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 Claims
Claims 1-19 are pending in this application.
Claims 1, 18, and 19 are currently amended.
No claims are newly presented.
No claims are cancelled.
Examiner's Note
Examiner has cited particular paragraphs / columns and line numbers or figures in the references as applied to the claims below for the convenience of the applicant. Although the specified citations are representative of the teachings in the art and are applied to the specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested from the applicant, in preparing the responses, to fully consider the references in entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the examiner. Applicant is reminded that the Examiner is entitled to give the broadest reasonable interpretation to the language of the claims. Furthermore, the Examiner is not limited to Applicants’ definition which is not specifically set forth in the claims.
Priority
It is made of record that certified copies of the priority documents have been received.
Continued Examination
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on Sep. 17, 2026 has been entered.
Claim Rejections - 35 USC § 103
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1-6 and 18-19 are rejected under 35 U.S.C. 103 as being unpatentable over Hall (US RE38870 E) in view of Lee (KR 102471234 B1) in view of Cho et al. (US 11355006 B1) in view of Neser (US 20220058399 A1) (the combination of which will be referred to as 'combination Hall' hereinafter). As regards the individual claims:
Regarding claim 1, Hall teaches a crosswalk safety system comprising:
a sensor device configured to obtain information related to a speed of a vehicle approaching a crosswalk through a roadway and a separation distance between the vehicle and the crosswalk; (Hall: ¶ 020; Col. 4, Lns. 20-23; independently monitor each lane of traffic with speed detection devices that have a direct line-of-sight to approaching vehicles.) (Hall: Fig. 003) a first warning device configured to issue a first warning to the vehicle in response that the speed obtained through the sensor device is equal to or greater than a first reference speed and the separation distance between the vehicle and the crosswalk is a first separation distance; (Hall: ¶ 049; Cols. 15, Lns. 52-55; Authorities can limit and enforce a maximum vehicle speed, even in the absence of a pedestrian. This is accomplished by setting the Controller 10 to also respond to Conditional Control 40 sensors 40a for speed control) (Hall: ¶ 047; Cols. 15, Lns. 21-34; Controller 10 illuminates a System Status Alarm 70 display 70b in direct view of the driver, to inform of the pedestrian's presence. . . . Conditional Control 40 is provided by a sensor 40a that is used to detect the presence of a vehicle traveling in the direction of the intersection) (Hall: ¶ 047; Cols. 15, Lns. 32-34; ground-mounted induction loop) a second warning device configured to issue a second warning to the vehicle in response that the speed obtained through the sensor device is equal to or greater than a second reference speed (Hall: ¶ 047; Cols. 15, Lns. 17-25, 31-34; Additional reinforcement is provided when the Controller 10 illuminates a System Status Alarm 70 display 70b in direct view of the driver, to inform of the pedestrian's presence. The system can also activate an alarm 70c directed at the pedestrian to alert him to his impending collision with the vehicle . . . Conditional Control 40 is provided by a sensor 40a that is used to detect the presence of a vehicle traveling in the direction of the intersection such as one or more ultrasonic sensors. (A ground-mounted induction loop would also suffice.)) (Hall: ¶ 022; Cols. 10, Lns. 12-28; authorities can set the threshold of the Trigger Sensors 30 required to invoke a system response, set the degree of activation response for Vehicle Restrictors 20, set the threshold and duration of camera response, or change the System Status Alarm 70 message for visual display . . . These parameters are unique to a particular implementation and they are the levels that a monitored object has to reach before a certain system response is invoked or changed) (Hall: ¶ 027; Cols. 11, Lns. 4-6; Trigger Sensors 30a, 30b, 30c in FIG. 2 are speed detection sensors such as the radar or laser device) and the separation distance between the vehicle and the crosswalk is a second separation distance after issuing the first warning; (Hall: ¶ 047; Cols. 15, Lns. 17-25, 31-34; As the pedestrian and the vehicle advanced toward the same intersection, the Trigger Sensor 30a notifies the Controller 10 to activate the Vehicle Restrictors 20, to provide an indication to the operator to slow down. Additional reinforcement is provided when the Controller 10 illuminates a System Status Alarm 70 display 70b in direct view of the driver, to inform of the pedestrian's presence. The system can also activate an alarm 70c directed at the pedestrian to alert him to his impending collision with the vehicle . . . Conditional Control 40 is provided by a sensor 40a that is used to detect the presence of a vehicle traveling in the direction of the intersection such as one or more ultrasonic sensors. (A ground-mounted induction loop would also suffice.)) . . . a controller electrically connected to the sensor device, the first warning device, the second warning device, and the robot to control operations of the first warning device, the second warning device, and the robot. (Hall: ¶ 007; Col. 6, Lns. 34-39; Controller 10 hardware is an industrial grad computer having a conventional microprocessor and computer readable memory that is used to provide control for the Collision Avoidance System based upon input from sensors and operational settings. The Controller 10 then executes the control logic to activate the appropriate outputs)
