter road, and wherein a second travel route is created passing through a second center point between another of the pair of lane lines when the pedestrian will not enter the road.” The Examiner is in partial agreement with Applicant’s arguments.
With respect to the limitations “the vicinity being within a predetermined distance threshold relative to the identified position of the pause-by object and the pedestrian, perform autonomous driving along the travel route in response to determining that the pedestrian is detected and based on the identified position of the pause-by object being in the vicinity of the pedestrian,”, the Examiner respectfully asserts that Sakamoto does teach or suggest these limitations in at least paragraphs [0031]-[0033], [0040], and [0096] (see in particular teachings pertaining to automated driving to avoid passing through warning region R and expanding warning region R).
With respect to the limitations “and set one or more points on a center of a pair of lane lines, wherein a first travel route is created, as the travel route, passing through a first center point between the pedestrian and one of the pair of lane lines when the pedestrian will enter road, and wherein a second travel route is created passing through a second center point between another of the pair of lane lines when the pedestrian will not enter the road.”, the Examiner is in agreement with Applicant’s arguments, as neither Tanaka nor Sakamoto teach or suggest the claimed center points.
Accordingly, the 35 USC 103 rejection of independent claims 1 and 4-5 and their respective dependent claims has been withdrawn. Upon further search and consideration of the modified scope of the claims, a new ground(s) of rejection is made over Tanaka, Sakamoto, and Toda.
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.
Claims 1-11 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.
Regarding independent claims 1, 4, and 5, independent claim 1 recites “and set one or more points on a center of a pair of lane lines, wherein a first travel route is created, as the travel route, passing through a first center point between the pedestrian and one of the pair of lane lines when the pedestrian will enter road, and wherein a second travel route is created passing through a second center point between another of the pair of lane lines when the pedestrian will not enter the road.” Here, the phrasing of “one of the pair of lane lines” and “another of the pair of lane lines” renders the claim indefinite, as the definition of “one of the pair of lane lines” and “another of the pair of lane lines” is unclear. Specifically, “one of the pair of lane lines” makes it unclear whether the “one” refers to one particular lane line of the already-claimed “a pair of lane lines” or whether the “one” refers collectively to “a pair of lane lines”. Similarly, “another of the pair of lane lines” makes it unclear whether “another” refers to a different lane line of the already-claimed “a pair of lane lines”, whether the “another” refers to a second, separate pair of lane lines, or whether “another of the pair of lane lines” refers to a duplication of “the pair of lane lines”. Independent claims 4 and 5 recite parallel limitations; therefore, independent claims 4 and 5 are rejected under similar reasoning as independent claim 1.
Claims 2-3 and 6-11 are dependent upon claim 1 and therefore inherit the above-described deficiencies. Accordingly, claims 2-3 and 6-11 are rejected under similar reasoning as claim 1 above.
Regarding claim 2, the claim recites “and in the creation, creates the second travel route assuming the pedestrian will not enter the road even when the pedestrian is detected…” However, antecedent basis for “the creation” is unclear. Claim 1, upon which claim 2 depends, recites several instances of creation: “create a travel route over which the vehicle will travel when the pedestrian is detected,”, “wherein a first travel route is created, as the travel route,”, and “wherein a second travel route is created”. While the claim does refer to creating the second travel route, it is still unclear whether “the creation” specifically refers to the creation of the second travel route. Therefore, it is unclear which “creation” claim 2 intends to refer to.
Claim 8 is dependent upon claim 2 and therefore inherits the above-described deficiencies. Accordingly, claim 8 is rejected under similar reasoning as claim 2 above.
Regarding claim 3, the claim recites “and in the creation, creates the second travel route assuming the pedestrian will not enter the road when the pedestrian is detected…” However, antecedent basis for “the creation” is unclear. Claim 1, upon which claim 3 depends, recites several instances of creation: “create a travel route over which the vehicle will travel when the pedestrian is detected,”, “wherein a first travel route is created, as the travel route,”, and “wherein a second travel route is created”. While the claim does refer to creating the second travel route, it is still unclear whether “the creation” specifically refers to the creation of the second travel route. Therefore, it is unclear which “creation” claim 3 intends to refer to.
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1-9 is/are rejected under 35 U.S.C. 103 as being unpatentable over Tanaka et al. (US 2021/0146958 A1), hereinafter Tanaka, in view of Sakamoto et al. (US 2018/0349714 A1), hereinafter Sakamoto, and in further view of Toda et al. (US 2020/0279487 A1), hereinafter Toda.
