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 .
Continued Examination Under 37 CFR 1.114
Receipt is acknowledged of a request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e) and a submission, filed on 05/05/2026.
Response to Amendment
The amendment filed on 05/05/2026 is being entered. Claims 1-21 are pending. Claims 1, 11, 12, 17 and 19 are amended. The amendment overcomes the previous 35 U.S.C. 103 rejections. However, after further consideration and search, claims 1-21 are rejected under 35 U.S.C. 103.
Claim Rejections - 35 USC § 103
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.
Claims 1, 3, 10, 12-14, 16, 18, 19, and 21 are rejected under 35 U.S.C. 103 as being unpatentable over Ravichandran et al. (U.S. Publication No. 2018/0281794 A1) hereinafter Ravichandran in view of Jung et al. (U.S. Patent No. 12,246,734 A1) hereinafter Jung in view of Iagnemma et al. (U.S. Patent No. 10,473,470 B2) hereinafter Iagnemma.
Regarding claim 1, Ravichandran discloses a computer-implemented method [see Paragraph 0050], comprising:
(a) obtaining a pull-over command indicating an autonomous vehicle is to pull-over to a side of a travel way [see Paragraphs 0091, 0094, and 0100 - discusses that a monitoring system of an autonomous vehicle (AV) detects a fault or failure in one or more components in the AV or an AV system and a stop request (pull-over command) is initiated]
(b) in response to the pull-over command, obtaining a sampled representation of map data see Paragraph 0101 - discusses that when the stop request is initiated then the AV system evaluates the map data to identify a target stopping place for the AV, see Paragraph 0135 - discusses that multiple stopping places are considered];
(c) determining, see Paragraph 0157 - discusses determining a plurality of stopping areas 802 and constructing a proximity region that removes some of the stopping areas 802 and leaving candidate stopping areas 903 that include stopping places using the map data along a route of the vehicle];
(d) determining a ranking of the one or more candidate pull-over locations [see Paragraphs 0158 and 0161 – discusses determining available stopping places in the stopping areas] based on
(i) a feasibility of the autonomous vehicle completing a stop at each respective candidate pull-over location [see Paragraph 0158 - discusses that individual stopping places are determined leaving only feasible stopping places (same direction as travel of the vehicle) 1011 to 1015 - stopping places having the same direction of travel are ranked higher than stopping places not having the same direction of travel]
(ii) a quality of each respective candidate pull-over location [see Paragraph 0161 - discusses determining a quality metric for each stopping place and using a quality threshold to further remove stopping places (including some of the feasible stopping places 1014, 1015) and to form a goal region - the stopping places 1011 to 1013 have a higher quality metric than 1014 to 1015 and are therefore ranked higher – these higher ranked stopping places are the acceptable stopping places, see Paragraph 0167 – discusses determining available stopping places from the acceptable stopping places];
(e) based on the ranking of the one or more candidate pull-over locations, determining a selected pull-over location for the autonomous vehicle [see Paragraphs 0177, 0179, and 0199 - discusses the AV system selecting an available stopping place in the goal region]; and
(f) controlling a motion of the autonomous vehicle based on the selected pull-over location [see Paragraphs 0179 and 0199 - discusses the AV system executes a trajectory plan to the available stopping place in the goal region].
Jung discloses a pull-over command indicating a target time for the autonomous vehicle to pull-over [see Column 14 lines 45-51 – discusses receiving a fault indication and mapping information in the fault indication to a corresponding constraint that is output to a vehicle system, see Column 14 lines 64-67 and see Column 15 lines 1-25 – discusses constraint outputs include contingent trajectories that include a second contingent that corresponds to an amount of time that the vehicle has until it needs to be pulled over, a third contingent that is a second pull over time that is less than the second contingent pull over time], the target time being based on the severity of a condition associated with the pull-over [see Column 23 lines 24-35 – discusses that when there is a fault of a sensor and the vehicle is travelling in an adverse condition (weather), then the constraint that is applied is to pull over within a predetermined time].
Jung suggests that applying constraints (pull over time) when there is a fault indication allows the vehicle to operate safely and efficiently [see Column 6 lines 4-15]. Jung further suggests that weather restricts traversal of a vehicle through an environment [see Column 15 lines 26-34].
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention, with a reasonable expectation of success, to modify the pull-over command and ranking of the pull-over locations as taught by Ravichandran to include a target time for the autonomous vehicle to pull-over based on the severity of a condition associated with the pull-over as taught by Jung in order to allow the vehicle to operate safely and efficiently during an adverse condition (weather) [Jung, see Column 6 lines 4-15 and see Column 15 lines 26-34].
Iagnemma discloses obtaining a sampled representation of map data comprising a plurality of encoded descriptors corresponding to a plurality of pull- over locations for the autonomous vehicle [see Column 6 lines 37-43 – discusses annotated map data, see Column 9 lines 16-52 – discusses that the annotated map data includes data about areas that contain stopping places, see Column 10 lines 6-125 – discusses that the stopping places are based upon the annotated map data, includes all types of stopping places (acceptable and unacceptable)]; and
(c) determining, from among the plurality of encoded descriptors, one or more candidate pull-over locations for the autonomous vehicle by querying the sampled representation using one or more segments identifiers corresponding to one or more segments of a route of the autonomous vehicle [see Column 10 lines 47-67, Column 11, and Column 12 lines 1017 – discusses that a goal region is determined where stopping is allowed (candidate pull-over locations) by using the annotated map data, and see Figure 7 below – depicts segments with identifiers that include candidate stopping locations along a route (see Column 4 lines 10-15)];
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Figure 7 of Iagnemma
Iagnemma suggests that annotated map data includes legal stopping places, illegal stopping places, restrictions on how long a vehicle can stop, restrictions on what type of vehicles can stop there, restrictions on what activities stopped vehicles can engage in (e.g., loading zones) and any other relevant information when determining an acceptable stopping place [see Column 9 lines 16-47].
