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 .
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1-3,5,7-12,14 and 16 are rejected under 35 U.S.C. 102(a)(1) and (a)(2) as being anticipated by Bradlow (US 20200124430 A1).
Claim 1. Bradlow teaches a driving assistance device
(Fig. 5 a sensor system of a PMV)
comprising:
at least one memory configured to store instructions
([0181] memories 2106)
; and
at least one processor ([0180][0181]) configured to execute the instructions to:
acquire travel information about a vehicle, the travel information including traveling video of
the vehicle and sidewalk information related to a sidewalk
([0141] In some embodiments, different types of sensor data are combined with location data to develop a characteristic fingerprint of a surface for a travel corridor... an asphalt bike lane and a concrete sidewalk may be arranged in a parallel, adjacent fashion...the utilized travel corridor for a PMV may be inferred using the general location data and specific data from one or more sensors.
[0135] The data collected from an imaging device may be used to determine a travel surface type.
[0143][0144] the disclosed embodiments can distinguish between the PMV traveling on the bike lane 702 or the sidewalk 704 by combining the outputs of sensor data with known characteristics based on location data (e.g., urban layout).
[0176][0177] a single video frame of visual data that is analyzed by the second recurrent neural network. As shown, the recurrent neural network determined that a travel surface in the video frame is a sidewalk. The determination may be associated with a confidence value.).
the sidewalk comprising a first portion on which the vehicle is not allowed and a second portion on which the vehicle is allowed
([0063] Local ordinances may restrict PMVs from traveling in particular lanes or routes or prohibit usage in pedestrian corridors.
[0084] In some instances, a PMV may be restricted from traveling in a particular travel corridor. For example, a PMV may be prohibited from using the car lanes 210 and 212, or sidewalks 240. );
detect driving of the vehicle as dangerous driving, based on the sidewalk information, in a
case where the vehicle is traveling on the first portion
([0122] A command or action may occur if the analysis algorithm predicts that a PMV has been traveling on a particular surface at a particular confidence level.);
detect driving of the vehicle as non-dangerous driving, based on the traveling video, in a case where the vehicle is traveling on the second portion detect dangerous driving of the vehicle based on sidewalk information related to a sidewalk, the sidewalk information included in the travel information
([0065] A computational algorithm may require, for example, a threshold amount of matching to identify the pattern. Hence, a matching value that is less than the threshold may be recognized as a known pattern but not identified as such to perform an action accordingly. );
and present the dangerous driving.
([0122] a warning message may issue if the PMV has been determined to be traveling on a sidewalk for at least 15 seconds...For example, a display device of the PMV may issue a warning message to move off a sidewalk if the analysis algorithm is 75% confident. ).
Claim 2. Bradlow teaches the driving assistance device according to claim 1,
wherein the at least one processor is further configured to execute the instructions to:
acquire position information of the vehicle
([0104] In some embodiments, a PMV integrates an electronic magnetic compass (e.g., a magnetometer) to assist in position location or navigation applications.
[0113][0114] The location data 402 may be obtained from a GPS system or other similar system. ),
and detect the dangerous driving based on the position information and coordinate information
of the sidewalk
.([0116] The data analysis algorithm 508 may utilize sensor data 504 to determine the travel surface type as a function of location.
[0122] The PMV trip 606 may create a feedback loop between location data and commands or actions that influence the PMV trip 606.)
Claim 3. Bradlow teaches the driving assistance device according to claim 1,
wherein the at least one processor is further configured to execute the instructions to:
detect the dangerous driving based on position information of a pedestrian
([0122] For example, a display device of the PMV may issue a warning message to move off a sidewalk if the analysis algorithm is 75% confident. The PMV trip 606 may create a feedback loop between location data and commands or actions that influence the PMV trip 606. The behavior of a PMV user may be affected or altered due to the use of the map during the PMV trip 606. ).
.
Claim 5. Bradlow teaches the driving assistance device according to claim 2,
wherein the at least one processor is further configured to execute the instructions to:
detect the dangerous driving based on whether a roadway and the sidewalk are
distinguished from each other
([0141] For example, an asphalt bike lane and a concrete sidewalk may be arranged in a parallel, adjacent fashion. GPS data may not be of sufficient resolution to distinguish PMV travel in the bike lane from PMV travel on the sidewalk. In this example, the utilized travel corridor for a PMV may be inferred using the general location data and specific data from one or more sensors.).