Regarding claim 1, Tanaka teaches a route planner comprising a processor configured to:
detect a pedestrian from surrounding data representing a situation of surroundings of a vehicle,
Tanaka teaches ([0059]): "A surrounding situation sensor 141 recognizes surrounding situation information of the vehicle M1… The surrounding situation information includes target information about a target recognized by the surrounding situation sensor 141. The target is exemplified by a surrounding vehicle, a pedestrian, a roadside structure, an obstacle, a white line, a signal, and the like."
identify a position of a pause-by object in the surroundings of the vehicle prompting the pedestrian to pause,
Tanaka teaches ([0051]): "The intervention suppression area information 134 is information in which a geographic region (hereinafter referred to as an "intervention suppression area") in which intervention of preventative safety control is to be suppressed is associated with map information (location information). Typically, the intervention suppression area corresponds to a specific area in which substantial safety is expected, such as around a stop area or a boarding and alighting area for a passenger transport vehicle..." Tanaka further teaches ([0054]): "FIG. 5 shows an example of an operation timing of the preventive safety control when the vehicle M1, as a commercial bus, approaches and stops at a bus area. For example, as shown in FIG. 5, in the case where the surrounding of the bus stop area is set as the intervention suppression area..." FIG. 5, included below, depicts the identification of the pause-by object in the surrounding of the vehicle prompting the pedestrian to pause.
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create a travel route over which the vehicle will travel when the pedestrian is detected,
Tanaka teaches ([0073]): "For example, the first controller 12 generates a target trajectory for stopping the vehicle M1 at a stop area. More specifically, the first controller 12 recognizes a stop area as a destination and a person or a structure around the stop area based on the map information 132, the vehicle position information, and the surrounding situation information. Then, the first controller 12 generates a target trajectory for stopping at the stop area while avoiding the surrounding people and structures, based on these information."
However, Tanaka does not outright teach assuming the pedestrian will enter a road on which the vehicle will travel when the identified position of the pause-by object is not in a vicinity of the pedestrian, and assuming the pedestrian will not enter the road when the identified position of the pause-by object is in the vicinity of the pedestrian, the vicinity being within a predetermined distance threshold relative to the identified position of the pause-by object and the pedestrian, and performing autonomous driving along the travel route in response to determining that the pedestrian is detected and based on the identified position of the pause-by object being in the vicinity of the pedestrian. Sakamoto teaches a pedestrian behavior prediction apparatus and method, comprising:
assuming the pedestrian will enter a road on which the vehicle will travel when the identified position of the pause-by object is not in a vicinity of the pedestrian,
Sakamoto teaches ([0093]): "In the above-described first to fourth embodiments, when it is determined that the person 32 visually recognizes a predetermined object, crossing of the person 32 is predicted. However, if an object that interrupts crossing does not exist, crossing may be started regardless of the presence/absence of visual recognition of the predetermined object." Sakamoto further teaches ([0094]): "FIG. 8A is a plan view showing a state in which an own vehicle 1 is traveling on a roadway 21 by automated driving as the fifth embodiment. In this embodiment, sidewalks 22 are partitioned from the roadway 21 by partition members 33D." Sakamoto even further teaches ([0095]): "The partition member 33D is provided with a gap SP capable of passing a walker. In this embodiment, a person 32 exists near the gap SP on the sidewalk 22." Sakamoto still further teaches ([0096]): "Here, as shown in FIG. 8B, in a case in which the person 32 exists near the gap SP, there is a possibility that the person 32 has a desire to move across the roadway 21 through the gap SP. Hence, in a case in which it is confirmed that the person 32 exists within the range of a predetermined distance from the gap SP, the prediction ECU 17 predicts that the person 32 moves in the crossing direction through the gap SP and expands the warning region R to the side of the roadway 21, as indicated by an arrow E4." The Examiner has interpreted the person 32 existing within the predetermined distance of the gap SP as amounting to the pedestrian not being in a vicinity of the pause-by object (i.e., the partition member).