Hall does not explicitly teach: . . . a robot arranged to move between the vehicle and a pedestrian crossing the crosswalk . . . wherein the controller is configured to perform machine learning on an operation of the robot . . . ; however, Lee does teach:
. . . a robot arranged to move between the vehicle and a pedestrian crossing the crosswalk (Lee: ¶ 064; drivable area P represents a range in which the safe companion robot 100a can drive, and preferably may be a rectangular area having vehicle stop lines 300a and 300b of both lanes as rims.). . . wherein the controller is configured to perform machine learning on an operation of the robot, (Lee: ¶ 072; companion robot 100a may generate input data obtained by merging image information and LIDAR information into one, and apply the generated input data to a pre-learned second analysis model to estimate object recognition) (Lee: ¶ 019; [Fig.] 6 is a diagram for explaining the configuration of a second analysis model) (Lee: Fig. 6; [showing use of Convolutional Neural Network (CNN)]) . . .
Before the effective filling date of the claimed invention, it would have been obvious to one of ordinary skill in the art to combine the teachings of Lee with the teachings of Hall because doing so would result in the predicable benefit of “helping a pedestrian at a crosswalk [avoid] a collision with a vehicle in advance by accompanying the pedestrian to safely pass at the crosswalk" (Lee: ¶ 007) in a way that easily merges with the multi-step warning process that Hall teaches.
To the extent Hall is silent regarding or does not explicitly teach: in response that the separation distance between the vehicle and the crosswalk obtained through the sensor device is less than or equal to a third separation distance after issuing the second warning; and; however, Cho does teach:
in response that the separation distance between the vehicle and the crosswalk obtained through the sensor device is less than or equal to a third separation distance after issuing the second warning; and (Cho: ¶ 053; Col. 9, Lns. 54-61; When the electronic device 110 identifies that a distance between the vehicle 120 and the crosswalk is less than or equal to a first distance d1, or the traffic light turns on in green, the electronic device 110 may then provide a signal requesting the first indicator 400 to form the screen wall.).
Before the effective filling date of the claimed invention, it would have been obvious to one of ordinary skill in the art to combine the teachings of Cho with the teachings of Hall because doing so would result in the predicable benefit of "notifying the pedestrians of approaching vehicles or a method of controlling the speed of the vehicle approaching the crosswalk" (Cho: ¶ 004; Col. 1, Lns 30-35).
To the extent Hall is silent regarding or does not explicitly teach: wherein the controller is further configured to perform machine learning on the first separation distance, the second separation distance, the third separation distance, the first reference speed, and the second reference speed, and wherein the controller is configured to reset one or more of the first separation distance, the second separation distance, the third separation distance, the first reference speed, and second reference speed based on a result of the machine learning; however, Neser does teach:
wherein the controller is further configured to perform machine learning on the first separation distance, the second separation distance, the third separation distance, the first reference speed, and the second reference speed, and wherein the controller is configured to reset one or more of the first separation distance, the second separation distance, the third separation distance, the first reference speed, and second reference speed (Neser: ¶ 059; car 114e impinges on a danger zone 138 of the animal 118. The impingement may be actual or predicted, even though there has been no actual contact of the car 114e to the animal 118. This near-miss detection will cause . . . a real-time alert to warn the driver of the car 114e, or take some other action. Also in image 130, it is evident that truck 114d has entered the crosswalk 112 while pedestrian 116 is still in the crosswalk. Depending on dimensional thresholds of the danger zones 134d, 136, respectively, an alert may be logged and stored in a data storage device) based on a result of the machine learning. (Neser: ¶ 064; In at least some cases, kriging algorithms perform spatial interpolation by applying weighting factors based on the calculated distance between geographic points where anchor points or danger zone boundary data has been collected. The kriging techniques model the correlation structures of the data parsed from images as a function of distance and may include information about any known covariance between the predicted separation or lack of separation between danger zone boundaries and other spatial information (co-kriging).)
