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, 2, 4-8, 10-14, 16, and 18-22 are pending in this application.Claims 1, 13, and 16 are currently amended.
No claims are currently are newly presented.
No claims are currently cancelled.
Continued Examination Under 37 CFR 1.114
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 January 9, 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, 2, 4, 6-8, 10-14, 16, and 18-22 are rejected under 35 U.S.C. 103 as being unpatentable over Rubin et al. (US 20130293394 A1) in view of Shashua et al. (US 20170010618 A1 ) (the combination of which is referred to as combination Rubin hereinafter). As regards the individual claims:
Regarding claim 1, Rubin teaches a:
method for detection of a target vehicle without vehicle-to-vehicle capability, (Rubin: ¶ 024; vehicle-to-vehicle collision prevention systems and method[]) the method being performed by an electronic control unit of an ego vehicle, the method comprising: (Rubin: Clm. 001; a V2V transmitter configured to operate in a transmitting vehicle) obtaining sensor of the ego vehicle, the at least one on-board sensor being configured to sense objects within a sensing range of the at least one on-board sensor, and the sensor data indicating presence of the target vehicle within the sensing range of the at least one on-board sensor (Rubin: ¶ 159; A vehicle may be known because it is "seen" by one or more sensors, such as a video camera, radar, sonar or lidar. This latter vehicle may or may not be equipped.) determining that the target vehicle is without vehicle-to-vehicle capability by comparing the sensor data to output data from a vehicle-to-vehicle system of the ego vehicle (Rubin: ¶ 152; A key embodiment of this invention that improves effectiveness and encourages adoption is the detection of nearby non-equipped vehicles and the transmission of data about that vehicle.) (Rubin: ¶ 054; Local [to the vehicle] sensors, such as video, radar, and sonar are used by a first vehicle to determine relative speed, location and heading of a non-equipped, nearby, second, "subject" vehicle, to proxy.) (Rubin: ¶ 173; When another vehicle sends data on behalf of a different, non-transmitting vehicle we call the first vehicle the "proxy transmitter.) (Rubin: ¶172; There are a number of reasons why a vehicle in the proxy candidate list is not actually proxied. One reason is that it is properly transmitting.) (Rubin: ¶ 162; detection of nearby non-equipped vehicles [after which] the transmission of data about that vehicle [is affected]). determining based on the sensor data and on current positioning data of the ego vehicle, fusion data representing at least one of a current position, a current direction and a current speed of the target vehicle (Rubin:¶ 473; There are numerous ways to use local sensors to improve position matching, or calibration. Consider, for example, a situation with a first vehicle stopped at a light in a lane, with a second vehicle directly in front, a third vehicle directly behind and a fourth vehicle directly to the left. Using local sensors such as sonar, radar, and video, it is easy for vehicle one to compute the position of vehicles two, three and four, with respect to vehicle one, within a few cm or better. Each of these four vehicles, if equipped, is regularly transmitting the location of each respective vehicle. By comparing the V2V received locations from vehicles two, three and four and comparing these locations to the locations observed by the local sensors, it is possible to achieve with 100% confidence a one-to-one relationship between the received messages and the locally observed vehicles, even though the locations in the received messages are not precisely the observed locations of the vehicles.) wirelessly transmitting the fusion data of the target vehicle, (Rubin: ¶ 162; detection of nearby non-equipped vehicles [after which] the transmission of data about that vehicle [is effected]) using a cellular network radio technology or a wireless local area network radio technology, (Rubin: ¶ 118; implement secure gateways of V2V information over secondary, third-party, or insecure networks such as WiFi, cellular phone) . . . positioning information of the target vehicle, the positioning information of the target vehicle . . . (Rubin:¶ 473; Using local sensors such as sonar, radar, and video, it is easy for vehicle one to compute the position of vehicles two, three and four, with respect to vehicle one, within a few cm or better. Each of these four vehicles, if equipped, is regularly transmitting the location of each respective vehicle. By comparing the V2V received locations from vehicles two, three and four and comparing these locations to the locations observed by the local sensors, it is possible to achieve with 100% confidence a one-to-one relationship between the received messages and the locally observed vehicles, even though the locations in the received messages are not precisely the observed locations of the vehicles.)