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention, with a reasonable expectation of success, to modify the method as taught by Ravichandran to include a sampled representation of map data comprising a plurality of encoded descriptors corresponding to a plurality of pull- over locations for the autonomous vehicle and to determine one or more candidate pull-over locations for the autonomous vehicle by querying the sampled representation using one or more segments identifiers corresponding to one or more segments of a route of the autonomous vehicle as taught by Iagnemma in order to differentiate legal, illegal, and restricted stopping places from one another in order to find an acceptable stopping location [Iagnemma, see Column 9 lines 16-47].
Regarding claim 3, Ravichandran, Jung, and Iagnemma disclose the invention with respect to claim 1. Ravichandran further discloses wherein (f) comprises: generating a trajectory for the autonomous vehicle to travel to a stopped position within a goal range associated with the selected pull-over location [see Paragraphs 0177 and 0199 - discusses selecting the available stopping place and identifying a trajectory to the available stopping place in a goal region where the vehicle travels to a stopped position at the stopped place]; and
controlling the motion of the autonomous vehicle based on the trajectory such that the autonomous vehicle reaches the stopped position within the goal range [see Paragraphs 0179 and 0199 - discusses the AV executing the trajectory in the goal region to the selected available stopping place where the vehicle will be in a stopped position at the stopped place].
Regarding claim 10, Ravichandran, Jung, and Iagnemma disclose the invention with respect to claim 1. Ravichandran further discloses wherein the pull-over command is see Paragraphs 0091, 0094, and 0100 - discusses that a monitoring system (onboard system) of an autonomous vehicle (AV) detects a fault or failure], and wherein the pull-over command is generated in response to at least one of: see Paragraphs 0091, 0094, and 0100 - the fault or failure being in one or more components in the AV or AV system (hardware)]
Regarding claim 12, Ravichandran discloses an autonomous vehicle control system [see Paragraph 0079] comprising: one or more processors [see Paragraph 0087 – discusses a processor]; and one or more tangible non-transitory computer-readable media storing instruction that are executable by the one or more processors to perform operations [see Paragraph 0080 – discusses a memory storing machine instructions, and see Paragraph 0087 – discusses a processor executing algorithms], the operations comprising:
(a) obtaining a pull-over command indicating an autonomous vehicle is to pull-over to a side of a travel way [see Paragraphs 0091, 0094, and 0100 - discusses that a monitoring system of an autonomous vehicle (AV) detects a fault or failure in one or more components in the AV or an AV system and a stop request (pull-over command) is initiated]
(b) in response to the pull-over command, obtaining a sampled representation of map data see Paragraph 0101 - discusses that when the stop request is initiated then the AV system evaluates the map data to identify a target stopping place for the AV, see Paragraph 0135 - discusses that multiple stopping places are considered];
(c) determining, see Paragraph 0157 - discusses determining a plurality of stopping areas 802 and constructing a proximity region that removes some of the stopping areas 802 and leaving candidate stopping areas 903 that include stopping places using the map data along a route of the vehicle];
(d) determining a ranking of the one or more candidate pull-over locations [see Paragraphs 0158 and 0161 – discusses determining available stopping places in the stopping areas] based on
(i) a feasibility of the autonomous vehicle completing a stop at each respective candidate pull-over location see Paragraph 0158 - discusses that individual stopping places are determined leaving only feasible stopping places (same direction as travel of the vehicle) 1011 to 1015 - stopping places having the same direction of travel are ranked higher than stopping places not having the same direction of travel],
(ii) a quality of each respective candidate pull-over location; [see Paragraph 0161 - discusses determining a quality metric for each stopping place and using a quality threshold to further remove stopping places (including some of the feasible stopping places 1014, 1015) and to form a goal region - the stopping places 1011 to 1013 have a higher quality metric than 1014 to 1015 and are therefore ranked higher – these higher ranked stopping places are the acceptable stopping places, see Paragraph 0167 – discusses determining available stopping places from the acceptable stopping places], and
(e) based on the ranking of the one or more candidate pull-over locations, determining a selected pull-over location for the autonomous vehicle [see Paragraphs 0177, 0179, and 0199 - discusses the AV system selecting an available stopping place in the goal region]; and
(f) controlling a motion of the autonomous vehicle based on the selected pull-over location [see Paragraphs 0179 and 0199 - discusses the AV system executes a trajectory plan to the available stopping place in the goal region].
Jung discloses a pull-over command indicating a target time for the autonomous vehicle to pull-over [see Column 14 lines 45-51 – discusses receiving a fault indication and mapping information in the fault indication to a corresponding constraint that is output to a vehicle system, see Column 14 lines 64-67 and see Column 15 lines 1-25 – discusses constraint outputs include contingent trajectories that include a second contingent that corresponds to an amount of time that the vehicle has until it needs to be pulled over, a third contingent that is a second pull over time that is less than the second contingent pull over time], the target time being based on the severity of a condition associated with the pull-over [see Column 23 lines 24-35 – discusses that when there is a fault of a sensor and the vehicle is travelling in an adverse condition (weather), then the constraint that is applied is to pull over within a predetermined time].
Jung suggests that applying constraints (pull over time) when there is a fault indication allows the vehicle to operate safely and efficiently [see Column 6 lines 4-15]. Jung further suggests that weather restricts traversal of a vehicle through an environment [see Column 15 lines 26-34].
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention, with a reasonable expectation of success, to modify the pull-over command and ranking of the pull-over locations as taught by Ravichandran to include a target time for the autonomous vehicle to pull-over based on the severity of a condition associated with the pull-over as taught by Jung in order to allow the vehicle to operate safely and efficiently during an adverse condition (weather) [Jung, see Column 6 lines 4-15 and see Column 15 lines 26-34].
