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 .
Status of the Claims
This Office Action is in response to the Applicants’ filing on 11/21/2025. Claims 1-20 were previously pending, of which claims 1-3, 13-16, and 18-20 have been amended, no claims have been cancelled or newly added. Accordingly, claims 1-20 are currently pending and are being examined below.
Response to Arguments
With respect to Applicant's remarks, see pages 13-18, filed 11/21/2025; Applicant’s “Amendment and Remarks” have been fully considered. Applicant’s remarks will be addressed in sequential order as they were presented.
With respect to the claim rejections under 35 U.S.C. § 103, applicant’s “Amendment and Remarks” have been fully considered and are not persuasive. Further consideration of the prior art of record determined that Zheng does appear to disclose the limitation as amended in claim 1, as previously rejected in claim 2. The prior art of record does allow for the determination of the likelihood of successfully taking over manual control with regard to a portion on a roadway. This would be determined upon entry to each road section, and calculated based on the map data, as the vehicle approached the area in which the takeover was necessary. Nothing in the claim language appears to have these ratios predetermined and assigned to the road section prior to the vehicle accessing the map information or that the road sections scheduled be traveled must be more than the continuation of a currently traveled road. The prior art reads on the claim language by the comparison of the estimated time for takeover to the required time to successfully takeover, that is calculated as the driver travels toward each road section using at least the map traffic data, risk associated with different road portions, and generic response times, as described in [0069, 0111-0114]. For clarity, updated application of prior art addresses the amended language, as mapped below. Therefore, the amended claims are still rejected under 35 U.S.C. § 103, and have been updated in the final office action below.
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.
Claims 1, 2, 4-15, and 17-20 are rejected under 35 U.S.C. 103 as being unpatentable over Zheng et al. (US 2019/0184897), hereinafter Zheng, in view of Kim et al. (US 2020/0166945 A1), hereinafter Kim.
With respect to claim 1, Zheng discloses An information processing device, comprising: a notification unit comprising a vibrator; ([0149-0150] “Specifically, the warning media …used to warn the driver …the selected media forms may include a vibration mechanism”)
a central processing unit (CPU) configured to: acquire the specific success ratio for each road section of a plurality of road sections; ([0069] “Additionally, there may be certain geographical areas where autonomous driving is prohibited or is deemed unsafe such as acceleration lanes, exit lanes, toll booths, known construction zones, school zones and portions of roadway near such areas. The risk associated with such events is determined by the auto mode risk detector 730.” [0112] “Additionally, information from the generic response time profile 1420, which includes for instance, an amount of time consumed by other drivers”)
wherein the switch is from automatic driving to manual driving; (see at least [0093] “The switch risk determiner 240 comprises a switch direction controller 1210, an autonomous to human (A-H) mode switch risk determiner 1230”)
calculate a manual driving recoverable time required for a driver who executes the automatic driving, to achieve the specific success ratio for the each road section of the plurality of road sections, (see at least [0111] “As shown in FIG. 14, the output of the switch task estimator… to initiate the switch to the manual mode of operation of the vehicle are input to the response time estimator 1430… estimates an amount of time required by the driver to complete each of the tasks estimated by the switch task estimator 1460. By one embodiment, the response time estimator 1430 estimates the amount of time required to perform the tasks based on a current passenger state, a driver profile 1410, and a generic response time profile 1420.” Note: The risk associated with the portions of roadway are determined in 230, output to 240 for risk assessment and time estimation, calculate the takeover time based on the risk of the portion of the roadway, and initiate the takeover if the time is less than the time to required execute a successful transition.)
wherein the manual driving recoverable time is calculated for the each of the road section, of the plurality of road sections, scheduled to travel, the specific success ratio is associated with a local dynamic map (LDM), (see at least [0111-0114] “By one embodiment, the response time estimator 1430 estimates the amount of time required to perform the tasks based on a current passenger state, a driver profile 1410, and a… generic response time profile 1420, which includes for instance, an amount of time consumed by other drivers… tasks to be performed and the corresponding response time estimated in performing the tasks are input to the switching risk estimator 1440.” [0046] “By one embodiment, to determine the risk, the current risk evaluator 230 receives as input, real-time vehicle data, real-time intrinsic and extrinsic data, sensor data, the driver profile 210, and the map/road configuration data 220.” Note: It is understood that the generic response time profile combined with the driver profile would give the likelihood of a successful takeover in the given time estimated. As written, this could be calculated as the vehicle entered each road section, rather than having it be retrieved as a predetermined value from the LDM.)