and assuming the pedestrian will not enter the road when the identified position of the pause-by object is in the vicinity of the pedestrian,
Sakamoto teaches ([0094]): "FIG. 8A is a plan view showing a state in which an own vehicle 1 is traveling on a roadway 21 by automated driving as the fifth embodiment. In this embodiment, sidewalks 22 are partitioned from the roadway 21 by partition members 33D." Sakamoto further teaches ([0095]): "The partition member 33D is provided with a gap SP capable of passing a walker. In this embodiment, a person 32 exists near the gap SP on the sidewalk 22." Sakamoto even further teaches ([0096]): "Here, as shown in FIG. 8B, in a case in which the person 32 exists near the gap SP, there is a possibility that the person 32 has a desire to move across the roadway 21 through the gap SP. Hence, in a case in which it is confirmed that the person 32 exists within the range of a predetermined distance from the gap SP, the prediction ECU 17 predicts that the person 32 moves in the crossing direction through the gap SP and expands the warning region R to the side of the roadway 21, as indicated by an arrow E4." Sakamoto still further teaches ([0097]): " According to this embodiment, the arrangement form of the partition member 33D is considered, and crossing of the person 32 is predicted based on the presence/absence of the gap SP in the partition member 33D. For this reason, according to this embodiment, it is possible to perform behavior prediction of the person 32 at a high accuracy." Therefore, when the pedestrian is in the vicinity of the pause-by object (i.e., the pedestrian is near the partition member and a gap is not present), the person 32 is not predicted to cross.
the vicinity being within a predetermined distance threshold relative to the identified position of the pause-by object and the pedestrian,
Sakamoto teaches ([0096]): "Here, as shown in FIG. 8B, in a case in which the person 32 exists near the gap SP, there is a possibility that the person 32 has a desire to move across the roadway 21 through the gap SP. Hence, in a case in which it is confirmed that the person 32 exists within the range of a predetermined distance from the gap SP, the prediction ECU 17 predicts that the person 32 moves in the crossing direction through the gap SP and expands the warning region R to the side of the roadway 21, as indicated by an arrow E4."
perform autonomous driving along the travel route in response to determining that the pedestrian is detected and based on the identified position of the pause-by object being in the vicinity of the pedestrian,
Sakamoto teaches ([0031]): "The own vehicle 1 detects the objects 3 on the roadway 21 and sidewalks 22 by the detection unit 16, and sets a traveling route so as to avoid the objects, thereby performing automated driving. " Sakamoto further teaches ([0033]): "As shown in FIG. 3, if the plurality of objects 3 are confirmed from the detection result (peripheral information of the vehicle 1) of the detection unit 16, the prediction ECU 17 sets a warning region R for each object 3. The warning region R is a region used to avoid contact of the own vehicle 1, that is, a region recommended not to overlap the own vehicle 1." Sakamoto even further teaches ([0040]): "Based on the prediction result from the prediction ECU 17, the traveling control ECU 12 sets a traveling route not to pass through the warning region R for each object 3, thereby preventing the own vehicle 1 from coming into contact with each object 3." Sakamoto still further teaches ([0096]): "Here, as shown in FIG. 8B, in a case in which the person 32 exists near the gap SP, there is a possibility that the person 32 has a desire to move across the roadway 21 through the gap SP. Hence, in a case in which it is confirmed that the person 32 exists within the range of a predetermined distance from the gap SP, the prediction ECU 17 predicts that the person 32 moves in the crossing direction through the gap SP and expands the warning region R to the side of the roadway 21, as indicated by an arrow E4."
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Tanaka to incorporate the teachings of Sakamoto to provide assuming the pedestrian will enter a road on which the vehicle will travel when the identified position of the pause-by object is not in a vicinity of the pedestrian, and assuming the pedestrian will not enter the road when the identified position of the pause-by object is in the vicinity of the pedestrian, the vicinity being within a predetermined distance threshold relative to the identified position of the pause-by object and the pedestrian, and performing autonomous driving along the travel route in response to determining that the pedestrian is detected and based on the identified position of the pause-by object being in the vicinity of the pedestrian. Tanaka and Sakamoto are each directed towards similar pursuits in the field of pedestrian behavior monitoring for vehicles. Accordingly, one of ordinary skill in the art would find it advantageous to incorporate the behavior prediction of Sakamoto, as doing so beneficially allows for behavior prediction of the pedestrian at a high accuracy based on proximity to (or away from) the pause-by object, as recognized by Sakamoto (see at least [0097]). Further, Sakamoto advantageously allows for collision avoidance based on the behavior prediction (see at least [0031]-[0033] and [0040]).
However, neither Tanaka nor Sakamoto teach or suggest setting one or more points on a center of a pair of lane lines, wherein a first travel route is created, as the travel route, passing through a first center point between the pedestrian and one of the pair of lane lines when the pedestrian will enter road, and wherein a second travel route is created passing through a second center point between another of the pair of lane lines when the pedestrian will not enter the road. Toda teaches a vehicle control apparatus and method, comprising:
and set one or more points on a center of a pair of lane lines,
Toda teaches ([0047]): "The second control unit 160 includes, for example, an acquisition unit 162, a speed control unit 164, and a steering control unit 166. The acquisition unit 162 acquires information on the target trajectory (trajectory points) generated by the action plan generation unit 140 and stores it in a memory (not shown)." FIG. 4, included below, demonstrates that the target trajectory includes one or more points on a center of a pair of lane lines (i.e., the center between LL and R).