Iagnemma discloses obtaining a sampled representation of map data comprising a plurality of encoded descriptors corresponding to a plurality of pull- over locations for the autonomous vehicle [see Column 6 lines 37-43 – discusses annotated map data, see Column 9 lines 16-52 – discusses that the annotated map data includes data about areas that contain stopping places, see Column 10 lines 6-125 – discusses that the stopping places are based upon the annotated map data, includes all types of stopping places (acceptable and unacceptable)]; and
(c) determining, from among the plurality of encoded descriptors, one or more candidate pull-over locations for the autonomous vehicle by querying the sampled representation using one or more segments identifiers corresponding to one or more segments of a route of the autonomous vehicle [see Column 10 lines 47-67, Column 11, and Column 12 lines 1017 – discusses that a goal region is determined where stopping is allowed (candidate pull-over locations) by using the annotated map data, and see Figure 7 below – depicts segments with identifiers that include candidate stopping locations along a route (see Column 4 lines 10-15) ];
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Figure 7 of Iagnemma
Iagnemma suggests that annotated map data includes legal stopping places, illegal stopping places, restrictions on how long a vehicle can stop, restrictions on what type of vehicles can stop there, restrictions on what activities stopped vehicles can engage in (e.g., loading zones) and any other relevant information when determining an acceptable stopping place [see Column 9 lines 16-47].
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention, with a reasonable expectation of success, to modify the processor as taught by Ravichandran to obtain a sampled representation of map data comprising a plurality of encoded descriptors corresponding to a plurality of pull- over locations for the autonomous vehicle and to determine one or more candidate pull-over locations for the autonomous vehicle by querying the sampled representation using one or more segments identifiers corresponding to one or more segments of a route of the autonomous vehicle as taught by Iagnemma in order to differentiate legal, illegal, and restricted stopping places from one another in order to find an acceptable stopping location [Iagnemma, see Column 9 lines 16-47].
Iagnemma further discloses determining a ranking of the one or more candidate pull-over locations based on an impact on one or more motion dynamics of the autonomous vehicle associated with each respective candidate pull-over location [see Column 10 lines 47-67, Column 11– discusses that that candidate pull-over locations are determined whether or not a vehicle can stop there, stopping is a motion dynamic].
Iagnemma suggests determining an acceptable, feasible, and desirable stopping place [see Column 9 lines 11-15].
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention, with a reasonable expectation of success, to modify the processor as taught by Ravichandran to determine a ranking of the one or more candidate pull-over locations based on an impact on one or more motion dynamics of the autonomous vehicle associated with each respective candidate pull-over location as taught by Iagnemma in order to determine an acceptable, feasible, and desirable stopping place [Iagnemma, see Column 9 lines 11-15].
Regarding claim 13, Ravichandran, Jung, and Iagnemma disclose the invention with respect to claim 12. Ravichandran further discloses wherein the selected pull-over location comprises a goal range [see Paragraph 0177 - discusses a goal region], and wherein (f) comprises:
generating a trajectory for the autonomous vehicle to travel to a stopped position within the goal range associated with the selected pull-over location [see Paragraphs 0177 and 0199 - discusses selecting the available stopping place and identifying a trajectory to the available stopping place in a goal region where the vehicle travels to a stopped position at the stopped place]; and
controlling the motion of the autonomous vehicle based on the trajectory such that the autonomous vehicle reaches the stopped position within the goal range [see Paragraphs 0179 and 0199 - discusses the AV executing the trajectory in the goal region to the selected available stopping place where the vehicle will be in a stopped position at the stopped place].
Regarding claim 14, Ravichandran, Jung, and Iagnemma disclose the invention with respect to claim 13. Ravichandran further discloses wherein the goal range defines an area, on a shoulder of the travel way, in which the autonomous vehicle is to stop [see Paragraph 0119 - discusses a stopping place includes a road shoulder, and see Figure 9 below – depicts stopping areas (that include stopping places) on a road shoulder (903), and see Figure 10 below – depicts the stopping places 1011-1013 in a goal region that are determined in the shaded areas].
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Figure 9 of Ravichandran Figure 10 of Ravichandran
Regarding claim 16, Ravichandran, Jung, and Iagnemma disclose the invention with respect to claim 12. Ravichandran further discloses wherein the plurality of pull-over locations are outside of a boundary defining one or more lanes of travel on the travel way [see Paragraphs 0119 and 0158 - discusses a parking lot/parking spots that are encoded in map data, see Paragraph 0017 – discusses using a parking lot/space databases ].
Regarding claim 18, Ravichandran, Jung, and Iagnemma Jung disclose the invention with respect to claim 12. Ravichandran further discloses wherein the operations further comprise:
generating a pull-over route for the autonomous vehicle to travel to the selected pull-over location [see Paragraphs 0177 and 0199 - discusses selecting the available stopping place and identifying a trajectory to the available stopping place in a goal region where the vehicle travels to a stopped position at the stopped place], and
wherein (f) comprises controlling the motion of the autonomous vehicle in accordance with the pull-over route [see Paragraphs 0179 and 0199 - discusses the AV executing the trajectory in the goal region to the selected available stopping place where the vehicle will be in a stopped position at the stopped place].
Regarding claim 19, Ravichandran discloses an autonomous vehicle [see Paragraph 0078 – autonomous vehicle] comprising:
one or more processors [see Paragraph 0087 – discusses a processor]; and
one or more tangible non-transitory computer-readable media storing instructions that are executable by the one or more processors to perform operations [see Paragraph 0080 – discusses a memory storing machine instructions, and see Paragraph 0087 – discusses a processor executing algorithms], the operations comprising:
(a) obtaining a pull-over command indicating the autonomous vehicle is to pull-over to a side of a travel way [see Paragraphs 0091, 0094, and 0100 - discusses that a monitoring system of an autonomous vehicle (AV) detects a fault or failure in one or more components in the AV or an AV system and a stop request (pull-over command) is initiated]
(b) in response to the pull-over command, obtaining a sampled representation of map data see Paragraph 0101 - discusses that when the stop request is initiated then the AV system evaluates the map data to identify a target stopping place for the AV, see Paragraph 0135 - discusses that multiple stopping places are considered];
(c) determining, see Paragraph 0157 - discusses determining a plurality of stopping areas 802 and constructing a proximity region that removes some of the stopping areas 802 and leaving candidate stopping areas 903 that include stopping places using the map data along a route of the vehicle];
(d) determining a ranking of the one or more candidate pull-over locations [see Paragraphs 0158 and 0161 – discusses determining available stopping places in the stopping areas] based on
(i) a feasibility of the autonomous vehicle completing a stop at each respective candidate pull-over location see Paragraph 0158 - discusses that individual stopping places are determined leaving only feasible stopping places (same direction as travel of the vehicle) 1011 to 1015 - stopping places having the same direction of travel are ranked higher than stopping places not having the same direction of travel],
(ii) a quality of each respective candidate pull-over location; [see Paragraph 0161 - discusses determining a quality metric for each stopping place and using a quality threshold to further remove stopping places (including some of the feasible stopping places 1014, 1015) and to form a goal region - the stopping places 1011 to 1013 have a higher quality metric than 1014 to 1015 and are therefore ranked higher – these higher ranked stopping places are the acceptable stopping places, see Paragraph 0167 – discusses determining available stopping places from the acceptable stopping places], and
(e) based on the ranking of the one or more candidate pull-over locations, determining a selected pull-over location for the autonomous vehicle [see Paragraphs 0177, 0179, and 0199 - discusses the AV system selecting an available stopping place in the goal region]; and
(f) controlling a motion of the autonomous vehicle based on the selected pull-over location [see Paragraphs 0179 and 0199 - discusses the AV system executes a trajectory plan to the available stopping place in the goal region].