determine notification timing of a manual driving recovery request notification based on the calculated manual driving recoverable time; ([0146] “The warning instruction analyzer 1910 inputs each analyzed task to the warning time determiner 1950. The warning time determiner 1950 determines an amount of time required to perform a warning operation (referred to herein as warning duration time). Specifically, the warning duration time corresponds to a time period wherein a warning alert is presented to the driver of the vehicle, in order to ensure that the driver performs the corresponding task in a timely manner.”)
and control the notification unit to execute a notification process associated with the manual driving recovery request notification for the driver, wherein the manual driving recovery request notification includes a vibration of the vibrator. ([0149-0150] “Specifically, the warning media determiner 1970 associates each task with the at least one media 1980 that is used to warn the driver to perform the respective task… the warning media determiner 1970 may utilize vibratory media and/or display media to warn the driver.”)
Zheng discloses changing a vehicle from autonomous to manual based on map information, but does not explicitly disclose an LDM with a layers of information about the surrounding traffic.
However, Kim teaches the LDM includes a hierarchy of layers of information including predicted moving direction information to control the automatic driving; (see at least [0311-0314] “The LDM data 1050 may include a first layer 1052, a second layer 1054, a third layer 1056 and a fourth layer 1058” [0279] “Based on LDM data received through V2X communication, the LDM may store all relevant information (e.g., the present vehicle (another vehicle) location, speed, traffic light status, weather information, road surface condition, etc.) on a traffic condition (or a road condition for an area” [0462] “other vehicles located in an adjacent area are driving in the same direction, it is highly likely to have a similar predicted route.” [0284] “the vehicle of the present disclosure may construct autonomous driving using an LDM (relative coordinate high-definition map) formed by LDM data received through V2X communication”)
As both are in the same field of endeavor, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the map of Zheng to include the Local Dynamic Map disclosed in Kim, with reasonable expectation of success. The motivation for doing so would have been to provide a way to get continuously updated traffic data from the surrounding vehicles to control the autonomous vehicle, see Kim [0279].
With respect to claim 2, Zheng discloses the specific success ratio for the each road section of the plurality of road sections is ancillary information of the LDM. (see at least [0046] “The map/road configuration data 220 provides information pertaining to a geographical location where the vehicle is currently located. Additionally, the map/road configuration data 220 may include information corresponding to traffic in the geographical location of the vehicle.” [0111-0113] “information from the generic response time profile… may be used by the response time estimator 1430…the response time required to perform the set of estimated tasks may be determined based on…an amount of traffic on the road”)
With respect to claim 4, Zheng discloses the CPU is further configured to calculate the manual driving recoverable time based on learning data associated with the driver. ([0046] “The driver profile 210 data includes information pertaining to a driving history of the driver. Such information may include, for instance, a number of violations the driver has been involved in a predetermined time-period, a model of the vehicle the driver is operating, characteristics of the driver… etc.” [0112] “Moreover, the driver profile 1410 may comprise an alertness score of the driver that may be computed based on prior mode switching operations from autonomous to manual mode”)
With respect to claim 5, Zheng discloses the CPU is further configured to calculate the manual driving recoverable time based on learning data associated with the driver and each driver state of a plurality of driver states of the driver. ([0046] “The current risk evaluator 230 is configured to determine a risk… receives as input, real-time vehicle data, real-time intrinsic and extrinsic data, sensor data, the driver profile 210, and the map/road configuration data 220.” [0052] “The switch risk determiner 240 receives the real-time intrinsic and extrinsic data, information pertaining to the current state of the driver, and the current mode in which the vehicle is operating.” [0112] “Moreover, the driver profile 1410 may comprise an alertness score of the driver that may be computed based on prior mode switching operations from autonomous to manual mode”)
With respect to claim 6, Zheng discloses the CPU is further configured to calculate the manual driving recoverable time based on correspondence data between a recovery ratio and a recovery delay time from the automatic driving to the manual driving, and the recovery delay time is based on learning data associated with the driver and each driver state of a plurality of driver states of the driver. ([0112] “Moreover, the driver profile 1410 may comprise an alertness score of the driver that may be computed based on prior mode switching operations from autonomous to manual mode, and the corresponding times required by the driver in those switching operations to perform the set of estimated tasks.”)
With respect to claim 7, Zheng discloses the CPU is further configured to: acquire information from a sensor; and analyze a driver state of the plurality of driver states based on the acquired information. ([0084] “By one embodiment, the sensor activator 1010 activates the in-situ sensors 1020 to detect the driver state.”)