Before the effective filling date of the claimed invention, it would have been obvious to one of ordinary skill in the art to combine the teachings of Neser with the teachings of Hall because doing so would result in the predicable benefit of improving the prediction accuracy of “time-based predictive dangerous conditions." (Neser: ¶ 068).
Regarding claim 2, as detailed above, combination Hall teaches the invention as detailed with respect to claim 1. Hall further teaches:
wherein the sensor device includes a Light Detection and Ranging (LiDAR) sensor. (Hall: ¶ 009; Col. 7, Lns. 4; speed detection (radar, laser))
Regarding claim 3, as detailed above, combination Hall teaches the invention as detailed with respect to claim 2. Hall further teaches:
further including: a traffic light arranged in an external direction of the crosswalk to transmit a traffic signal to vehicles in a state that a direction in which the crosswalk faces the roadway is the external direction, (Hall: Fig. 003; [[40a]]) wherein the sensor device is coupled to the traffic light. (Hall: ¶ 047; Cols. 15, Lns. 29-31; Conditional Control 40 is provided by a sensor 40a that is used to detect the presence of a vehicle traveling in the direction of the intersection)
Regarding claim 4, as detailed above, combination Hall teaches the invention as detailed with respect to claim 3. Hall further teaches:
wherein the traffic light includes a plurality of traffic lights, each of which is arranged adjacent to an end portion of the crosswalk in an extension direction in a state that a direction in which the crosswalk extends is the extension direction, (Hall: Fig. 005; [[30a]]) wherein the sensor device is coupled to each of the traffic lights, and wherein the controller is coupled to at least one of the plurality of traffic lights. (Hall: ¶ 047; Cols. 15, Lns. 18-25; Trigger Sensor 30a notifies the Controller 10 to activate the Vehicle Restrictors 20, to provide an indication to the operator to slow down. Additional reinforcement is provided when the Controller 10 illuminates a System Status Alarm 70 display 70b in direct view of the driver, to inform of the pedestrian's presence. The system can also activate an alarm 70c directed at the pedestrian to alert him to his impending collision with the vehicle.)
Regarding claim 5, as detailed above, combination Hall teaches the invention as detailed with respect to claim 1. Hall further teaches:
wherein the first warning device includes a light source member that emits light to provide the first warning to the vehicle. (Hall: Fig. 003; [[40a]]) (Hall: ¶ 047; Cols. 15, Lns. 18-25; Trigger Sensor 30a notifies the Controller 10 to activate the Vehicle Restrictors 20, to provide an indication to the operator to slow down. Additional reinforcement is provided when the Controller 10 illuminates a System Status Alarm 70 display 70b in direct view of the driver, to inform of the pedestrian's presence. The system can also activate an alarm 70c directed at the pedestrian to alert him to his impending collision with the vehicle.)