Jung discloses a pull-over command indicating a target time for the autonomous vehicle to pull-over [see Column 14 lines 45-51 – discusses receiving a fault indication and mapping information in the fault indication to a corresponding constraint that is output to a vehicle system, see Column 14 lines 64-67 and see Column 15 lines 1-25 – discusses constraint outputs include contingent trajectories that include a second contingent that corresponds to an amount of time that the vehicle has until it needs to be pulled over, a third contingent that is a second pull over time that is less than the second contingent pull over time], the target time being based on the severity of a condition associated with the pull-over [see Column 23 lines 24-35 – discusses that when there is a fault of a sensor and the vehicle is travelling in an adverse condition (weather), then the constraint that is applied is to pull over within a predetermined time].
Jung suggests that applying constraints (pull over time) when there is a fault indication allows the vehicle to operate safely and efficiently [see Column 6 lines 4-15]. Jung further suggests that weather restricts traversal of a vehicle through an environment [see Column 15 lines 26-34].
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention, with a reasonable expectation of success, to modify the pull-over command and ranking of the pull-over locations as taught by Ravichandran to include a target time for the autonomous vehicle to pull-over based on the severity of a condition associated with the pull-over as taught by Jung in order to allow the vehicle to operate safely and efficiently during an adverse condition (weather) [Jung, see Column 6 lines 4-15 and see Column 15 lines 26-34].
Iagnemma discloses obtaining a sampled representation of map data comprising a plurality of encoded descriptors corresponding to a plurality of pull- over locations for the autonomous vehicle [see Column 6 lines 37-43 – discusses annotated map data, see Column 9 lines 16-52 – discusses that the annotated map data includes data about areas that contain stopping places, see Column 10 lines 6-125 – discusses that the stopping places are based upon the annotated map data, includes all types of stopping places (acceptable and unacceptable)]; and
(c) determining, from among the plurality of encoded descriptors, one or more candidate pull-over locations for the autonomous vehicle by querying the sampled representation using one or more segments identifiers corresponding to one or more segments of a route of the autonomous vehicle [see Column 10 lines 47-67, Column 11, and Column 12 lines 1017 – discusses that a goal region is determined where stopping is allowed (candidate pull-over locations) by using the annotated map data, and see Figure 7 below – depicts segments with identifiers that include candidate stopping locations along a route (see Column 4 lines 10-15)];
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Figure 7 of Iagnemma
Iagnemma suggests that annotated map data includes legal stopping places, illegal stopping places, restrictions on how long a vehicle can stop, restrictions on what type of vehicles can stop there, restrictions on what activities stopped vehicles can engage in (e.g., loading zones) and any other relevant information when determining an acceptable stopping place [see Column 9 lines 16-47].
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention, with a reasonable expectation of success, to modify the processor as taught by Ravichandran to obtain a sampled representation of map data comprising a plurality of encoded descriptors corresponding to a plurality of pull- over locations for the autonomous vehicle and to determine one or more candidate pull-over locations for the autonomous vehicle by querying the sampled representation using one or more segments identifiers corresponding to one or more segments of a route of the autonomous vehicle as taught by Iagnemma in order to differentiate legal, illegal, and restricted stopping places from one another in order to find an acceptable stopping location [Iagnemma, see Column 9 lines 16-47].
Iagnemma further discloses determining a ranking of the one or more candidate pull-over locations based on an impact on one or more motion dynamics of the autonomous vehicle associated with each respective candidate pull-over location [see Column 10 lines 47-67, Column 11– discusses that that candidate pull-over locations are determined whether or not a vehicle can stop there, stopping is a motion dynamic].
Iagnemma suggests determining an acceptable, feasible, and desirable stopping place [see Column 9 lines 11-15].
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention, with a reasonable expectation of success, to modify the processor as taught by Ravichandran to determine a ranking of the one or more candidate pull-over locations based on an impact on one or more motion dynamics of the autonomous vehicle associated with each respective candidate pull-over location as taught by Iagnemma in order to determine an acceptable, feasible, and desirable stopping place [Iagnemma, see Column 9 lines 11-15].
Regarding claim 21, Ravichandran, Jung, and Iagnemma disclose the invention with respect to claim 1. Jung further discloses wherein the condition associated with the pull-over comprises inclement weather [see Column 23 lines 24-35 – discusses that when there is a fault of a sensor and the vehicle is travelling in an adverse condition (weather), then the constraint that is applied is to pull over within a predetermined time].
Claims 1, 4-7, 11, 12, 15, and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Lashkari et al. (U.S. Publication No. 2023/0398985 A1) hereinafter Lashkari in view of Soltanian et al. (U.S. Publication No. 2020/0031337 A1) hereinafter Soltanian in view of Iagnemma et al. (U.S. Patent No. 10,473,470 B2) hereinafter Iagnemma.
