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 .
To expedite the prosecution of this application, Examiner is not restricting claim(s) 44-46, and 54-70. Claim(s) 44-46, and 54-57 does not have the unity of invention with claim(s) 58-70, in this application. Further amendments to claim(s) 44-46, and 54-70 or their dependent claims, and arguments directed to mutually exclusive limitations, may force the US Patent Office, to issue claim restriction, in an effort to establish the unity of invention, in the subsequent Office action. Applicant is kindly requested to claim the same subject matter in at least each of the independent claims.
Per the 2019 (PEG) guidance, claim(s) 44, 58, and 69 were reviewed for abstract idea. Claim(s) 58 and 69 can be streamlined to determine the subject matter eligibility, and the eligibility of the claims is “self-evident.” Claim(s) 44 passes the subject matter eligibility requirement at step 2a prong 2, “practical application.”
Claims 44 and 58 are objected for minor informality. Applicant is kindly requested to amend the terms “and/or” to either “and” or “or.”
IDS filed on 10/10/2024 has been considered along with the search report.
Specification
Amendments to the specification filed on 10/10/2024 are accepted and entered.
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.
Claim(s) 44-46, and 54-57 are rejected under 35 U.S.C. 103 as being unpatentable over Lau (US 2019/0333387 A1), in view of Cho (US 2020/0207338 A1), and further in view of Woolley (US 20190178672 A1).
Consider claim 44, Lau discloses a method of selectively alerting a vulnerable road user of safety risks, Lau discloses “a cooperative intelligent traffic system between bicycles, motorcycles, and other vehicles. Sensor data from mobile devices and other sensor devices associated with the vehicle can be sent to an edge network computing device (e.g., a multi-access edge computing device) and be processed at the edge network to identify threats, hazards or performance recommendations (speed, heartrate, pulse, cadence), and then transmit the threat assessment data to other bicycles, motorcycles, and vehicles nearby.” See ¶ 0017, comprising:
receiving, from a plurality of data sources, safety-related data, wherein the plurality of data sources comprises one or more sensors (sensor device 202) and a remote data source (network node 206), Lau discloses, "In system 200, a sensor device 202 associated with a bicycle or other vehicle can send sensor data to a multi-access edge computing device 208 associated with a network node 206. The multi-access edge computing device 208 can analyze the sensor data and send the results of the analysis to UE 204 associated with another bicycle or vehicle."; See ¶ 0039
generating, by a processing element (multi-access edge computing device 208), an environmental model of an environment around the vulnerable road user based on the safety-related data, Lau discloses, "The sensor data about the hazard 210 can be sent to the MEC device 208 which analyzes the data in order to determine a threat assessment or determine whether an alert should be sent to UE 204. The assessment or alert data can be sent to UE 204 which enables the rider operating the bicycle associated with UE 204 to dodge, avoid, or otherwise be alerted to the presence of hazard 210." See ¶ 0041; Lau discloses, "The multi-access edge computing device 208 can determine the location of the sensor device 202 based on either network location services or based on GPS data received from the sensor device in order to plot and/or otherwise record the location of the hazard 210. The location can be used to superimpose the hazard on an augmented reality display associated with UE 204 to provide the rider with a view of where the hazard is. The location can also be used to select the UE 204 from among a group of UEs. For instance, if there are multiple bicycles trailing the first bicycle associated with the sensor device 202, but they are spread out, the MEC device 208 can determine the location of the hazard and the location and traveling direction of the other bicycles (via their respective UEs) and then select to which UE to send the alert based on the relevance of the alert to each UE device. For example, if the UE 204 is trailing directly behind the sensor device 202, then the alert for the hazard 210 is particularly relevant, but if another UE, also trailing behind, but some distance to the side of the sensor device 202, may not require the warning." See ¶ 0045,