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wherein a first travel route is created, as the travel route, passing through a first center point between the pedestrian and one of the pair of lane lines when the pedestrian will enter road,
Toda teaches ([0075]): "The pedestrian avoidance determination unit 141 acquires information on a current position and a speed V2 in a transverse direction of a crossing pedestrian (P2 in FIG. 4) recognized by the pedestrian recognition unit 131, and estimates a future position of the crossing pedestrian at a certain time point on the basis of the acquired information. The certain time point is a future time point at which the host vehicle M reaches the same position as the crossing pedestrian in a lane direction. When the position of the crossing pedestrian at the time point overlaps with a line of sight area Q having a width slightly larger than a width of the host vehicle M around a target trajectory K of the host vehicle M, it is determined that the crossing pedestrian will interfere with the trajectory of the host vehicle M." Toda further teaches ([0078]): "In principle, when the pedestrian avoidance determination unit 141 determines that the crossing pedestrian interferes with the trajectory of the host vehicle M, the avoidance control unit 142 controls the speed control unit 164 and/or the steering control unit 166, and executes a predetermined avoidance support for avoiding contact between the vehicle and the crossing pedestrian by controlling one or both of the steering and acceleration/deceleration of the vehicle." Toda even further teaches ([0079]): "The predetermined avoidance support is, for example, causing the host vehicle M to perform some or all of deceleration, slowing down, temporary stopping, and avoidance by steering by controlling the speed control unit 164 and/or the steering control unit 166." Referring to FIG. 4, included above, one of ordinary skill in the art would recognize that causing the host vehicle M to perform deceleration and temporary stopping of the vehicle would still result in the vehicle passing through at least one of the center points (i.e., the trajectory points).
and wherein a second travel route is created passing through a second center point between another of the pair of lane lines when the pedestrian will not enter the road.
Toda teaches ([0092]): "FIG. 6 is a diagram which shows a state of determining whether the pedestrian P is crossing the road L. Another vehicle m is traveling on the oncoming lane L2 side and the avoidance control unit 142 determines that a state of the oncoming lane L2 side is not suitable for crossing. The pedestrian recognition unit 131 determines that a pedestrian P2 is not a crossing pedestrian even when the pedestrian P2 is moving in a direction of the road L and a negative determination is obtained in step S102 on the basis of the result of the determination by the avoidance control unit 142. In addition, it is determined that a pedestrian who is not moving to the road L side, such as a pedestrian P3, is not a crossing pedestrian, and a negative determination is obtained in step S102. When a negative determination is obtained in step S102, the avoidance support is not performed." Toda further teaches ([0078]): "In principle, when the pedestrian avoidance determination unit 141 determines that the crossing pedestrian interferes with the trajectory of the host vehicle M, the avoidance control unit 142 controls the speed control unit 164 and/or the steering control unit 166, and executes a predetermined avoidance support for avoiding contact between the vehicle and the crossing pedestrian by controlling one or both of the steering and acceleration/deceleration of the vehicle." Therefore, when it is determined that the pedestrian will not enter the road, avoidance support is not performed and the host vehicle M is allowed to continue the trajectory normally. In the example of FIG. 4, included above, one of ordinary skill in the art would appreciate that if it were instead determined that that pedestrian P2 is not a crossing pedestrian, avoidance support would not be implemented and the host vehicle would be allowed to pass through a second center point (for example, a center point located beyond pedestrian P2).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Tanaka and Sakamoto to incorporate the teachings of Toda to provide setting one or more points on a center of a pair of lane lines, wherein a first travel route is created, as the travel route, passing through a first center point between the pedestrian and one of the pair of lane lines when the pedestrian will enter road, and wherein a second travel route is created passing through a second center point between another of the pair of lane lines when the pedestrian will not enter the road. Tanaka, Sakamoto, and Toda are each directed towards similar pursuits in the field of pedestrian behavior monitoring for vehicles. Accordingly, one of ordinary skill in the art would find it advantageous to incorporate the teachings of Toda, as the first and second travel routes of Toda beneficially allow for avoidance of a collision between the vehicle and a pedestrian determined to be entering the road (see at least [0078]-[0079]), while preventing unnecessary collision avoidance when a detected pedestrian will not enter the road (see at least [0092]).