Regarding claim 1, Lashkari discloses a computer-implemented method [see Paragraphs 0052 and 0061 – discusses a controller performs process 200 which is further specified in processes 300-600], comprising:
(a) obtaining a pull-over command indicating an autonomous vehicle is to pull-over to a side of a travel way [see Paragraph 0063 - discusses that an emergency vehicle is detected by sensors of a vehicle in step 204]
(b) in response to the pull-over command, obtaining a sampled representation of map data see Paragraph 0066 - discusses step 206 using map information after detecting the emergency vehicle in step 204];
(c) determining, see Paragraphs 0064 and 0066 - further elaborates on step 206 (Figure 3) discusses performing an initial cell localization for a plurality of cells using the map data along a route for the vehicle at step 304, each cell representing different locations to which a vehicle may pull over (candidate pull-over locations), see Paragraph 0070 - discusses that the cell localization is finalized at step 312, where possible locations to which the vehicle may pull over (candidate pull-over locations)];
(d) determining a ranking of the one or more candidate pull-over locations [see Paragraphs 0080-0082 – further specifies step 208 (see Figure 4) where step 416 uses a feasibility and a quality to determine a probability for a candidate pull-over locations as a road rules probability, and 0113-0116 - discusses determining the probability score for each cell] based on
(i) a feasibility of the autonomous vehicle completing a stop at each respective candidate pull-over location see Paragraphs 0077 - further elaborates on step 208 and discusses determining a feasibility for each of the candidate pull-over locations to which the vehicle may pull over at step 412] and
(ii) a quality of each respective candidate pull-over location [see Paragraph 0077 - further elaborates on step 208 that the quality (parking on a hill, parking near a stop sign, parking near fire hydrants) of candidate pull-over locations is taken into account, and disfavoring candidate pull-over locations based on the quality (while inversely favoring others) at step 414];
(e) based on the ranking of the one or more candidate pull-over locations, determining a selected pull-over location for the autonomous vehicle [see Paragraphs 0118-0120 - discusses determining an optimal/desirable cell (candidate pull-over location) based on the probability for each of the cells]; and
(f) controlling a motion of the autonomous vehicle based on the selected pull-over location [see Paragraph 0123 - discusses controlling movement of the vehicle to the optimal cell (candidate pull-over location)].
Soltanian discloses a pull-over command indicating a target time for the autonomous vehicle to pull-over, the target time being based on the severity of a condition associated with a pull-over [see Paragraphs 0004 and 0036 – discusses calculating a time of arrival of the other vehicle based on distance and speed using sensors, the sensor data is then used to determine a collision point at an intersection in a road (severity of a condition), next a comparison of (1) the estimated time of collision between a vehicle and an emergency vehicle with (2) the amount of time required to pull the vehicle over and stop it along the side of the road (target time) is performed based on the determined collision point (severity of a condition)].
Soltanian suggests that by performing a comparison of (1) the estimated time of collision between a vehicle and an emergency vehicle with (2) the amount of time required to pull the vehicle over and stop it along the side of the road (target time), prevents collisions with emergency vehicles (at collision points)[see Paragraph 0026]. Soltanian further suggests that comparing using the target time allows for control of the vehicle in sufficient time to stop the vehicle before a collision [see Paragraph 0036].
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention, with a reasonable expectation of success, to modify the pull-over command and ranking of the pull-over locations as taught by Lashkari to include a target time for the autonomous vehicle to pull-over as taught by Soltanian in order to prevent a collision with an emergency vehicle at a collision point[Soltanian, see Paragraphs 0026 and 0036].
Iagnemma discloses obtaining a sampled representation of map data comprising a plurality of encoded descriptors corresponding to a plurality of pull- over locations for the autonomous vehicle [see Column 6 lines 37-43 – discusses annotated map data, see Column 9 lines 16-52 – discusses that the annotated map data includes data about areas that contain stopping places, see Column 10 lines 6-125 – discusses that the stopping places are based upon the annotated map data, includes all types of stopping places (acceptable and unacceptable)]; and
(c) determining, from among the plurality of encoded descriptors, one or more candidate pull-over locations for the autonomous vehicle by querying the sampled representation using one or more segments identifiers corresponding to one or more segments of a route of the autonomous vehicle [see Column 10 lines 47-67, Column 11, and Column 12 lines 1017 – discusses that a goal region is determined where stopping is allowed (candidate pull-over locations) by using the annotated map data, and see Figure 7 below – depicts segments with identifiers that include candidate stopping locations along a route (see Column 4 lines 10-15)];
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Figure 7 of Iagnemma
Iagnemma suggests that annotated map data includes legal stopping places, illegal stopping places, restrictions on how long a vehicle can stop, restrictions on what type of vehicles can stop there, restrictions on what activities stopped vehicles can engage in (e.g., loading zones) and any other relevant information when determining an acceptable stopping place [see Column 9 lines 16-47].
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention, with a reasonable expectation of success, to modify the method as taught by Lashkari to include a sampled representation of map data comprising a plurality of encoded descriptors corresponding to a plurality of pull- over locations for the autonomous vehicle and to determine one or more candidate pull-over locations for the autonomous vehicle by querying the sampled representation using one or more segments identifiers corresponding to one or more segments of a route of the autonomous vehicle as taught by Iagnemma in order to differentiate legal, illegal, and restricted stopping places from one another in order to find an acceptable stopping location [Iagnemma, see Column 9 lines 16-47].
Regarding claim 4, Lashkari, Soltanian, and Iagnemma disclose the invention with respect to claim 1. Lashkari further discloses wherein (d) comprises determining the ranking of the one or more candidate pull-over locations based on one or more motion parameters of the autonomous vehicle [see Paragraphs 0104-0105 - discusses in step 217 at step 610 in which an arrival time for host vehicle to reach the candidate pull-over location (cell) is determined based on the speed (velocity) of the host vehicle , see Paragraph 0108 - discusses determining the vehicle contact probability using the arrival time at the cell as determined at step 610, see Paragraphs 0116-0117 - discusses summing the vehicle contact probability with the road rules probability to determine the optimal cell (highest ranked)] and
Soltanian further discloses a target time for an autonomous vehicle to pull-over [see Paragraphs 0004 and 0036].
Soltanian suggests that comparing using the target time prevents a collision [see Paragraph 0036].