analyzing simultaneously, by the processing element, the safety-related data received and modeled in the environmental model to identify one or more safety risks or threats, Lau discloses, “sensor device 202 can include one or more accelerometers that determine the location of the hazard 210 based on detecting sudden changes in movement, either side to side, or braking, or accelerating, and send the accelerometer data to the MEC device 208. The MEC device 208 can determine the level of threat based on the acceleration levels. For instance, if the acceleration is above a predetermined threshold, the MEC device 208 can determine that a threat exists, and send an alert to the UE 204.” See ¶ 0042;
determining, by the processing element, whether the one or more safety risks or threats includes a high risk and/or a close proximity risk, Lau discloses, "In the embodiment shown in FIG. 5, a paceline or peloton of bicyclists can be sending sensor data to a MEC device 508 and receive threat assessment data or other relevant information back from the MEC device 508. As an example, the MEC device 508 can receive sensor data from riders at the front of the paceline (e.g., rider 502) and send the threat assessment data to riders to the rear (e.g., riders 504 and 506). Similarly, the MEC device 508 can also receive sensor data from rider 504 and provide threat assessment data based on the sensor data from rider 504 to rider 506.” “As the paceline changes, as rider 502 moves from the front to the back and rider 504 moves to the front, the MEC device 508 can detect these changes and adjust which sensor data is analyzed and delivered to the appropriate riders. For example, as rider 502 moves to the back, their sensor data is not as relevant as the sensor data from rider 504, and so MEC device 508 can primarily analyze sensor data from rider 504 to deliver threat assessments to riders 506 and 502." See ¶ 0052 and 0053; and
when the one or more safety risks or threats includes the high risk and/or the close proximity risk, transmitting, by the processing element, to the vulnerable road user via a user interface or other alerting mechanism an alert comprising information about the high risk and/or the close proximity risk, Lau discloses, "For example, as rider 502 moves to the back, their sensor data is not as relevant as the sensor data from rider 504, and so MEC device 508 can primarily analyze sensor data from rider 504 to deliver threat assessments to riders 506 and 502. The threat assessment data provided by MEC 508 can also include information about the path and other maneuvers by riders near the front to riders at the back, and does not have to relate to road obstructions or hazards. This can enable riders at the back to anticipate changes in directions to avoid accidents and other similar events. The threat assessment data can also include information about bicycle accidents near the front, as sensor data can be analyzed by MEC device 508 to detect accidents (sudden loss in speed, large acceleration etc.), and riders near the rear can be alerted to these accidents (audible message/tone, visual warning, augmented reality warning, etc.)." See ¶ 0053 and 0054.
With respect to wherein the environmental model (i) classifies each safety-related data as one of long-term, temporary, or dynamic and (ii) maps the classified safety-related data to a map layer, wherein long-term means that the safety-related data does not change during the vulnerable road user's travel, and, in an analogous art, Cho teaches, “map updating device 300 includes a sensor data reception module 310, an obstacle detection module 320, an obstacle classification module 330, a confidence value calculation module 340, a map updating module 350, and a memory 360.” See ¶ 0087, Cho teaches, “The obstacle classification module 330 classifies the detected obstacles according to a predetermined criterion on the basis of the obstacle information OI. Meanwhile, as indicated with a dotted line in FIG. 3, the map updating device 300 may not include the sensor data reception module 310 and the obstacle detection module 320. In this case, the obstacle classification module 330 receives the obstacle information OI from the outside. For example, the autonomous valet parking apparatus 50 detects an object around the autonomous valet parking apparatus 50 and determines whether the detected object is an obstacle that is not present on the stored map on the basis of the map stored in the autonomous valet parking apparatus 50.” See ¶ 0097, Cho teaches, “The obstacle classification module 330 determines whether the detected obstacle is a permanent obstacle, a semi-permanent obstacle, or a temporary obstacle.” See ¶ 0099, Cho teaches, “the map updating module 350 updates the obstacles on the map further on the basis of the obstacle information OI and the obstacle type information OCI.” See ¶ 0111.