Regarding claim 6, as detailed above, combination Hall teaches the invention as detailed with respect to claim 5. Cho further teaches:
wherein the light source member includes a plurality of light source members arranged along an extension direction in an external direction of the crosswalk in a state that a direction in which the crosswalk faces the roadway is the external direction and a direction in which the crosswalk extends is the extension direction. (Cho: ¶ 055; Cols. 10, Lns. 24-25; may control the indicator 500 to display at least some of the LEDs 502 in green) (Cho: Fig. 002)
Regarding claim 18, Hall teaches a method of controlling a crosswalk safety system, the method comprising:
obtaining, by a controller, (Hall: ¶ 007; Col. 6, Lns. 34-39; Controller 10 hardware is an industrial grad computer having a conventional microprocessor and computer readable memory that is used to provide control for the Collision Avoidance System based upon input from sensors and operational settings. The Controller 10 then executes the control logic to activate the appropriate outputs) information related to a speed of a vehicle approaching a crosswalk through a roadway and a separation distance between the vehicle and the crosswalk; (Hall: ¶ 020; Col. 4, Lns. 20-23; independently monitor each lane of traffic with speed detection devices that have a direct line-of-sight to approaching vehicles.) issuing, by the controller, a first warning to the vehicle in response that the speed of the vehicle is equal to or greater than a first reference speed and the separation distance between the vehicle and the crosswalk is a first separation distance; (Hall: ¶ 049; Cols. 15, Lns. 52-55; Authorities can limit and enforce a maximum vehicle speed, even in the absence of a pedestrian. This is accomplished by setting the Controller 10 to also respond to Conditional Control 40 sensors 40a for speed control) (Hall: ¶ 047; Cols. 15, Lns. 21-34; Controller 10 illuminates a System Status Alarm 70 display 70b in direct view of the driver, to inform of the pedestrian's presence. . . . Conditional Control 40 is provided by a sensor 40a that is used to detect the presence of a vehicle traveling in the direction of the intersection) (Hall: ¶ 047; Cols. 15, Lns. 32-34; ground-mounted induction loop)
issuing, by the controller, a second warning to the vehicle in response that the speed of the vehicle is equal to or greater than a second reference speed lower than the first reference speed (Hall: ¶ 022; Cols. 10, Lns. 12-28; authorities can set the threshold of the Trigger Sensors 30 required to invoke a system response, set the degree of activation response for Vehicle Restrictors 20, set the threshold and duration of camera response, or change the System Status Alarm 70 message for visual display . . . These parameters are unique to a particular implementation and they are the levels that a monitored object has to reach before a certain system response is invoked or changed) (Hall: ¶ 027; Cols. 11, Lns. 4-6; Trigger Sensors 30a, 30b, 30c in FIG. 2 are speed detection sensors such as the radar or laser device) and the separation distance between the vehicle and the crosswalk is a second separation distance shorter than the first separation distance after issuing the first warning; and (Hall: ¶ 047; Cols. 15, Lns. 17-25, 31-34; As the pedestrian and the vehicle advanced toward the same intersection, the Trigger Sensor 30a notifies the Controller 10 to activate the Vehicle Restrictors 20, to provide an indication to the operator to slow down. Additional reinforcement is provided when the Controller 10 illuminates a System Status Alarm 70 display 70b in direct view of the driver, to inform of the pedestrian's presence. The system can also activate an alarm 70c directed at the pedestrian to alert him to his impending collision with the vehicle . . . Conditional Control 40 is provided by a sensor 40a that is used to detect the presence of a vehicle traveling in the direction of the intersection such as one or more ultrasonic sensors. (A ground-mounted induction loop would also suffice.))
Hall does not explicitly teach: controlling, by the controller, a robot of the crosswalk safety system, to move between the vehicle and a pedestrian crossing the crosswalk. . . performing, by the controller, machine learning on an operation of the robot; . . .; however, Lee does teach:
controlling, by the controller, a robot of the crosswalk safety system, to move between the vehicle and a pedestrian crossing the crosswalk (Lee: ¶ 064; drivable area P represents a range in which the safe companion robot 100a can drive, and preferably may be a rectangular area having vehicle stop lines 300a and 300b of both lanes as rims.) . . . performing, by the controller, machine learning on an operation of the robot; . . . (Lee: ¶ 072; companion robot 100a may generate input data obtained by merging image information and LIDAR information into one, and apply the generated input data to a pre-learned second analysis model to estimate object recognition) (Lee: ¶ 019; [Fig.] 6 is a diagram for explaining the configuration of a second analysis model) (Lee: Fig. 6; [showing use of Convolutional Neural Network (CNN)]) . . .
Before the effective filling date of the claimed invention, it would have been obvious to one of ordinary skill in the art to combine the teachings of Lee with the teachings of Hall because doing so would result in the predicable benefit of “helping a pedestrian at a crosswalk [avoid] a collision with a vehicle in advance by accompanying the pedestrian to safely pass at the crosswalk" (Lee: ¶ 007) in a way that easily merges with the multi-step warning process that Hall teaches.