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention, with a reasonable expectation of success, to modify the determining the ranking as taught by Lashkari based on a target time for the autonomous vehicle to pull-over as taught by Soltanian in order to prevent a collision with an emergency vehicle at a collision point [Soltanian, see Paragraphs 0026 and 0036].
Regarding claim 5, Lashkari, Soltanian, and Iagnemma disclose the invention with respect to claim 4. Lashkari further discloses wherein the feasibility of the autonomous vehicle completing the stop at each respective pull-over location is indicative of a probability of the autonomous vehicle being able to travel to a stopped position at the pull-over location based on the one or more motion parameters [see Paragraph 0116-0117 – discusses a probability is determined after determining the feasibility in step 412, and the probability - see Paragraphs 0104-0105 - discusses in step 217 at step 610 in which an arrival time for host vehicle to reach the candidate pull-over location (cell) is determined based on the speed (velocity) of the host vehicle , see Paragraph 0108 - discusses determining the vehicle contact probability using the arrival time at the cell as determined at step 610, see Paragraphs 0116-0117 - discusses summing the vehicle contact probability with the road rules probability to determine the optimal cell (highest ranked)]
Soltanian further discloses a target time for an autonomous vehicle to pull-over [see Paragraphs 0004 and 0036].
Soltanian suggests that comparing using the target time prevents a collision [see Paragraph 0036].
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention, with a reasonable expectation of success, to modify the determining the ranking as taught by Lashkari based on a target time for the autonomous vehicle to pull-over as taught by Soltanian in order to prevent a collision with an emergency vehicle at a collision point [Soltanian, see Paragraphs 0026 and 0036].
Regarding claim 6, Lashkari, Soltanian, and Iagnemma disclose the invention with respect to claim 4. Lashkari further discloses wherein the one or more motion parameters are indicative of at least one of: (i) a speed of the autonomous vehicle, (ii) a heading of the autonomous vehicle [see Paragraph 0105 - discusses velocity of the autonomous vehicle, which is a speed and a direction (heading)]
Regarding claim 7, Lashkari, Soltanian, and Iagnemma disclose the invention with respect to claim 4. Lashkari further discloses wherein the target time for the autonomous vehicle to pull-over is provided by a remote computing system that is remote from the autonomous vehicle [see Paragraph 0053 - discusses that a control system and/or a controller of the vehicle is remote from the vehicle, see Paragraph 0055 - discusses that the controller (remote) performs the process 200, which includes processes 300-600].
Regarding claim 11, Lashkari, Soltanian, and Iagnemma disclose the invention with respect to claim 1. Lashkari further discloses (h) generating route data that is indicative of the route for the autonomous vehicle [see Paragraph 0123 - discusses 'processor 142 (of the controller) provides instructions to one or more of the braking system 106 of FIG. 1, the steering system 108 of FIG. 1, the drive system 110 of FIG. 1, and/or one or more other vehicle systems of the vehicle 100 of FIG. 1 that execute the processor 142's instructions to automatically move the vehicle 100 to the optimal pull over location (e.g., cell) via a route that is selected by the processor 142.'].
Regarding claim 12, Lashkari discloses an autonomous vehicle control system comprising: one or more processors [see Paragraph 0052 – discusses a processor 142]; and one or more tangible non-transitory computer-readable media storing instruction that are executable by the one or more processors to perform operations [see Paragraph 0060 – ‘on-transitory computer readable medium bearing the program and containing computer instructions stored therein for causing a computer processor (such as the processor 142) to perform and execute the program’], the operations comprising:
(a) obtaining a pull-over command indicating an autonomous vehicle is to pull-over to a side of a travel way [see Paragraph 0063 - discusses that an emergency vehicle is detected by sensors of a vehicle in step 204],
(b) in response to the pull-over command, obtaining a sampled representation of map data see Paragraph 0066 - discusses step 206 using map information after detecting the emergency vehicle in step 204];
(c) determining, see Paragraphs 0064 and 0066 - further elaborates on step 206 (Figure 3) discusses performing an initial cell localization for a plurality of cells using the map data along a route for the vehicle at step 304, each cell representing different locations to which a vehicle may pull over (candidate pull-over locations), see Paragraph 0070 - discusses that the cell localization is finalized at step 312, where possible locations to which the vehicle may pull over (candidate pull-over locations)];
(d) determining a ranking of the one or more candidate pull-over locations [see Paragraphs 0080-0082 – further specifies step 208 (see Figure 4) where step 416 uses a feasibility and a quality to determine a probability for a candidate pull-over locations as a road rules probability, and 0113-0116 - discusses determining the probability score for each cell] based on
(i) a feasibility of the autonomous vehicle completing a stop at each respective candidate pull-over location see Paragraphs 0077 - further elaborates on step 208 and discusses determining a feasibility for each of the candidate pull-over locations to which the vehicle may pull over at step 412],
(ii) a quality of each respective candidate pull-over location [see Paragraph 0077 - further elaborates on step 208 that the quality (parking on a hill, parking near a stop sign, parking near fire hydrants) of candidate pull-over locations is taken into account, and disfavoring candidate pull-over locations based on the quality (while inversely favoring others) at step 414], and
(e) based on the ranking of the one or more candidate pull-over locations, determining a selected pull-over location for the autonomous vehicle [see Paragraphs 0118-0120 - discusses determining an optimal/desirable cell (candidate pull-over location) based on the probability for each of the cells]; and
(f) controlling a motion of the autonomous vehicle based on the selected pull-over location [see Paragraph 0123 - discusses controlling movement of the vehicle to the optimal cell (candidate pull-over location)].
Soltanian discloses a pull-over command indicating a target time for the autonomous vehicle to pull-over, the target time being based on the severity of a condition associated with a pull-over [see Paragraphs 0004 and 0036 – discusses calculating a time of arrival of the other vehicle based on distance and speed using sensors, the sensor data is then used to determine a collision point at an intersection in a road (severity of a condition), next a comparison of (1) the estimated time of collision between a vehicle and an emergency vehicle with (2) the amount of time required to pull the vehicle over and stop it along the side of the road (target time) is performed based on the determined collision point (severity of a condition)].