It would have been obvious to one of ordinary skilled in the art at the time of invention (effective filing date for AIA application) to modify the invention of Lau and classify and store/update the obstacles as “permanent obstacle, a semi-permanent obstacle, or a temporary obstacle” and a mapped database, as suggested by, Cho, in an effort to allow other road users to warn of the updated obstacles on the road.
at least one of the temporary or dynamic safety-related data is from the one or more sensors (210), Cho teaches, “sensor 210 monitors the surroundings of the autonomous valet parking apparatus 50. According to embodiments, the sensor 210 measures the distance between the autonomous valet parking apparatus 50 and a specific object or detects a nearby object. For example, the sensor 210 includes at least one of the sensors selected from among an ultrasonic sensor, a RADAR sensor, a LIDAR sensor, a camera, an infrared sensor, a thermal sensor, and a millimeter wave sensor. The sensor 210 transmits data resulting from sensing or measurements to the transceiver 220 or to the vehicle controller 240.” See ¶ 0036 and 0037.
wherein at least one of the long-term safety-related data is from the remote data source, Cho teaches, “For example, software can be transferred from a website, server or other remote sources through a cable or over a wireless channel. Examples of the cables include coaxial cable, fiber optic cable, twisted pair cable, and digital subscriber line (DSL). Examples of the wireless channel include infrared frequency waves, radio frequency waves, and ultrahigh frequency waves” See ¶ 00129. In an analogous art, Woolley teaches, “The computing apparatus automatically updating a stored cyclist profile, stored in a system database, for the cyclist using the cycling profile data. The computing apparatus receives a routing request to provide a route for the cyclist, the request including start location data and destination location data; responsive to receiving the routing request, the computing apparatus accesses the stored cyclist profile within the system database. The computing apparatus then personalizes route data for an automatically calculated route for the cyclist, using the stored cyclist profile.” See abstract, Woolley teaches, “generate the route data 132 and ETA data 134, the routing engine 118, in addition to receiving information from the consumer device 104 and provider device 108, has access to a map database 120, a place database 126, a history database 128, and a user database 136. The map database 120 contains records for transportation infrastructure (e.g., data reflecting a road network, rail network, or other transportation route network). In one embodiment, the map database 120 may include OpenStreetMap (OSM) data or other proprietary road network data.” See ¶ 0049, Woolley teaches, “Responsive to a determination at decision block 1408 that the particular segment is not safe for bicycles, or has a prohibition on bicycles, an appropriate value may be attributed to the approved/prohibited identifier 236 to flag the relevant segment as being either allowed for (block 1414) or prohibited from (block 1410) future inclusion within the route data 132 for cyclists. Further, at block 1412, the routing engine 118 issues a communication to a cyclist in real-time, responsive to an observed usage of the route segment. This communication includes a warning to the cyclist regarding the safety of the segment, or the express prohibition on bicycle traffic on the segment.” See ¶ 00160.
It would have been obvious to one of ordinary skilled in the art at the time of invention (effective filing date for AIA application) to modify the combination of Lau- Woolley and classify and store/update the obstacles as “permanent obstacle,” and a remote mapped database, as suggested by, Woolley, in an effort to allow other road users to warn of the updated obstacles on the road segment.
Consider claim 45, the method of claim 44, wherein the remote data source is a third-party application or database comprising map data, Woolley teaches, “the routing engine 118, in addition to receiving information from the consumer device 104 and provider device 108, has access to a map database 120, a place database 126, a history database 128, and a user database 136. The map database 120 contains records for transportation infrastructure (e.g., data reflecting a road network, rail network, or other transportation route network). In one embodiment, the map database 120 may include OpenStreetMap (OSM) data or other proprietary road network data. In one embodiment, the routing engine 118 may include an Open Source Routing Machine (OSRM) engine or any one of several other proprietary routing engines.” See ¶ 0049
Consider claim 46, the method of claim 44, further comprising, determining, by the processing element, a safe route based on a current location of the vulnerable road user, destination data received from the vulnerable road user, and the environmental model, wherein the safe route minimizes safety risks or threats encountered, See Lau ¶ 0017, See Woolley ¶ 00160.