Claim 7. Bradlow teaches the driving assistance device according to claim 1, wherein the at least one processor is further configured to execute the instructions to: capture a traveling video of the vehicle, and compare the traveling video with the sidewalk information and detects the dangerous driving
([0176][0177] a single video frame of visual data that is analyzed by the second recurrent neural network. As shown, the recurrent neural network determined that a travel surface in the video frame is a sidewalk. The determination may be associated with a confidence value.).
Claim 8. Bradlow teaches the driving assistance device according to claim 1, wherein the at least one processor is further configured to execute the instructions to: warn a driver of the vehicle of the dangerous driving
([0122] For example, a warning message may issue if the PMV has been determined to be traveling on a sidewalk for at least 15 seconds. ).
Claim 9. Bradlow teaches the driving assistance device according to claim 8, wherein the at least one processor is further configured to execute the instructions to: warn the driver near an occurrence position stored in a storage device
([0006] PMV riding activities can be shared with local governments and agencies to help determine infrastructure needs and identify emerging or existing hazards in travel environments. [0063] In other instances, intelligent sensing systems are used to increase the safety of PMVs by warning users of restricted usage in areas of known hazards, such as in construction zones or nearby potholes. [0120] The map may be updated via wireless transmission to the PMV. The updated map may then be utilized to control or influence PMV usage during a PMV trip 606. ).
Claim 10. Bradlow teaches the a driving assistance method comprising:
acquiring travel information of a vehicle, the travel information including traveling video of
the vehicle and sidewalk information related to a sidewalk
([0141] In some embodiments, different types of sensor data are combined with location data to develop a characteristic fingerprint of a surface for a travel corridor... an asphalt bike lane and a concrete sidewalk may be arranged in a parallel, adjacent fashion...the utilized travel corridor for a PMV may be inferred using the general location data and specific data from one or more sensors.
[0135] The data collected from an imaging device may be used to determine a travel surface type.
[0143][0144] the disclosed embodiments can distinguish between the PMV traveling on the bike lane 702 or the sidewalk 704 by combining the outputs of sensor data with known characteristics based on location data (e.g., urban layout).
[0176][0177] a single video frame of visual data that is analyzed by the second recurrent neural network. As shown, the recurrent neural network determined that a travel surface in the video frame is a sidewalk. The determination may be associated with a confidence value.).
the sidewalk comprising a first portion on which the vehicle is not allowed and a second portion on which the vehicle is allowed
([0063] Local ordinances may restrict PMVs from traveling in particular lanes or routes or prohibit usage in pedestrian corridors.
[0084] In some instances, a PMV may be restricted from traveling in a particular travel corridor. For example, a PMV may be prohibited from using the car lanes 210 and 212, or sidewalks 240. );
detecting driving of the vehicle as dangerous driving, based on the traveling video, in a case
where the vehicle is traveling on the first portion
([0122] A command or action may occur if the analysis algorithm predicts that a PMV has been traveling on a particular surface at a particular confidence level.);
detecting driving of the vehicle as non-dangerous driving, based on the sidewalk
information, in a case where the vehicle is traveling on the second portion detecting dangerous
driving of the vehicle based on sidewalk information that pertains to a sidewalk included in the
travel information
([0065] A computational algorithm may require, for example, a threshold amount of matching to identify the pattern. Hence, a matching value that is less than the threshold may be recognized as a known pattern but not identified as such to perform an action accordingly. );
and presenting the dangerous driving in a case where the dangerous driving has been detected
([0122] a warning message may issue if the PMV has been determined to be traveling on a sidewalk for at least 15 seconds...For example, a display device of the PMV may issue a warning message to move off a sidewalk if the analysis algorithm is 75% confident. ).
Claim 11. Bradlow teaches a non-transitory recording medium having stored therein a program causing a computer to execute:
acquiring travel information of a vehicle from the vehicle, the travel information including
traveling video of the vehicle and sidewalk information related to a sidewalk
([0141] In some embodiments, different types of sensor data are combined with location data to develop a characteristic fingerprint of a surface for a travel corridor... an asphalt bike lane and a concrete sidewalk may be arranged in a parallel, adjacent fashion...the utilized travel corridor for a PMV may be inferred using the general location data and specific data from one or more sensors.
[0135] The data collected from an imaging device may be used to determine a travel surface type.
[0143][0144] the disclosed embodiments can distinguish between the PMV traveling on the bike lane 702 or the sidewalk 704 by combining the outputs of sensor data with known characteristics based on location data (e.g., urban layout).