Soltanian suggests that by performing a comparison of (1) the estimated time of collision between a vehicle and an emergency vehicle with (2) the amount of time required to pull the vehicle over and stop it along the side of the road (target time), prevents collisions with emergency vehicles (at collision points)[see Paragraph 0026]. Soltanian further suggests that comparing using the target time allows for control of the vehicle in sufficient time to stop the vehicle before a collision [see Paragraph 0036].
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention, with a reasonable expectation of success, to modify the pull-over command and ranking of the pull-over locations as taught by Lashkari to include a target time for the autonomous vehicle to pull-over as taught by Soltanian in order to prevent a collision with an emergency vehicle at a collision point[Soltanian, see Paragraphs 0026 and 0036].
Iagnemma discloses obtaining a sampled representation of map data comprising a plurality of encoded descriptors corresponding to a plurality of pull-over locations for the autonomous vehicle [see Column 6 lines 37-43 – discusses annotated map data, see Column 9 lines 16-52 – discusses that the annotated map data includes data about areas that contain stopping places, see Column 10 lines 6-125 – discusses that the stopping places are based upon the annotated map data, includes all types of stopping places (acceptable and unacceptable)]; and
(c) determining, from among the plurality of encoded descriptors, one or more candidate pull-over locations for the autonomous vehicle by querying the sampled representation using one or more segments identifiers corresponding to one or more segments of a route of the autonomous vehicle [see Column 10 lines 47-67, Column 11, and Column 12 lines 1017 – discusses that a goal region is determined where stopping is allowed (candidate pull-over locations) by using the annotated map data, and see Figure 7 below – depicts segments with identifiers that include candidate stopping locations along a route (see Column 4 lines 10-15)];
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Figure 7 of Iagnemma
Iagnemma suggests that annotated map data includes legal stopping places, illegal stopping places, restrictions on how long a vehicle can stop, restrictions on what type of vehicles can stop there, restrictions on what activities stopped vehicles can engage in (e.g., loading zones) and any other relevant information when determining an acceptable stopping place [see Column 9 lines 16-47].
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention, with a reasonable expectation of success, to modify the processor as taught by Lashkari to obtain a sampled representation of map data comprising a plurality of encoded descriptors corresponding to a plurality of pull- over locations for the autonomous vehicle and to determine one or more candidate pull-over locations for the autonomous vehicle by querying the sampled representation using one or more segments identifiers corresponding to one or more segments of a route of the autonomous vehicle as taught by Iagnemma in order to differentiate legal, illegal, and restricted stopping places from one another in order to find an acceptable stopping location [Iagnemma, see Column 9 lines 16-47].
Iagnemma further discloses determining a ranking of the one or more candidate pull-over locations based on an impact on one or more motion dynamics of the autonomous vehicle associated with each respective candidate pull-over location [see Column 10 lines 47-67, Column 11– discusses that that candidate pull-over locations are determined whether or not a vehicle can stop there, stopping is a motion dynamic].
Iagnemma suggests determining an acceptable, feasible, and desirable stopping place [see Column 9 lines 11-15].
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention, with a reasonable expectation of success, to modify the processor as taught by Lashkari to determine a ranking of the one or more candidate pull-over locations based on an impact on one or more motion dynamics of the autonomous vehicle associated with each respective candidate pull-over location as taught by Iagnemma in order to determine an acceptable, feasible, and desirable stopping place [Iagnemma, see Column 9 lines 11-15].
Regarding claim 15, Lashkari, Soltanian, and Iagnemma disclose the invention with respect to claim 12. Lashkari further discloses wherein (d) comprises determining a rank of a respective candidate pull-over location based on one or more motion parameters of the autonomous vehicle and a respective distance for the autonomous vehicle to reach the respective candidate pull-over location [see Paragraphs 0104-0105 - discusses in step 217 at step 610 in which a time for host vehicle to reach the candidate pull-over location (cell) is determined based on the speed (velocity) of the host vehicle and used in the vehicle contact probability, see Paragraph 0093 - discusses in step 212 determining the vehicle dynamics probability using the host vehicles minimum feasible distance to reach a cell, and see Paragraphs 0116-0117 - discusses summing the vehicle contact probability, the road rules probability, and the vehicle dynamics probability to determine the optimal cell (highest ranked)].
Regarding claim 17, Lashkari, Soltanian, and Iagnemma disclose the invention with respect to claim 12. Lashkari further discloses wherein (d) comprises performing a cost analysis of the one or more candidate pull-over locations [see Paragraphs 0080-0082 - discusses step 416 which use the feasibility and quality criteria to determine a probability for a candidate pull-over locations as a road rules probability, and see Paragraphs 0116-0117 - discusses summing the vehicle contact probability, the road rules probability, and the vehicle dynamics probability to determine the optimal cell (highest ranked)], wherein a cost for a respective candidate pull-over location is based on the feasibility of the autonomous vehicle completing the stop at the respective candidate pull-over location [see Paragraphs 0077 - further elaborates on step 208 and discusses determining a feasibility for each of the candidate pull-over locations to which the vehicle may pull over at step 412], the quality of the respective candidate pull-over location [see Paragraph 0077 - discusses at step 414 that the quality (parking on a hill, parking near a stop sign, parking near fire hydrants) of candidate pull-over locations is taken into account, and disfavoring candidate pull-over locations based on the quality (while inversely favoring others)], and a timing [see Paragraph 0108 - discusses determining a vehicle contact probability using the arrival time at the cell as determined at step 610] or distance constraint for the autonomous vehicle to pull-over [see Paragraph 0093 - discusses in step 212 determining a vehicle dynamics probability using the host vehicles minimum feasible distance to reach a cell].
Claim 2 is rejected under 35 U.S.C. 103 as being unpatentable over Lashkari in view of Soltanian in view of Iagnemma in view of Lee at al. (U.S. Publication No. 2023/0399019 A1) hereinafter Lee.
Regarding claim 2, Lashkari, Soltanian, and Iagnemma disclose the invention with respect to claim 1.
However, the combination of Lashkari, Soltanian, and Iagnemma fails to disclose further comprising: (g) for the selected pull-over location, determining a respective goal range that defines an area associated with the selected pull-over location within which the autonomous vehicle is to stop.