Consider claim 54, the method of claim 44, wherein determining, by the processing element, the at least one high risk is based on at least one of a relative speed, size, location, or type of the one or more safety risks or threats, See Lau ¶ 0017, ¶ 0042, ¶ 0051. See Woolley ¶ 00160
Consider claim 55, the method of claim 44, wherein the one or more sensors comprise radar, and the safety-related data received from the radar comprises first data related to a position and relative speed of an object, See Lau ¶ 0017, and See Cho ¶ 0036.
Consider claim 56, the method of claim 55, wherein the plurality of data sources comprise a safety device coupled to a light mobility vehicle, the safety device comprising a C- V2X module, wherein the safety-related data received from the C-V2X module comprises second data related to a position and relative speed of the object, and wherein the method further comprises comparing the first data and the second data to generate more accurate safety-related data related to a position and relative speed of the object, Cho teaches, “The transceiver 220 exchanges data with the infrastructure 100. This communication is called vehicle-to-infra V2I) communication. This communication is called “vehicle to infra (V2I)” communication. The transceiver 220 communicates the data with other vehicles. This communication is called vehicle-to-vehicle (V2V) communication. The V2I communication and the V2V communication are collectively called vehicle-to-everything (V2X) communication.” See ¶ 0038.
Consider claim 57, the method of claim 44, wherein the remote data source comprises a system database and the long-term safety-related data from the system database comprises trend data related to a high risk collision area or a location of a road hazard, See Lau ¶ 0051, See Woolley ¶ 00160.
Claim(s) 58-70 are rejected under 35 U.S.C. 103 as being unpatentable over Lau (US 2019/0333387 A1), in view of Cho (US 2020/0207338 A1), in view of Woolley (US 20190178672 A1), and further in view of Rubin (US 2013/0282277 A1).
Consider claim 58, a safety device for a light mobility vehicle (110/112), comprising: a housing (202) configured to couple to the light mobility vehicle, Lau teaches, “sensor device 202 can be a mobile phone or other device equipped with one or more sensors. In some embodiments, the sensor device 202 can be communicably coupled to a mobile device that transmits the sensor data to the MEC device 208 via the network node 206. In some embodiments, the sensor device 202 can be mounted on the bicycle, worn by the rider of the bicycle, or otherwise mounted on or carried by the rider.”;
a connectivity module (transmitter) positioned within the housing, the connectivity module configured to exchange safety-related data with at least one compatible connectivity device associated with at least one entity, Lau teaches, “the sensor device 202 can be communicably coupled to a mobile device that transmits the sensor data to the MEC device 208 via the network node 206.” See ¶ 0040; and
With respect to, a processing element positioned within the housing and in communication with the connectivity module and with one or more sensors, wherein the processing element is configured to: receive, from a plurality of data sources, a plurality of safety-related data, wherein the plurality of data sources includes at least the connectivity module and the one or more sensors; analyze the plurality of safety-related data simultaneously to determine one or more safety risks; determine whether the one or more safety risks includes a high risk and/or a close proximity risk that requires action; when the one or more safety risks includes the high risk and/or the close proximity risk that requires action, selectively transmit at least one alert related to the high risk and/or the close proximity risk that requires action, See rejection of claim 44;
when the one or more safety risks does not include the high risk or the close proximity risk that requires action, determine whether to selectively transmit at least one alternative alert that alerts the recipient of a lower risk and/or a distant risk, Lau teaches, “The sensor data about the hazard 210 can be sent to the MEC device 208 which analyzes the data in order to determine a threat assessment or determine whether an alert should be sent to UE 204. The assessment or alert data can be sent to UE 204 which enables the rider operating the bicycle associated with UE 204 to dodge, avoid, or otherwise be alerted to the presence of hazard 210.” See ¶ 0041; Lau teaches, “The MEC device 208 can perform image analysis to try and recognize whether there is an obstruction, what type, and then provide the appropriate feedback to the UE 204. If the sensor device 202 detects a movement, but then the MEC device 208 does not recognize any road obstruction, the MEC device 208 may determine not to send any alert to the UE 204… it may send an alert or notification that is a weak alert. If an object is recognized as an obstruction, the alert or notification can be a strong alert. Weak alerts and strong alerts can be color coded, different pitches, shapes, or have other variations to alert the rider associated with UE 204 to the confidence of the alert or notification.” See ¶ 0044.