To the extent Hall is silent regarding or does not explicitly teach: in response that the separation distance between the vehicle and the crosswalk is less than or equal to a third separation distance shorter than the second separation distance after issuing the second warning.; however, Cho does teach:
in response that the separation distance between the vehicle and the crosswalk is less than or equal to a third separation distance shorter than the second separation distance after issuing the second warning. (Cho: ¶ 053; Col. 9, Lns. 54-61; When the electronic device 110 identifies that a distance between the vehicle 120 and the crosswalk is less than or equal to a first distance d1, or the traffic light turns on in green, the electronic device 110 may then provide a signal requesting the first indicator 400 to form the screen wall.).
Before the effective filling date of the claimed invention, it would have been obvious to one of ordinary skill in the art to combine the teachings of Cho with the teachings of Hall because doing so would result in the predicable benefit of "notifying the pedestrians of approaching vehicles or a method of controlling the speed of the vehicle approaching the crosswalk" (Cho: ¶ 004; Col. 1, Lns 30-35).
To the extent Hall is silent regarding or does not explicitly teach: performing, by the controller, machine learning on the first separation distance, the second separation distance, the third separation distance, the first reference speed, and the second reference speed; and resetting, by the controller, one or more of the first separation distance, the second separation distance, the third separation distance, the first reference speed, and the second reference speed based on a result of the machine learning; however, Neser does teach:
performing, by the controller, machine learning on the first separation distance, the second separation distance, the third separation distance, the first reference speed, and the second reference speed; and resetting, by the controller, one or more of the first separation distance, the second separation distance, the third separation distance, the first reference speed, and the second reference speed (Neser: ¶ 059; car 114e impinges on a danger zone 138 of the animal 118. The impingement may be actual or predicted, even though there has been no actual contact of the car 114e to the animal 118. This near-miss detection will cause . . . a real-time alert to warn the driver of the car 114e, or take some other action. Also in image 130, it is evident that truck 114d has entered the crosswalk 112 while pedestrian 116 is still in the crosswalk. Depending on dimensional thresholds of the danger zones 134d, 136, respectively, an alert may be logged and stored in a data storage device) based on a result of the machine learning (Neser: ¶ 064; In at least some cases, kriging algorithms perform spatial interpolation by applying weighting factors based on the calculated distance between geographic points where anchor points or danger zone boundary data has been collected. The kriging techniques model the correlation structures of the data parsed from images as a function of distance and may include information about any known covariance between the predicted separation or lack of separation between danger zone boundaries and other spatial information (co-kriging).)
Before the effective filling date of the claimed invention, it would have been obvious to one of ordinary skill in the art to combine the teachings of Neser with the teachings of Hall because doing so would result in the predicable benefit of improving the prediction accuracy of “time-based predictive dangerous conditions." (Neser: ¶ 068).
Regarding claim 19, as detailed above, combination Hall teaches the invention as detailed with respect to claim 18. Lee further teaches:
further including: controlling, by the controller, the robot to move along a movement direction of the pedestrian in an external direction of the pedestrian in a state that the pedestrian enters the crosswalk (Lee: ¶ 064; drivable area P represents a range in which the safe companion robot 100a can drive, and preferably may be a rectangular area having vehicle stop lines 300a and 300b of both lanes as rims.) (Lee: Fig. 001; [[showing robot operating between crosswalk and vehicle driving area]])
And Hall further teaches: and the second warning is not issued, wherein the external direction is a direction in which the crosswalk faces the roadway... (Hall: ¶ 069; Cols. 19, Lns. 41-45; If some incident occurs downstream from the Collision Avoidance area that eventually causes the traffic to slow below a predetermined threshold then the system will automatically adjust the merging-lane traffic light 70d as the System Status Alarm 70 and the Vehicle Restrictor 20 accordingly)
Claims 7-10 and 16-17 are rejected under 35 U.S.C. 103 as being unpatentable over combination Hall as applied to claim 1 above, and further in view of Kim (KR 20220146985 A).