Regarding claim 2, Tanaka, Sakamoto, and Toda teach the aforementioned limitations of claim 1. However, Tanaka does not outright teach that the processor, in the detection, further detects a facial orientation of the pedestrian from surrounding data, and in the creation, creates the second travel route assuming the pedestrian will not enter the road even when the pedestrian is detected and the identified position of the pause-by object is not in the vicinity of the pedestrian in a case where the facial orientation of the pedestrian is not toward the road. Sakamoto further teaches:
the processor, in the detection, further detects a facial orientation of the pedestrian from surrounding data,
Sakamoto teaches ([0047]): "The case in which it is confirmed that the person 32 visually recognizes a certain object... indicates a case in which the prediction ECU 17 determines that the object exists in the direction of line of sight (on the line of sight) of the person 32, as will be described later in detail. This determination is done based on the detection result of the detection unit 16." The Examiner has interpreted the determination of the direction of line of sight of the person 32 as detecting a facial orientation of the pedestrian.
and in the creation, creates the second travel route assuming the pedestrian will not enter the road even when the pedestrian is detected and the identified position of the pause-by object is not in the vicinity of the pedestrian in a case where the facial orientation of the pedestrian is not toward the road.
Sakamoto teaches ([0095]): "The partition member 33D is provided with a gap SP capable of passing a walker. In this embodiment, a person 32 exists near the gap SP on the sidewalk 22." Sakamoto further teaches ([0096]): "Here, as shown in FIG. 8B, in a case in which the person 32 exists near the gap SP, there is a possibility that the person 32 has a desire to move across the roadway 21 through the gap SP. Hence, in a case in which it is confirmed that the person 32 exists within the range of a predetermined distance from the gap SP, the prediction ECU 17 predicts that the person 32 moves in the crossing direction through the gap SP and expands the warning region R to the side of the roadway 21, as indicated by an arrow E4." Sakamoto even further teaches ([0097]): " According to this embodiment, the arrangement form of the partition member 33D is considered, and crossing of the person 32 is predicted based on the presence/absence of the gap SP in the partition member 33D. For this reason, according to this embodiment, it is possible to perform behavior prediction of the person 32 at a high accuracy." Sakamoto still further teaches ([0098]): "The contents of this embodiment can be applied to the first to fourth embodiments. For example, as another embodiment, in a case in which the own vehicle 1 is traveling on the roadway 21 partitioned by the partition members 33D, using confirmation of the gap SP as one condition, the prediction ECU 17 may predict crossing of the person 32 based on what the person 32 visually recognizes. As still another embodiment, the prediction ECU 17 may predict crossing of the person 32 upon determining that the gap SP is located in the direction of line of sight of the person 32." That is, if the gap SP is not located in the direction of line of sight of the person 32, crossing is not predicted. As shown in FIG. 8A, both the gap and the guard rail are located in the direction of the road from the person 32. Sakamoto yet further teaches ([0031]): "The own vehicle 1 detects the objects 3 on the roadway 21 and sidewalks 22 by the detection unit 16, and sets a traveling route so as to avoid the objects, thereby performing automated driving." Sakamoto finally teaches ([0040]): "Based on the prediction result from the prediction ECU 17, the traveling control ECU 12 sets a traveling route not to pass through the warning region R for each object 3, thereby preventing the own vehicle 1 from coming into contact with each object 3." The Examiner notes that the warning region R is still monitored for pedestrians using sidewalk 22, as shown in FIG. 3. Therefore, even when it is assumed that the pedestrian will not enter the road, the route is still created in a manner which prevents passing through the pedestrian's warning region R.
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Tanaka, Sakamoto, and Toda to further incorporate the teachings of Sakamoto to provide that the processor, in the detection, further detects a facial orientation of the pedestrian from surrounding data, and in the creation, creates the second travel route assuming the pedestrian will not enter the road even when the pedestrian is detected and the identified position of the pause-by object is not in the vicinity of the pedestrian in a case where the facial orientation of the pedestrian is not toward the road. Tanaka, Sakamoto, and Toda are each directed towards similar pursuits in the field of pedestrian behavior monitoring for vehicles. Accordingly, one of ordinary skill in the art would find it advantageous to incorporate the behavior prediction of Sakamoto, as doing so beneficially allows for behavior prediction of the pedestrian at a high accuracy based on proximity to (or away from) the pause-by object, as recognized by Sakamoto (see at least [0097]). Further, Sakamoto advantageously allows for collision avoidance based on the behavior prediction (see at least [0031]-[0033] and [0040]).