wherein selectively transmitting the at least one alert limits a number of alerts sent to a recipient, Lau teaches, “The MEC device 208 can perform image analysis to try and recognize whether there is an obstruction, what type, and then provide the appropriate feedback to the UE 204. If the sensor device 202 detects a movement, but then the MEC device 208 does not recognize any road obstruction, the MEC device 208 may determine not to send any alert to the UE 204… it may send an alert or notification that is a weak alert. If an object is recognized as an obstruction, the alert or notification can be a strong alert. Weak alerts and strong alerts can be color coded, different pitches, shapes, or have other variations to alert the rider associated with UE 204 to the confidence of the alert or notification.” See ¶ 0044, in an analogous art, Rubin teaches, “Risk Determination” “risk value should be on a scale with human-understandable meanings. It is important that the "false warning" rate of a V2V system not be excessive, or drivers will become annoyed and turn it off. It is important that drivers understand the decisions of their V2V system and so come to trust it.” See ¶ 0405, Rubin teaches, “the final risk values of one and two is that the value of two implies a more comprehensive situational assessment; and thus communicates a higher confidence level than a value of one.” See ¶ 0406, Rubin teaches, “the driver warning threshold and automatic vehicle response thresholds should be subject to both minimums and maximums. Exceeding maximum values diminishes or the effective value of the aggregate V2V system. Below minimum values produces a large number of false or unnecessary warnings, not only diminishing the value of the system, but also creating negative impressions of V2V.” See ¶ 0446
It would have been obvious to one of ordinary skilled in the art at the time of invention (effective filing date for AIA application) to modify the combination of Lau-Cho-Woolley and limit the number of alert that “not only diminishing the value of the system, but also creating negative impressions of V2V” as suggested by Rubin.
Consider claim 59, the safety device of claim 58, wherein the one or more sensors are positioned within the housing or coupled to the housing, See Lau ¶ 0039.
Consider claim 60, The safety device of claim 58, wherein the one or more sensors are coupled to the light mobility vehicle, See Lau ¶ 0039.
Consider claim 61, The safety device of claim 58, wherein the connectivity module is a C-V2X chip, See Cho ¶ 0038.
Consider claim 62, The safety device of claim 61, wherein the one or more sensors comprise radar, See ¶ 0036 and 0037.
Consider claim 63, The safety device of claim 62, wherein the one or more sensors further comprise a camera coupled to the radar, wherein the processing element is further configured to: receive similar safety-related data from the camera and the radar; Cho teaches, “sensor 210 monitors the surroundings of the autonomous valet parking apparatus 50. According to embodiments, the sensor 210 measures the distance between the autonomous valet parking apparatus 50 and a specific object or detects a nearby object. For example, the sensor 210 includes at least one of the sensors selected from among an ultrasonic sensor, a RADAR sensor, a LIDAR sensor, a camera, an infrared sensor, a thermal sensor, and a millimeter wave sensor. The sensor 210 transmits data resulting from sensing or measurements to the transceiver 220 or to the vehicle controller 240.” See ¶ 0036 and 0037.
aggregate the similar safety-related data; and analyze the aggregated similar safety-related data to determine accurate safety-related data, Rubin teaches, “The basis of some of these methods is wireless transmission by a sending vehicle of its position and speed, then the computation by a receiving vehicle of a possible collision between the transmitting vehicle and the receiving vehicle by computing the future positions of both vehicle based on the received information combined with the position and speed information of the receiving vehicle. Then, either the driver of the receiving vehicle is warned to take evasive action or evasive action is initiated by the receiving vehicle automatically.” See ¶ 0005.