Regarding claim 7, Hall does not explicitly teach:
wherein the second warning device includes a bollard member that is configured to protrude upwards from a ground.; however, Kim does teach:
wherein the second warning device includes a bollard member that is configured to protrude upwards from a ground. (Kim: ¶ 001; an AUTO safety fence structure that can be installed on both sides of a crosswalk. This AUTO safety fence is usually buried in the underground space, but when the pedestrian traffic light is turned on, it automatically rises to the ground and blocks both sides of the crosswalk like a barrier.) (Kim: ¶ 006; high-pressure steel pillar in the following figure.2 is a circular rod with a diameter of 60cm (2EA on one side, 4EA on the left and right fences) . . . safety fence can be driven by an electronic sensitive sensor power transmission program. In other words, by adopting a device and circuit diagram compatible with the electronic circuit of a walking traffic light, when a green walking signal is emitted, the interlocked electronic sensitive precision sensor operates)
Before the effective filling date of the claimed invention, it would have been obvious to one of ordinary skill in the art to combine the teachings of Kim with the teachings of Hall because doing so would result in the predicable benefit of “ensure safe walking of socially vulnerable groups such as children and the elderly who are slow to walk from drunk driving or speeding vehicle" (Kim: ¶ 001).
Regarding claim 8, as detailed above, combination Hall in view of Kim teaches the invention as detailed with respect to claim 7. Kim teaches:
wherein the bollard member includes a plurality of bollard members arranged along an extension direction in an external direction of the crosswalk in a state that a direction in which the crosswalk faces the roadway is the external direction and a direction in which the crosswalk extends is the extension direction, (Kim: ¶ 001; an AUTO safety fence structure that can be installed on both sides of a crosswalk. This AUTO safety fence is usually buried in the underground space, but when the pedestrian traffic light is turned on, it automatically rises to the ground and blocks both sides of the crosswalk like a barrier.)
Regarding claim 9, as detailed above, combination Hall in view of Kim teaches the invention as detailed with respect to claim 8. Kim teaches:
wherein the first warning device includes a light source member that emits light to issue the first warning to the vehicle, (Cho: ¶ 055; Cols. 10, Lns. 24-25; may control the indicator 500 to display at least some of the LEDs 502 in green) wherein the light source member includes a plurality of light source member arranged along the extension direction in the external direction of the crosswalk, and (Cho: Fig. 002)
And Kim teaches: wherein the bollard member is arranged in the external direction of the light source member. (Kim: ¶ 001; an AUTO safety fence structure that can be installed on both sides of a crosswalk. This AUTO safety fence is usually buried in the underground space, but when the pedestrian traffic light is turned on, it automatically rises to the ground and blocks both sides of the crosswalk like a barrier.)
Regarding claim 10, as detailed above, combination Hall in view of Kim teaches the invention as detailed with respect to claim 7. Hall teaches:
further including: a traffic light installed in an external direction of the crosswalk to transmit a traffic signal to vehicles, wherein the traffic light is arranged in the external direction of the bollard member. (Hall: Fig. 003; [[40a][20a]])
Regarding claim 16, as detailed above, combination Hall in view of Kim teaches the invention as detailed with respect to claim 9. Lee teaches:
wherein the robot is arranged in a robot movement area which is defined between the crosswalk and the light source member. (Lee: ¶ 064; drivable area P represents a range in which the safe companion robot 100a can drive, and preferably may be a rectangular area having vehicle stop lines 300a and 300b of both lanes as rims.) (Lee: Fig. 001; [[showing robot operating between crosswalk and vehicle driving area]])
Regarding claim 17, as detailed above, combination Hall in view of Kim teaches the invention as detailed with respect to claim 16. Lee teaches:
wherein the robot moves along a movement direction of the pedestrian in the external direction of the pedestrian in a state that the pedestrian enters the crosswalk (Lee: ¶ 064; drivable area P represents a range in which the safe companion robot 100a can drive, and preferably may be a rectangular area having vehicle stop lines 300a and 300b of both lanes as rims.) (Lee: Fig. 001; [[showing robot operating between crosswalk and vehicle driving area]]) and the second warning is not issued, wherein the external direction is a direction in which the crosswalk faces the roadway (Hall: ¶ 069; Cols. 19, Lns. 41-45; If some incident occurs downstream from the Collision Avoidance area that eventually causes the traffic to slow below a predetermined threshold then the system will automatically adjust the merging-lane traffic light 70d as the System Status Alarm 70 and the Vehicle Restrictor 20 accordingly)
Claims 11-15 are rejected under 35 U.S.C. 103 as being unpatentable over combination Hall in view of Kim as applied to claim 7 above, and further in view of Steinmann (CH 644418 A5).