Regarding claim 3, Tanaka, Sakamoto, and Toda teach the aforementioned limitations of claim 1. However, Tanaka does not outright teach that the processor, in the detection, further detects an entry-restricting state restricting entry of the pedestrian to the road from the surrounding data, and in the creation, creates the second travel route assuming the pedestrian will not enter the road when the pedestrian is detected and the entry-restricting state is detected. Sakamoto further teaches:
the processor, in the detection, further detects an entry-restricting state restricting entry of the pedestrian to the road from the surrounding data,
Sakamoto teaches ([0031]): "The own vehicle 1 detects the objects 3 on the roadway 21 and sidewalks 22 by the detection unit 16, and sets a traveling route so as to avoid the objects, thereby performing automated driving." Sakamoto further teaches ([0032]): "The obstacle 33 may be, for example, a fallen object such as garbage, may be an installed object such as a traffic signal or a guard fence, and may be either a movable or an immovable." Sakamoto even further teaches([0094]): "FIG. 8A is a plan view showing a state in which an own vehicle 1 is traveling on a roadway 21 by automated driving as the fifth embodiment. In this embodiment, sidewalks 22 are partitioned from the roadway 21 by partition members 33D." Sakamoto still further teaches ([0095]): "The partition member 33D is provided with a gap SP capable of passing a walker. In this embodiment, a person 32 exists near the gap SP on the sidewalk 22."
and in the creation, creates the second travel route assuming the pedestrian will not enter the road when the pedestrian is detected and the entry-restricting state is detected.
Sakamoto teaches ([0094]): "FIG. 8A is a plan view showing a state in which an own vehicle 1 is traveling on a roadway 21 by automated driving as the fifth embodiment. In this embodiment, sidewalks 22 are partitioned from the roadway 21 by partition members 33D." Sakamoto further teaches ([0095]): "The partition member 33D is provided with a gap SP capable of passing a walker. In this embodiment, a person 32 exists near the gap SP on the sidewalk 22." Sakamoto even further teaches ([0096]): "Here, as shown in FIG. 8B, in a case in which the person 32 exists near the gap SP, there is a possibility that the person 32 has a desire to move across the roadway 21 through the gap SP. Hence, in a case in which it is confirmed that the person 32 exists within the range of a predetermined distance from the gap SP, the prediction ECU 17 predicts that the person 32 moves in the crossing direction through the gap SP and expands the warning region R to the side of the roadway 21, as indicated by an arrow E4." Sakamoto still further teaches ([0097]): " According to this embodiment, the arrangement form of the partition member 33D is considered, and crossing of the person 32 is predicted based on the presence/absence of the gap SP in the partition member 33D. For this reason, according to this embodiment, it is possible to perform behavior prediction of the person 32 at a high accuracy." Sakamoto yet further teaches ([0031]): "The own vehicle 1 detects the objects 3 on the roadway 21 and sidewalks 22 by the detection unit 16, and sets a traveling route so as to avoid the objects, thereby performing automated driving." Sakamoto finally teaches ([0040]): "Based on the prediction result from the prediction ECU 17, the traveling control ECU 12 sets a traveling route not to pass through the warning region R for each object 3, thereby preventing the own vehicle 1 from coming into contact with each object 3." The Examiner notes that the warning region R is still monitored for pedestrians using sidewalk 22, as shown in FIG. 3. Therefore, even when it is assumed that the pedestrian will not enter the road, the route is still created in a manner which prevents passing through the pedestrian's warning region R.
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Tanaka and Sakamoto to further incorporate the teachings of Sakamoto to provide that the processor, in the detection, further detects an entry-restricting state restricting entry of the pedestrian to the road from the surrounding data, and in the creation, creates the second travel route assuming the pedestrian will not enter the road when the pedestrian is detected and the entry-restricting state is detected. Tanaka and Sakamoto are each directed towards similar pursuits in the field of pedestrian behavior monitoring for vehicles. Accordingly, one of ordinary skill in the art would find it advantageous to incorporate the behavior prediction of Sakamoto, as doing so beneficially allows for behavior prediction of the pedestrian at a high accuracy based on proximity to (or away from) the pause-by object, as recognized by Sakamoto (see at least [0097]). Further, Sakamoto advantageously allows for collision avoidance based on the behavior prediction (see at least [0031]-[0033] and [0040]).