However, Rubin does not explicitly teach: to a traffic information collecting center; and wirelessly receiving, at the ego vehicle from the traffic information collecting center, . . . comprising differential data specifying a difference relative to the fusion data as wirelessly transmitted by the electronic control unit; but, Shashua teaches:
to a traffic information collecting center; (Shashua: ¶ 0581; Server 2230 may receive data collected by vehicles 2201 and 2202, including landmarks (e.g., 2205 and 2206) recognized by vehicles 2201 and 2202. Data collected by vehicles 2201 and 2202 regarding landmarks may include position data (e.g., location of the landmarks), physical size of the landmarks, distances between two sequentially recognized landmarks along road segment). (Shashua: ¶ 589) from the traffic information collecting center, (Shashua: ¶ 532; [the server p]rocessor 2232 may distribute the updated autonomous vehicle road navigation model to a plurality of autonomous vehicles, such as vehicles 2201 and 2202, and other vehicles that travel along road segment 2200 at later times.) (Shashua: ¶ 616; as a vehicle travels along a particular road segment, processor 110 may access one or more local maps corresponding to the road segment being traversed. The local maps may be part of sparse data map 800 stored on a server located remotely with respect to the vehicle, and the one or more local maps may be wirelessly downloaded as needed.) comprising differential data specifying a difference relative to (Shashua: ¶ 527; Landmarks may be stored in an autonomous vehicle road navigation model or a sparse map (e.g., sparse map 800).) (Shashua: ¶ 533; identifier may include a distance of the landmark relative to another landmark. For example, the identifier associated with landmark 2206 may include a distance d from landmark 2206 to landmark 2205. The distance d is shown as a distance between landmarks 2205 and 2206 along road segment 2200.) (Shashua: Fig. 22; [showing differential data]) the fusion data as wirelessly transmitted by the electronic control unit; (Shashua: ¶ 0581; Vehicles 2201 and 2202 may both pass landmark 2206, and may measure positions of landmark 2206 and transmit the measured positions to server 2230. Server 2230 may determine a refined position of a landmark based on the measured position data of the landmarks received from vehicles 2201 and 2202. . . . The target position of landmark 2206 may be used by other vehicles later) (Shashua: ¶ 527; landmarks included in sparse data map 800 may be used for locating vehicles 2201 and 2202 (e.g., determining locations of vehicles 2201 and 2202 along a target trajectory stored in the model or sparse map). as wirelessly transmitted by the electronic control unit) (Shashua: ¶ 0581; Server 2230 may receive data collected by vehicles 2201 and 2202, including landmarks (e.g., 2205 and 2206) recognized by vehicles 2201 and 2202. Data collected by vehicles 2201 and 2202 regarding landmarks may include position data (e.g., location of the landmarks), physical size of the landmarks, distances between two sequentially recognized landmarks along road segment).
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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 Rubin with the teachings of Shashua because doing so would reduce the “sheer volume of data needed to store and update the map[s].” (Shashua: ¶ 005).
Regarding claim 2, as detailed above, combination Rubin teaches the invention as detailed with respect to claim 1. Rubin further teaches:
wherein the fusion data is wirelessly transmitted using the vehicle-to-vehicle system to another vehicle having its own vehicle-to-vehicle system (Rubin: ¶ 054; Local [to the vehicle] sensors, such as video, radar, and sonar are used by a first vehicle to determine relative speed, location and heading of a non-equipped, nearby, second, "subject" vehicle, to proxy.)