Regarding claim 11, as detailed above, combination Hall in view of Kim teaches the invention as detailed with respect to claim 7. Hall does not explicitly teach:
wherein the second warning device includes: a rack connected to a lower side of the bollard member; a pinion engaged with the rack to move the rack up or down as the pinion rotates; and a motor operatively connected to the controller and connected to the pinion and configured to rotate the pinion.; however, Steinmann does teach:
wherein the second warning device includes: a rack connected to a lower side of the bollard member; a pinion engaged with the rack to move the rack up or down as the pinion rotates; and a motor operatively connected to the controller and connected to the pinion and configured to rotate the pinion. (Steinmann: Clm. 004; Barrier device according to claim 1, characterized in that an electric motor (13) with self-locking gearbox (14) is provided for extending and retracting the barrier post, which is mounted on the bearing frame (6) and connected to the barrier post (9) via a chain, belt or rack drive).
Before the effective filling date of the claimed invention, it would have been obvious to one of ordinary skill in the art to combine the teachings of Steinmann with the teachings of Hall because doing so would result in the predicable benefit of a bollard that "operates reliably and has a structurally simple, cost-effective design." (Steinmann: ¶ 007).
Regarding claim 12, as detailed above, combination Hall in view of Kim in view of Steinmann teaches the invention as detailed with respect to claim 11. Steinmann teaches:
wherein the second warning device further includes a stopper that protrudes from a lower end portion of the rack toward the pinion so that the stopper limits movement of the rack within a predetermined distance. (Steinmann: ¶ 035; To retract and extend the barrier post 9, an electric motor 13 with a self-locking gear 14 is provided,)
Regarding claim 13, as detailed above, combination Hall in view of Kim in view of Steinmann teaches the invention as detailed with respect to claim 12. Steinmann teaches:
wherein the stopper selectively engages with the pinion to prevent the rotation of the pinion. (Steinmann: ¶ 025; To retract and extend the barrier post 9, an electric motor 13 with a self-locking gear 14 is provided,)
Regarding claim 14, as detailed above, combination Hall in view of Kim in view of Steinmann teaches the invention as detailed with respect to claim 11. Steinmann teaches:
wherein the rack includes a guide hole extending in a longitudinal direction of the rack, and wherein the second warning device further includes a guide inserted into the guide hole to guide a vertical movement of the rack. (Steinmann: ¶ 014; barrier device with a retractable barrier post which is guided longitudinally and is releasably locked at least in its effective position, characterized in that the barrier post (9) is supported in two ways for its longitudinal guidance by means of rollers) (Steinmann: ¶ 006; At the bottom of the locking body, guide pins are arranged on its outer side, which run in longitudinal grooves of the guide tube.)
Regarding claim 15, as detailed above, combination Hall in view of Kim teaches the invention as detailed with respect to claim 7. Hall does not explicitly teach:
wherein a surface of the bollard member in an external direction includes a curved area which is convex or concave toward the external direction in a state that a direction in which the crosswalk faces the roadway is the external direction.; however, Steinmann does teach:
wherein a surface of the bollard member in an external direction includes a curved area which is convex or concave toward the external direction in a state that a direction in which the crosswalk faces the roadway is the external direction. (Steinmann: ¶ 023; barrier post could also have a round profile. In this case, profile rollers adapted to the curvature of the post would be appropriately used.).
Before the effective filling date of the claimed invention, it would have been obvious to one of ordinary skill in the art to combine the teachings of Steinmann with the teachings of Hall because doing so would result in the predicable benefit of a bollard that "operates reliably and has a structurally simple, cost-effective design." (Steinmann: ¶ 007).