[0176][0177] a single video frame of visual data that is analyzed by the second recurrent neural network. As shown, the recurrent neural network determined that a travel surface in the video frame is a sidewalk. The determination may be associated with a confidence value.).
the sidewalk comprising a first portion on which the vehicle is not allowed and a second portion on which the vehicle is allowed
([0063] Local ordinances may restrict PMVs from traveling in particular lanes or routes or prohibit usage in pedestrian corridors.
[0084] In some instances, a PMV may be restricted from traveling in a particular travel corridor. For example, a PMV may be prohibited from using the car lanes 210 and 212, or sidewalks 240. );
detecting driving of the vehicle as dangerous driving, based on the sidewalk information, in a
case where the vehicle is traveling on the first portion
([0122] A command or action may occur if the analysis algorithm predicts that a PMV has been traveling on a particular surface at a particular confidence level.);
detecting driving of the vehicle as non-dangerous driving, based on the traveling video, in a
case where the vehicle is traveling on the second portion detecting dangerous driving of the vehicle based on sidewalk information that pertains to a sidewalk included in the travel information
([0065] A computational algorithm may require, for example, a threshold amount of matching to identify the pattern. Hence, a matching value that is less than the threshold may be recognized as a known pattern but not identified as such to perform an action accordingly. );
and presenting the dangerous driving to a predetermined output destination in a case
where the dangerous driving has been detected
([0122] a warning message may issue if the PMV has been determined to be traveling on a sidewalk for at least 15 seconds...For example, a display device of the PMV may issue a warning message to move off a sidewalk if the analysis algorithm is 75% confident. ).
Claim 12. Bradlow teaches the driving assistance device according to claim 1, wherein the vehicle is a bicycle, and the second portion is a dedicated bicycle lane provided on the sidewalk
([0005] Examples of the vehicles include personal mobility vehicles (PMVs) such as scooters, bicycles, or transportation pods.
[0083] The bike lanes are delineated by car-side lane markings 224 and curb-side lane markings 222.
[0084] In some instances, a PMV may be restricted from traveling in a particular travel corridor. For example, a PMV may be prohibited from using the car lanes 210 and 212, or sidewalks 240. ).
Claim 14. Bradlow teaches the driving assistance method according to claim 10, further comprising detecting the dangerous driving based on position information of a pedestrian, wherein the vehicle is a bicycle, and second portion is a dedicated bicycle lane provided on the sidewalk
([0005] Examples of the vehicles include personal mobility vehicles (PMVs) such as scooters, bicycles, or transportation pods.
[0083] The bike lanes are delineated by car-side lane markings 224 and curb-side lane markings 222.
[0084] In some instances, a PMV may be restricted from traveling in a particular travel corridor. For example, a PMV may be prohibited from using the car lanes 210 and 212, or sidewalks 240. ).
Claim 16. Bradlow teaches the non-transitory recording medium according to claim 11, further comprising
detecting the dangerous driving based on position information of a pedestrian, wherein the vehicle is a bicycle, and second portion is a dedicated bicycle lane provided on the sidewalk
([0005] Examples of the vehicles include personal mobility vehicles (PMVs) such as scooters, bicycles, or transportation pods.
[0083] The bike lanes are delineated by car-side lane markings 224 and curb-side lane markings 222.
[0084] In some instances, a PMV may be restricted from traveling in a particular travel corridor. For example, a PMV may be prohibited from using the car lanes 210 and 212, or sidewalks 240. ).
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
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) 4 and 6 are rejected under 35 U.S.C. 103 as being unpatentable over Bradlow in view of Haynes (US 20230339395 A1).
Claim 4. Bradlow teaches the driving assistance device according to claim 3, and discloses the use of position information but does not specifically disclose wherein the position information of the pedestrian is acquired by a mobile terminal.
However, Haynes teaches wherein the position information of the pedestrian is acquired by a mobile terminal
([0178] f the risk estimation indicates a high probability of a collision with a pedestrian, the mobility safety system 104 may selectively record only the sensor data related to the pedestrian's location and movement,
[0185] In addition to adjusting the behavior of the mobility platform and generating alerts, the mobility safety system 104 may provide feedback to the operator of the device via a user interface for example on a mobile device)
Therefore, it would have been obvious to one ordinarily skilled in the art before the effective filing date of invention to use the position information as taught by Haynes within the system of Bradlow for the purpose of avoiding a collision with a pedestrian based on the sensed data.
Claim 6. Bradlow teaches the driving assistance device according to claim 3, and discloses the use of restricting the travel along high pedestrian traffic and slowing the vehicle but does not specifically disclose wherein the at least one processor is further configured to execute the instructions to: detect the dangerous driving in a case where a distance between the vehicle and the pedestrian exceeds a threshold and the vehicle suddenly brakes.