Regarding claim 4, Tanaka teaches a method for route planning having a route planner creating a travel route of a vehicle execute a process comprising:
detecting a pedestrian from surrounding data representing a situation of surroundings of the vehicle,
Tanaka teaches ([0059]): "A surrounding situation sensor 141 recognizes surrounding situation information of the vehicle M1… The surrounding situation information includes target information about a target recognized by the surrounding situation sensor 141. The target is exemplified by a surrounding vehicle, a pedestrian, a roadside structure, an obstacle, a white line, a signal, and the like."
identifying a position of a pause-by object in the surroundings of the vehicle prompting the pedestrian to pause,
Tanaka teaches ([0051]): "The intervention suppression area information 134 is information in which a geographic region (hereinafter referred to as an "intervention suppression area") in which intervention of preventative safety control is to be suppressed is associated with map information (location information). Typically, the intervention suppression area corresponds to a specific area in which substantial safety is expected, such as around a stop area or a boarding and alighting area for a passenger transport vehicle..." Tanaka further teaches ([0054]): "FIG. 5 shows an example of an operation timing of the preventive safety control when the vehicle M1, as a commercial bus, approaches and stops at a bus area. For example, as shown in FIG. 5, in the case where the surrounding of the bus stop area is set as the intervention suppression area..." FIG. 5, included above, depicts the identification of the pause-by object in the surrounding of the vehicle prompting the pedestrian to pause.
creating a travel route over which the vehicle will travel when the pedestrian is detected,
Tanaka teaches ([0073]): "For example, the first controller 12 generates a target trajectory for stopping the vehicle M1 at a stop area. More specifically, the first controller 12 recognizes a stop area as a destination and a person or a structure around the stop area based on the map information 132, the vehicle position information, and the surrounding situation information. Then, the first controller 12 generates a target trajectory for stopping at the stop area while avoiding the surrounding people and structures, based on these information."
However, Tanaka does not outright teach assuming the pedestrian will enter a road on which the vehicle will travel when the identified position of the pause-by object is not in a vicinity of the pedestrian, and assuming the pedestrian will not enter the road when the identified position of the pause-by object is in the vicinity of the pedestrian, the vicinity being within a predetermined distance threshold relative to the identified position of the pause-by object and the pedestrian, and performing autonomous driving along the travel route in response to determining that the pedestrian is detected and based on the identified position of the pause-by object being in the vicinity of the pedestrian. Sakamoto teaches a pedestrian behavior prediction apparatus and method, comprising:
assuming the pedestrian will enter a road on which the vehicle will travel when the identified position of the pause-by object is not in a vicinity of the pedestrian,
Sakamoto teaches ([0093]): "In the above-described first to fourth embodiments, when it is determined that the person 32 visually recognizes a predetermined object, crossing of the person 32 is predicted. However, if an object that interrupts crossing does not exist, crossing may be started regardless of the presence/absence of visual recognition of the predetermined object." Sakamoto further teaches ([0094]): "FIG. 8A is a plan view showing a state in which an own vehicle 1 is traveling on a roadway 21 by automated driving as the fifth embodiment. In this embodiment, sidewalks 22 are partitioned from the roadway 21 by partition members 33D." Sakamoto even further teaches ([0095]): "The partition member 33D is provided with a gap SP capable of passing a walker. In this embodiment, a person 32 exists near the gap SP on the sidewalk 22." Sakamoto still further teaches ([0096]): "Here, as shown in FIG. 8B, in a case in which the person 32 exists near the gap SP, there is a possibility that the person 32 has a desire to move across the roadway 21 through the gap SP. Hence, in a case in which it is confirmed that the person 32 exists within the range of a predetermined distance from the gap SP, the prediction ECU 17 predicts that the person 32 moves in the crossing direction through the gap SP and expands the warning region R to the side of the roadway 21, as indicated by an arrow E4." The Examiner has interpreted the person 32 existing within the predetermined distance of the gap SP as amounting to the pedestrian not being in a vicinity of the pause-by object (i.e., the partition member).
and assuming the pedestrian will not enter the road when the identified position of the pause-by object is in the vicinity of the pedestrian,
Sakamoto teaches ([0094]): "FIG. 8A is a plan view showing a state in which an own vehicle 1 is traveling on a roadway 21 by automated driving as the fifth embodiment. In this embodiment, sidewalks 22 are partitioned from the roadway 21 by partition members 33D." Sakamoto further teaches ([0095]): "The partition member 33D is provided with a gap SP capable of passing a walker. In this embodiment, a person 32 exists near the gap SP on the sidewalk 22." Sakamoto even further teaches ([0096]): "Here, as shown in FIG. 8B, in a case in which the person 32 exists near the gap SP, there is a possibility that the person 32 has a desire to move across the roadway 21 through the gap SP. Hence, in a case in which it is confirmed that the person 32 exists within the range of a predetermined distance from the gap SP, the prediction ECU 17 predicts that the person 32 moves in the crossing direction through the gap SP and expands the warning region R to the side of the roadway 21, as indicated by an arrow E4." Sakamoto still further teaches ([0097]): " According to this embodiment, the arrangement form of the partition member 33D is considered, and crossing of the person 32 is predicted based on the presence/absence of the gap SP in the partition member 33D. For this reason, according to this embodiment, it is possible to perform behavior prediction of the person 32 at a high accuracy." Therefore, when the pedestrian is in the vicinity of the pause-by object (i.e., the pedestrian is near the partition member and a gap is not present), the person 32 is not predicted to cross.