Regarding claim 4, as detailed above, combination Rubin teaches the invention as detailed with respect to claim 1. Rubin further teaches:
further comprising wherein the current positioning data of the ego vehicle is global positioning system (GPS), data (Rubin: ¶ 722-723; raw position information into the V2V transceiver comes from a local or embedded GPS receiver) and wherein the fusion data comprises GPS data representing the current position of the target vehicle (Rubin: ¶ 054; Local [to the vehicle] sensors, such as video, radar, and sonar are used by a first vehicle to determine relative speed, location and heading of a non-equipped, nearby, second, "subject" vehicle, to proxy.)
Regarding claim 6, as detailed above, combination Rubin teaches the invention as detailed with respect to claim 1. Rubin further teaches:
wherein the sensor data is obtained as combined sensor data from at least two of the on-board sensors of different type (Rubin: ¶ 474-476; [positioning] algorithm works as follows. (a) The first vehicle determines its absolute geolocation using the best means available to it, such as GPS coordinates. (b) It records the location in received messages from all vehicles in its range. (c) It makes its best determination of the relative location to itself of every vehicle within sight or sensor distance (the vehicles "in sight.") (d) It compares the data received in (b) with the data computed in (c) to map the equipped vehicles in range to the vehicles in sight, where possible. Note that not all vehicles in sight may be equipped, and vice versa. Vehicles that may be so mapped are called the "consensus building set." (e) It then compares, for each vehicle in the consensus building set, the absolute geolocation as computed in (c) with the location in the received message received in (b). (f) These differences, as determined in (e), are the offsets for each vehicle in the consensus building set. (g) All of the offsets in (f) are averaged . . . averaging is done only for vehicles whose position relative to the first vehicle may be determined by local sensors, such as radar, sonar or video. (Other sensors specifically adapted to this task may also be used, such as lidar or magnetic sensing.)) (Rubin: ¶ 482; A V2V equipped vehicle may have a lane map of high confidence. Its local vision system is able to determine the position of lane lines relative to the vehicle with high accuracy [and further applied to the above algorithm])
Regarding claim 7, as detailed above, combination Rubin teaches the invention as detailed with respect to claim 1. Rubin further teaches:
wherein the at least one on-board sensor is one or more of a radar based sensor, a camera based sensor, a Light Detection and Ranging based sensor, and an ultra high frequency radio based sensor(Rubin: ¶ 159; A vehicle may be known because it is "seen" by one or more sensors, such as a video camera, radar, sonar or lidar. This latter vehicle may or may not be equipped.)
Regarding claim 8, as detailed above, combination Rubin teaches the invention as detailed with respect to claim 1. Rubin further teaches:
wherein the positioning data of the ego vehicle comprises at least one of a current position, a current direction and a current speed of the ego vehicle (Rubin: Fig. 022; [table showing the data transmitted in a V2V message includes a current position, a current direction and a current speed])
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Regarding claim 10, as detailed above, combination Rubin teaches the invention as detailed with respect to claim 1. Rubin further teaches:
wirelessly receiving fusion data of another target vehicle from another vehicle (Rubin: ¶ 055-056; a message header indicates that a message is a proxy message being transmitted by a vehicle other than the subject vehicle [this is] a novel method to "hand off" the transmission of a proxy message from one transmitting vehicle to another transmitting vehicle.)
Regarding claim 11, as detailed above, combination Rubin teaches the invention as detailed with respect to claim 1. Rubin further teaches:
providing the fusion data as an input to at least one vehicle control system (Rubin: ¶ 428-432; camera may be used [or other sensors may be used for] observing cars sliding on a slippery road may be considered either a road condition or a traffic condition. Also road conditions include the state of fixtures such as the current or predicted state of traffic lights. . . the V2V system may now identify a vehicle about to run a stop sign or red light . . . the inclusion of collision type information in a message is generally non-required information, but information that may be helpful in creating a response [and] if a V2V system included automatic vehicle responses, those responses would be similar to the human responses)
While Rubin does not explicitly teach:
and performing vehicle control using the at least one vehicle control system and based on the fusion data; Rubin does teach:
A system where the driver can set the threshold for an automatic response to a received warning message from the system, a threshold, that once exceed, permits automatic control of the vehicle to mitigate the consequences from a predicted possible collision (Rubin: ¶ 444; drivers or owners of vehicles may select a threshold for automatic vehicle response to received risk messages. Below this threshold the vehicle will not take automatic protective, mitigation, or avoidance action. At or above this threshold, the vehicle will.)