Response to Arguments
Applicant's remarks filed Sep. 17, 2026 have been fully considered with respect to the previous applied 35 U.S.C. § 103 rejection but are not persuasive. Applicant argues that:
Applicant respectfully submits that Hall, Lee, Cho, Kim, Steinmann, taken individually or combined, fail to teach or suggest inventive features of the presently claimed invention including i) performing, by the controller, machine learning on an operation of the robot, ii) performing, by the controller, machine learning on the first separation distance, the second separation distance, the third separation distance, the first reference speed, and the second reference speed: and iii) resetting, by the controller, one or more of the first separation distance, the second separation distance, the third separation distance, the first reference speed, and the second reference speed based on a result of the machine learning, as is called for by claim(s) 1 and 18. Hall fails to disclose such features. Instead, Hall merely discloses an authority which may set various thresholds corresponding to operating parameters of the system, such as a response threshold of trigger sensor 30, an operating intensity of vehicle restrictor 20, a camera response threshold, a speeding threshold, a traffic-flow threshold, and a system operating-time threshold. (Applicant’s Arguments filed Sep. 17, 2026, pgs. 7-8).
Newly applied art Neser (US 20220058399 A1) teaches a system with multiple “dimensional thresholds of the danger zones” including at least one for proximity to animals and pedestrians and one for entering a crosswalk. Neser : ¶ 059. Neser further teaches using kriging algorithms to assessing and applying warning zone distinctions by “model[ing] the correlation structures of the data parsed from images as a function of distance and may include information about any known covariance between the predicted separation or lack of separation between danger zone boundaries and other spatial information.” Neser : ¶ 064. Therefore, before the effective filing date of the claimed invention, it would be obvious to one of ordinary skill in the art that Neser teaches the limitation based on the logic that Neser discloses the claimed invention except for explicitly teaching 3 static zones, but It would have been an obvious matter of design choice to use a 3 static zones in lieu of the Neser’s multiple variable zones based. Since applicant has not disclosed that the use of 3 static zones solves any stated problem or is for any particular purpose and it appears that the invention would perform equally as well implemented with variable zones in lieu of a 3 static zones. Furthermore, a person of ordinary skill in the art would find the implementation of the use of 3 static zones an obvious variation of variable zones.
Applicant also argues:
Lee merely discloses use of deep learning for recognizing the states of a vehicle and a pedestrian and for predicting a probability of collision, wherein the learning in Lee is directed to, for example, object recognition, state estimation, collision-probability prediction, and determination of a travel path. . . . In contrast, Applicant's independent claims 1 and 18 call for i) performing, by the controller, machine learning on an operation of the robot, ii) performing, by the controller, machine learning on the first separation distance, the second separation distance, the third separation distance, the first reference speed, and the second reference speed; and iii) resetting, by the controller, one or more of the first separation distance, the second separation distance, the third separation distance, the first reference speed, and the second reference speed based on a result of the machine learning. In this configuration, since the controller performs machine learning with respect to the respective separation distances and reference speeds and resets an optimal distance or speed based on the learning result, it may effectively reduce the occurrence of accidents. (Applicant’s Arguments filed Sep. 17, 2026, pg. 10 (citations omitted)).
Newly applied art Nese is relied upon for the teaching of the second limitation reciting: “ii) performing, by the controller, machine learning on the first separation distance, the second separation distance, the third separation distance, the first reference speed, and the second reference speed; and iii) resetting, by the controller, one or more of the first separation distance, the second separation distance, the third separation distance, the first reference speed, and the second reference speed based on a result of the machine learning.” As explained supra Neser teaches a system with multiple “dimensional thresholds of the danger zones” that is informed by a kriging algorithm. Neser : ¶¶ 059-064. Previously applied art Lee is relied upon for the teaching of “i) performing, by the controller, machine learning on an operation of the robot.” Examiner respectfully notes that the claimed limitation contains broad language “performing machine learning” which has been interpreted to mean any form of machine learning involving the robot, which could include object recognition as taught in Lee: ¶ 064, 019, and Fig. 6.
Finally, Applicant argues that Steinmann does not disclose the above cited new limitations. Steinmann is not relied upon for the above-argued independent claim limitation, but is only applied to unargued dependent claims 11-15. Consequently, Applicant’s amendments and arguments are moot with respect to Steinmann.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure Uçar (US 20210209943 A1) which discloses a robot assembled crosswalk.
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/C.P./Examiner, Art Unit 3663
/ANGELA Y ORTIZ/Supervisory Patent Examiner, Art Unit 3663
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