the vicinity being within a predetermined distance threshold relative to the identified position of the pause-by object and the pedestrian,
Sakamoto teaches ([0096]): "Here, as shown in FIG. 8B, in a case in which the person 32 exists near the gap SP, there is a possibility that the person 32 has a desire to move across the roadway 21 through the gap SP. Hence, in a case in which it is confirmed that the person 32 exists within the range of a predetermined distance from the gap SP, the prediction ECU 17 predicts that the person 32 moves in the crossing direction through the gap SP and expands the warning region R to the side of the roadway 21, as indicated by an arrow E4."
performing autonomous driving along the travel route in response to determining that the pedestrian is detected and based on the identified position of the pause-by object being in the vicinity of the pedestrian,
Sakamoto teaches ([0031]): "The own vehicle 1 detects the objects 3 on the roadway 21 and sidewalks 22 by the detection unit 16, and sets a traveling route so as to avoid the objects, thereby performing automated driving. " Sakamoto further teaches ([0033]): "As shown in FIG. 3, if the plurality of objects 3 are confirmed from the detection result (peripheral information of the vehicle 1) of the detection unit 16, the prediction ECU 17 sets a warning region R for each object 3. The warning region R is a region used to avoid contact of the own vehicle 1, that is, a region recommended not to overlap the own vehicle 1." Sakamoto even further teaches ([0040]): "Based on the prediction result from the prediction ECU 17, the traveling control ECU 12 sets a traveling route not to pass through the warning region R for each object 3, thereby preventing the own vehicle 1 from coming into contact with each object 3." Sakamoto still further teaches ([0096]): "Here, as shown in FIG. 8B, in a case in which the person 32 exists near the gap SP, there is a possibility that the person 32 has a desire to move across the roadway 21 through the gap SP. Hence, in a case in which it is confirmed that the person 32 exists within the range of a predetermined distance from the gap SP, the prediction ECU 17 predicts that the person 32 moves in the crossing direction through the gap SP and expands the warning region R to the side of the roadway 21, as indicated by an arrow E4."
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Tanaka to incorporate the teachings of Sakamoto to provide assuming the pedestrian will enter a road on which the vehicle will travel when the identified position of the pause-by object is not in a vicinity of the pedestrian, and assuming the pedestrian will not enter the road when the identified position of the pause-by object is in the vicinity of the pedestrian, the vicinity being within a predetermined distance threshold relative to the identified position of the pause-by object and the pedestrian, and performing autonomous driving along the travel route in response to determining that the pedestrian is detected and based on the identified position of the pause-by object being in the vicinity of the pedestrian. Tanaka and Sakamoto are each directed towards similar pursuits in the field of pedestrian behavior monitoring for vehicles. Accordingly, one of ordinary skill in the art would find it advantageous to incorporate the behavior prediction of Sakamoto, as doing so beneficially allows for behavior prediction of the pedestrian at a high accuracy based on proximity to (or away from) the pause-by object, as recognized by Sakamoto (see at least [0097]). Further, Sakamoto advantageously allows for collision avoidance based on the behavior prediction (see at least [0031]-[0033] and [0040]).
However, neither Tanaka nor Sakamoto teach or suggest setting one or more points on a center of a pair of lane lines, wherein a first travel route is created, as the travel route, passing through a first center point between the pedestrian and one of the pair of lane lines when the pedestrian will enter road, and wherein a second travel route is created passing through a second center point between another of the pair of lane lines when the pedestrian will not enter the road. Toda teaches a vehicle control apparatus and method, comprising:
and setting one or more points on a center of a pair of lane lines,
Toda teaches ([0047]): "The second control unit 160 includes, for example, an acquisition unit 162, a speed control unit 164, and a steering control unit 166. The acquisition unit 162 acquires information on the target trajectory (trajectory points) generated by the action plan generation unit 140 and stores it in a memory (not