Lee discloses determining a respective goal range that defines an area associated with a selected pull-over location within which an autonomous vehicle is to stop [see Figure 15 and see Paragraphs 0202 and 0206 - discusses when a vehicle (see Paragraph 0006 - discusses an autonomous vehicle) is pulling over in a location, determining a safety zone (goal range), based on navigation information (see Paragraph 0132 - for example, an HD map), where a minimal risk maneuver (MRM) is performed and the vehicle stops in the safety zone (goal range)].
Lee suggests that by determining the safety zone, the vehicle can safely stop [see Paragraph 0200].
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention, with a reasonable expectation of success, to modify the computer-implemented method as taught by Lashkari to include a step (g) of determining a respective goal range that defines an area associated with a selected pull-over location within which an autonomous vehicle is to stop as taught by Lee in order to safely stop the vehicle [Lee, see Paragraph 0200].
Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over Lashkari in view of Soltanian in view of Iagnemma in view of Lerenc at al. (U.S. Publication No. 2013/0158869 A1) hereinafter Lerenc.
Regarding claim 8, Lashkari discloses the invention with respect to claim 1.
However, the combination of Lashkari, Soltanian, and Iagnemma fails to disclose wherein (c) comprises: determining a distance from the autonomous vehicle to each of the plurality of pull-over locations; and determining the one or more candidate pull-over locations based on the distance from the autonomous vehicle to each of the plurality of pull-over locations.
Lerenc discloses determining a distance from a vehicle to each of the plurality of pull-over locations [see Paragraphs 0028 and 0042-0043 - discusses calculating a distance to each pullover location]; and determining one or more candidate pull-over locations based on the distance from the autonomous vehicle to each of the plurality of pull-over locations [see Paragraph 0045-0047 - discusses changing the distance to time and excluding locations when the time (based on distance) exceeds a maximum travel time].
Lerenc suggests that by excluding locations that are outside of a maximum travel time reduces intensive computations [see Paragraphs 0022-0024].
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention, with a reasonable expectation of success, to modify the computer implemented-method at step (c) as taught by Lashkari to include determining a distance from a vehicle to each of the plurality of pull-over locations and determining one or more candidate pull-over locations based on the distance from the autonomous vehicle to each of the plurality of pull-over locations as taught by Lerenc in order to reduce intensive computations by excluding locations outside of a maximum travel time (based on distance) [Lerenc, see Paragraphs 0022-0024] for the autonomous vehicle.
Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over Lashkari in view of Soltanian in view of Iagnemma in view of Iagnemma at al. (U.S. Publication No. 2018/0113470 A1) hereinafter Iagnemma II.
Regarding claim 9, Lashkari, Soltanian, and Iagnemma disclose the invention with respect to claim 1.
However, the combination of Lashkari, Soltanian, and Iagnemma fails to disclose wherein the quality of the respective candidate pull-over location is based on a width and a length of a respective candidate pull-over location.
Iagnemma II discloses wherein a quality of a respective candidate pull-over location is based on a width and a length of a respective candidate pull-over location [see Paragraph 0093 - discusses a footprint (length and width) of an autonomous vehicle (AV) is used as a quality, see Paragraph 0022 – discusses that a potential (candidate) stopping place is defined as a shape corresponding to a footprint of the vehicle].
Iagnemma II suggests that a vehicle might not physically fit in stopping place depending on the shape and size of the vehicle [see Paragraph 0093]
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention, with a reasonable expectation of success, to modify the quality criteria as taught by Lashkari to include a quality of a respective candidate pull-over location that is based on a width and a length (of vehicle footprint) of a respective candidate pull-over location as taught by Iagnemma II in order to ensure that a vehicle can physically fit in the stopping place [Iagnemma II, see Paragraph 0093].
Claim 20 is rejected under 35 U.S.C. 103 as being unpatentable over Ravichandran in view of Lopez in view of Iagnemma in view of Bonk at al. (U.S. Publication No. 2019/0135283 A1) hereinafter Bonk.
Regarding claim 20, Ravichandran, Jung, and Iagnemma disclose the invention with respect to claim 19.
Ravichandran further discloses wherein (f) comprises: generating a trajectory for the autonomous vehicle to travel to a stopped position within a goal range associated with the selected pull-over location [see Paragraphs 0177 and 0199 - discusses selecting the available stopping place and identifying a trajectory to the available stopping place in a goal region where the vehicle travels to a stopped position at the stopped place], and controlling the motion of the autonomous vehicle based on the trajectory such that the autonomous vehicle reaches the stopped position within the goal range [see Paragraphs 0179 and 0199 - discusses the AV executing the trajectory in the goal region to the selected available stopping place where the vehicle will be in a stopped position at the stopped place].
However, the combination of Ravichandran, Jung, and Iagnemma fails to disclose (g) adjusting the route of the autonomous vehicle such that the autonomous vehicle is routed to the selected pull-over location.
Bonk discloses adjusting a route of an autonomous vehicle such that the autonomous vehicle is routed to a selected pull-over location [see Paragraph 0056 - discusses that a route planning engine of an autonomous vehicle provides a vehicle control module with a route such as a pick-up location (pullover location), the route planning engine generates the route based on instructions from a network computing system, and see Paragraphs 0042-0044 - discusses that a routing engine of the network computing system determines a detour route - therefore, a detour is determined to the pick-up location (pull-over location)].
Bonk suggests that road anomalies can affect the vehicle and cause the vehicle to be damaged [see Paragraph 0042], and by taking a detour avoids the anomaly (and damage to the vehicle) [see Paragraph 0044].
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention, with a reasonable expectation of success, to modify the computer implemented-method as taught by Ravichandran to adjust a route of an autonomous vehicle such that the autonomous vehicle is routed to a selected pull-over location (i.e. a detour) as taught by Bonk in order to avoid damaging the autonomous vehicle do to a road anomaly [Bonk, see Paragraphs 0042 and 0044].
Response to Arguments
Applicants’ arguments appear to be directed solely to the amended subject matter, and are not persuasive, as noted supra in the rejections of that claimed subject matter.
Conclusion
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/SHAYNE M. GILBERTSON/Examiner, Art Unit 3665
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