Consider claim 64, The safety device of claim 58, wherein the plurality of data sources further comprise a remote server storing long-term safety-related data related to long-term safety risks, See Lau ¶ 0051, See Woolley ¶ 00160.
Consider claim 65, The safety device of claim 58, wherein selectively transmitting one or more alerts comprises flashing a light in a direction of an other entity to alert the other entity when the one or more high risks are associated with the other entity, Rubin teaches, “A driver-initiated warning may also be "automatically" generated by any emergency action, including but not limited to: using the horn, swerving, sudden braking, unusually fast acceleration, rough road surface, slippery road surface, use of dynamic traction control or anti-skid braking control, detection of an accident, deployment of airbags, or use of emergency flashers.” See ¶ 0645, and 0704.
Consider claim 66, The safety device of claim 58, wherein selectively transmitting one or more alerts comprises transmitting an audible alert or a notification on a display that is in communication with the processing element when the one or more high risks are associated with the safety device, Rubin teaches, “A driver-initiated warning may also be "automatically" generated by any emergency action, including but not limited to: using the horn, swerving, sudden braking, unusually fast acceleration, rough road surface, slippery road surface, use of dynamic traction control or anti-skid braking control, detection of an accident, deployment of airbags, or use of emergency flashers.” See ¶ 0645, and 0704.
Consider claim 67, The safety device of claim 58, wherein selectively transmitting one or more alerts comprises increasing the intensity or frequency of the one or more alerts when the one or more high risks or one or more close proximity risks are imminent, Lau teaches, “If an object is recognized as an obstruction, the alert or notification can be a strong alert. Weak alerts and strong alerts can be color coded, different pitches, shapes, or have other variations to alert the rider associated with UE 204 to the confidence of the alert or notification.” See ¶ 0044.
Consider claim 68, The safety device of claim 58, wherein determining one or more high risks or one or more close proximity risks comprises determining one or more locations of the one or more safety risks relative to the safety device, and wherein a safety risk in a path of the safety device or that will cross the path of the safety device is considered higher risk than a safety risk that is not in the path of the safety, Lau teaches, “threat assessment data provided by MEC 508 can also include information about the path” See ¶ 0054 and ¶ 0044. Cho teaches, “term “driving route” refers to a driving path along which a vehicle drives.” See ¶ 0029.
Consider claim 69, a safety device for a light mobility vehicle, comprising: a housing configured to couple to the light mobility vehicle; a connectivity module positioned within the housing, the connectivity module configured to exchange safety-related data with at least one compatible connectivity device associated with at least one entity; one or more sensors positioned within or coupled to the housing; and a processing element positioned within the housing and in communication with the connectivity module and with the one or more sensors, wherein the processing element is configured to: receive, from a plurality of data sources, safety-related data, wherein the plurality of data sources comprise the connectivity module and the one or more sensors; analyze the safety-related data received from the plurality of data sources in parallel to determine one or more safety risks; determine one or more high risks of the one or more safety risks that require action based on one or more of a size, speed, location, and type of the one or more safety risks; and selectively transmit one or more alerts or one or more messages related to the one or more high risks that require action, wherein selectively transmitting the one or more alerts or one or more messages avoids transmitting an overwhelming number of alerts or messages, See rejection of claims 44 and 58.
Consider claim 70, The safety device of claim 69, wherein the connectivity module comprises a C-V2X module and the one or more sensors comprise radar, and wherein the safety-related data received from the radar comprises a position and speed of an object relative to the safety device, and wherein the processor is further configured to determine the one or more high risks are associated with the at least one entity, and wherein selectively transmitting one or more alerts or one or more messages related to the one or more high risks comprises transmitting a message related to the one or more high risk to the at least one compatible connectivity device via the C-V2X module, See rejection of claims 44 and 58, See Cho ¶ 0038.
Conclusion
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/Omer S Khan/Primary Examiner, Art Unit 2686