With respect to claim 8, Zheng discloses wherein a driver state of the plurality of driver states is driver information that reflects an arousal level of the driver. ([0049] “Additional information associated with the driver state may include information pertaining to a health of the driver, a functional state of the driver (i.e., whether the driver is drowsy, sleeping or feeling sleepy, and whether the driver is intoxicated), a mental state of the driver (e.g. an alertness level of the driver)”)
With respect to claim 9, Zheng discloses the CPU is further configured to: acquire operation information of the driver based on the switch from the automatic driving to the manual driving; ([0174] “As stated previously, the multi-modal switching warning unit collects information from a plurality of sensors to observe if the warning presented to the user is being followed. Further, the process in step 2270 determines based on the observation of step 2260, whether the scheduled task is completed.”)
and execute a learning data update process based on the operation information of the driver. ([0175] “In response to the scheduled task not being completed by the driver, the multi-modal switching warning unit 140 modifies the instruction in step 2280.”)
With respect to claim 10, Zheng discloses the notification control unit is further configured to execute the notification process of the manual driving recovery request notification for the driver via the notification unit at a specific timing, wherein the specific timing is based on the manual driving recoverable time. ([0102] “In step 1335, the process generates an A-H switch instruction warning, which is associated with a set of tasks to be performed by the driver of the vehicle before a successful switch to the human-driven mode of operating the vehicle can occur. Thereafter, the process in step 1340 generates (and outputs) the A-H vehicle control signal to instruct the control system of the vehicle to perform the switching operation concurrently with the driver performing the set of estimated tasks.”)
With respect to claim 11, Zheng discloses the notification unit further comprises at least one of a display unit or a sound output unit. ([0149-0150] “Specifically, the warning media determiner 1970 associates each task with the at least one media 1980 that is used to warn the driver to perform the respective task… Additionally, or alternatively, the type of selected media may be determined based on the state of the driver… a visual media (i.e., a display) and/or audio media form (i.e. speakers)”)
With respect to claim 12, Zheng discloses the specific success ratio corresponds to a requested recovery ratio (RRR) for recovery from the automatic driving to the manual driving. ([0112] “Moreover, the driver profile 1410 may comprise an alertness score of the driver that may be computed based on prior mode switching operations from autonomous to manual mode, and the corresponding times required by the driver in those switching operations to perform the set of estimated tasks.”)
With respect to claim 13, Zheng discloses an information processing device, comprising: a server configured to: generate a success ratio attached local dynamic map in which a success ratio of switch from automatic driving to manual driving is set for each road section of a plurality of road sections; ([0054] “Rather, the current risk evaluator 230 may execute an exception handling process e.g., to bring the vehicle to a stop in a safe manner… Instead, the current risk evaluator 230 may execute the exception handling process such as… , transmitting GPS location of the vehicle to a server that monitors the operations of the particular vehicle and other like vehicles.” Note: It is understood that the determination to transmit the GPS location to the server would be a marker that the takeover was unsuccessful and the ratio would be updated to modify future warning times as disclosed in paragraphs [0174-0175].)
and transmit the success ratio attached local dynamic map to a mobile device, ([0176] “This mobile device 2300 includes, but is not limited to, a smart phone, a tablet, a music player, a handled gaming console, a global positioning system (GPS) receiver,”)
wherein the mobile device: calculates a manual driving recoverable time required for a driver who executes the automatic driving to achieve the success ratio; ([0111-0112] “By one embodiment, the response time estimator 1430 estimates the amount of time required to perform the tasks based on a current passenger state, a driver profile 1410, and a generic response time profile 1420… Additionally, information from the generic response time profile 1420, which includes for instance, an amount of time consumed by other drivers” Note: It is understood that the generic response time profile combined with the driver profile would give the likelihood of a successful takeover in the given time estimated.)
determines notification timing of a manual driving recovery request notification based on the calculated manual driving recoverable time; ([0146] “The warning instruction analyzer 1910 inputs each analyzed task to the warning time determiner 1950. The warning time determiner 1950 determines an amount of time required to perform a warning operation (referred to herein as warning duration time). Specifically, the warning duration time corresponds to a time period wherein a warning alert is presented to the driver of the vehicle, in order to ensure that the driver performs the corresponding task in a timely manner.”)
and control a notification unit to execute a notification process associated with the manual driving recovery request notification for the driver, wherein the manual driving recovery request notification includes a vibration of a vibrator in the notification unit. ([0149-0150] “Specifically, the warning media determiner 1970 associates each task with the at least one media 1980 that is used to warn the driver to perform the respective task… the warning media determiner 1970 may utilize vibratory media and/or display media to warn the driver.”)