However, Haynes teaches wherein the at least one processor is further configured to execute the instructions to: detect the dangerous driving in a case where a distance between the vehicle and the pedestrian exceeds a threshold and the vehicle suddenly brakes
( [0125] physical alerts may also be generated, such as braking or swerving the mobility safety system 104 to avoid a potential collision. [0223] In some examples, the mobility safety system 104 can provide an emergency stop capability in the event of an imminent collision.
[0172] Once the level of risk exceeds a certain threshold, for example, the alert mechanism 214 is triggered to generate the first alert directed at the operator of the mobility platform.
[0178] if the risk estimation indicates a high probability of a collision with a pedestrian,
[0201] if the mobility safety system 104 is approaching a pedestrian who is looking at their phone and not paying attention to the road, the actor-ego interaction prediction component 704 may predict that the pedestrian is likely to continue walking in their current path and that the mobility safety system 104 needs to take evasive action.)
Therefore, it would have been obvious to one ordinarily skilled in the art before the effective filing date of invention to use the process to detect the dangerous driving in a case where a distance between the vehicle and the pedestrian exceeds a threshold and the vehicle suddenly brakes as taught by Haynes within the system of Bradlow for the purpose of enhancing the system to actuate evasive countermeasures in order to avoid a collision with a pedestrian.
Claim(s) 13, 15 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Bradlow in view of Takahashi (JP 2001357496 A).
Claim 13. Bradlow teaches the driving assistance device according to claim 4, and further discloses the process of communicating information with mobile phones ([0185]) but does not specifically disclose wherein the position information of the pedestrian is acquired by a mobile terminal held by the pedestrian
However, Takahashi teaches wherein the position information of the pedestrian is acquired by a mobile terminal held by the pedestrian
(Page 4/5- A position information search result signal 106 having a unique ID (Identifier) is transmitted from the mobile phone 102 to the car navigation devices 104a to 104c.
Page 9- if there is a vehicle approaching the road, regardless of whether it is a pedestrian, a bicycle, a motorcycle, or a vehicle, It is possible to warn all approaching moving objects having a mobile phone at a warning level corresponding to danger. ).
Therefore, it would have been obvious to one ordinarily skilled in the art before the effective filing date of invention to use the position information of the pedestrian as taught by Takahashi within the system of Bradlow for the purpose of communicating a warning to devices that are within range and proximity to a potential collision with the vehicle.
Claim 15. Bradlow teaches the method corresponding to claim 10, and discloses the process of communicating information with mobile phones ([0185]) but does not specifically disclose wherein the position information of the pedestrian is acquired by a mobile terminal held by the pedestrian.
However, Takahashi teaches wherein the position information of the pedestrian is acquired by a mobile terminal held by the pedestrian
(Page 4/5- A position information search result signal 106 having a unique ID (Identifier) is transmitted from the mobile phone 102 to the car navigation devices 104a to 104c.
Page 9- if there is a vehicle approaching the road, regardless of whether it is a pedestrian, a bicycle, a motorcycle, or a vehicle, It is possible to warn all approaching moving objects having a mobile phone at a warning level corresponding to danger. ).
Therefore, it would have been obvious to one ordinarily skilled in the art before the effective filing date of invention to use the position information of the pedestrian as taught by Takahashi within the system of Bradlow for the purpose of communicating a warning to devices that are within range and proximity to a potential collision with the vehicle.
Claim 17. Bradlow teaches the non-transitory recording medium according to claim 11, and further discloses the process of communicating information with mobile phones ([0185]) but does not specifically disclose wherein the position information of the pedestrian is acquired by a mobile terminal held by the pedestrian
However, Takahashi teaches wherein the position information of the pedestrian is acquired by a mobile terminal held by the pedestrian
(Page 4/5- A position information search result signal 106 having a unique ID (Identifier) is transmitted from the mobile phone 102 to the car navigation devices 104a to 104c.
Page 9- if there is a vehicle approaching the road, regardless of whether it is a pedestrian, a bicycle, a motorcycle, or a vehicle, It is possible to warn all approaching moving objects having a mobile phone at a warning level corresponding to danger. ).
Therefore, it would have been obvious to one ordinarily skilled in the art before the effective filing date of invention to use the position information of the pedestrian as taught by Takahashi within the system of Bradlow for the purpose of communicating a warning to devices that are within range and proximity to a potential collision with the vehicle.
Response to Arguments
Applicant’s arguments with respect to claim(s) 1-17 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/RUFUS C POINT/Primary Examiner, Art Unit 2689
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