Zheng discloses changing a vehicle from autonomous to manual based on map information, but does not explicitly disclose an LDM with a layers of information about the surrounding traffic.
However, Kim teaches wherein, the s (see at least [0081] “the vehicle 100 may be switched from the manual mode into the autonomous mode or from the autonomous module into the manual mode based on driving environment information received through a communication apparatus 400.” [0311-0314] “The LDM data 1050 may include a first layer 1052, a second layer 1054, a third layer 1056 and a fourth layer 1058… lane information under construction, a variable speed lane, a road surface condition, traffic, and the weather may be included in the third layer 1056.” [0462] “other vehicles located in an adjacent area are driving in the same direction, it is highly likely to have a similar predicted route.” Note: The combination of the time required to switch taught by Zheng and the LDM of Kim would have the timing data of recorded as environmental/road data to the LDM.)
As both are in the same field of endeavor, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the map of Zheng to include the Local Dynamic Map disclosed in Kim, with reasonable expectation of success. The motivation for doing so would have been to provide a way to get continuously updated traffic data from the surrounding vehicles to control the autonomous vehicle, see Kim [0279].
With respect to claim 14, Zheng discloses the server is further configured to execute, based on a traffic state of each road section of the plurality of road sections, a process to update the success ratio. ([0046] “The map/road configuration data 220 provides information pertaining to a geographical location where the vehicle is currently located.” [0054] “Instead, the current risk evaluator 230 may execute the exception handling process such as… transmitting GPS location of the vehicle to a server that monitors the operations of the particular vehicle and other like vehicles.” Note: It is understood that the determination to transmit the GPS location to the server would be a marker that the takeover was unsuccessful and the ratio would be updated to modify future warning times as disclosed in paragraphs [0174-0175].)
With respect to claim 15, all the limitations have been analyzed in view of claims 1 and 2 with the exception of sensors, and it has been determined that claim 15 does not teach or define any new limitations beyond those previously recited in claim 1; therefore, claim 15 is also rejected over the same rationale as claims 1 and 2, also the sensors as cited in paragraphs [0040] and [0066].
With respect to claim 17, all the limitations have been analyzed in view of claim 6, and it has been determined that claim 17 does not teach or define any new limitations beyond those previously recited in claim 6; therefore, claim 17 is also rejected over the same rationale as claim 6.
With respect to claim 18, all the limitations have been analyzed in view of claims 1 and 13, and it has been determined that claim 18 does not teach or define any new limitations beyond those previously recited in claims 1 and 13; therefore, claim 18 is also rejected over the same rationale as claims 1 and 13.
With respect to claims 19 and 20, all the limitations have been analyzed in view of claim 1, and it has been determined that claims 19 and 20 do not teach or define any new limitations beyond those previously recited in claim 1; therefore, claims 19 and 20 are also rejected over the same rationale as claim 1.
Claims 3 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Zheng in view of Kim as applied to claims 1 and 15 above, and further in view of Aoi et al. (US 2019/0056732), hereinafter Aoi.
With respect to claim 3, Zheng discloses the limitations of claim 1 and the risk and time estimation happening based on traffic information pertaining to certain portions of roads, but does not explicitly disclose the timing being made based on time to enter a road section.
However, Aoi teaches the CPU is further configured to determine, as the notification timing of the manual driving recovery request notification, timing based on a time to enter a road section of the plurality of road sections, that requires the manual driving, is equal to or larger than the manual driving recoverable time. ([0151] “In addition, in the case where a determination result by the manual driving recovery level setting unit 14 is Level 3, and it is not determined that manual driving cannot be recovered, the driver can cope with manual driving in 10 to 30 seconds. Thus, as shown in FIG. 4(b), the alert generation unit 17 controls the navigation apparatus 21 to announce a switch request, for example, 35 seconds before the switching zone Z2 is entered, according to the state of the driver.”)
As both are in the same field of endeavor, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify Zheng to include the above limitations disclosed in Aoi, with reasonable expectation of success. The motivation for doing so would have been to ensure the driver is notified within a proper period of entering a specified road segment, see Aoi [0148].
With respect to claim 16, all the limitations have been analyzed in view of claim 3, and it has been determined that claim 16 does not teach or define any new limitations beyond those previously recited in claim 3; therefore, claim 16 is also rejected over the same rationale as claim 3.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/S.M.O./Examiner, Art Unit 3669
/NAVID Z. MEHDIZADEH/Supervisory Patent Examiner, Art Unit 3669
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