Therefore, before the effective filing date of the claimed invention, it would be obvious to one of ordinary skill in the art that Rubin teaches the above limitation based on the logic that for Rubin's system to be able to trigger or block autonomous vehicle responses from the vehicles control system, it must be interfaced as pass the fusion system data, in some form, to the vehicle control system.
Regarding claim 12, as detailed above, combination Rubin teaches the invention as detailed with respect to claim 11. Rubin further teaches:
and/or and providing a warning indication of the target vehicle to a user interface of the ego vehicle (Rubin: ¶ 710; a large number of options exist for the V2V system to communicate with the driver, one preferred embodiment is by the use of visual indicators [for example] Red LEDs on the left or right indicates that a [target] vehicle is too close on that side)
Regarding claim 13, Rubin teaches an:
electronic control unit of an ego vehicle configured to detect a target vehicle without vehicle-to-vehicle capability, the electronic control unit comprising: (Rubin: Clm. 001; a V2V transmitter configured to operate in a transmitting vehicle) (Rubin: ¶ 162; detection of nearby non-equipped vehicles [after which] the transmission of data about that vehicle [is effected]) an obtain module configured to obtain sensor of the ego vehicle, the at least one on-board sensor being configured to sense objects within a sensing range of the at least one on-board sensor, and the sensor data indicating presence of the target vehicle within a sensing range of the at least one on-board sensor (Rubin: ¶ 159; A vehicle may be known because it is "seen" by one or more sensors, such as a video camera, radar, sonar or lidar. This latter vehicle may or may not be equipped.) a determine module configured to determine, based on determining that the target vehicle is without vehicle-to-vehicle capability (Rubin: ¶ 152; A key embodiment of this invention that improves effectiveness and encourages adoption is the detection of nearby non-equipped vehicles and the transmission of data about that vehicle.) (Rubin: ¶ 054; Local [to the vehicle] sensors, such as video, radar, and sonar are used by a first vehicle to determine relative speed, location and heading of a non-equipped, nearby, second, "subject" vehicle, to proxy.) (Rubin: ¶ 173; When another vehicle sends data on behalf of a different, non-transmitting vehicle we call the first vehicle the "proxy transmitter.) (Rubin: ¶172; There are a number of reasons why a vehicle in the proxy candidate list is not actually proxied. One reason is that it is properly transmitting.) (Rubin: ¶ 162; detection of nearby non-equipped vehicles [after which] the transmission of data about that vehicle [is affected]). and based on the sensor data and on current positioning data of the ego vehicle, fusion data representing at least one of a current position, a current direction and a current speed of the target vehicle; (Rubin:¶ 473; There are numerous ways to use local sensors to improve position matching, or calibration. Consider, for example, a situation with a first vehicle stopped at a light in a lane, with a second vehicle directly in front, a third vehicle directly behind and a fourth vehicle directly to the left. Using local sensors such as sonar, radar, and video, it is easy for vehicle one to compute the position of vehicles two, three and four, with respect to vehicle one, within a few cm or better. Each of these four vehicles, if equipped, is regularly transmitting the location of each respective vehicle. By comparing the V2V received locations from vehicles two, three and four and comparing these locations to the locations observed by the local sensors, it is possible to achieve with 100% confidence a one-to-one relationship between the received messages and the locally observed vehicles, even though the locations in the received messages are not precisely the observed locations of the vehicles.) a transmit module configured to wirelessly transmit the fusion data of the target vehicle, (Rubin: ¶ 162; detection of nearby non-equipped vehicles [after which] the transmission of data about that vehicle [is effected]) using a cellular network radio technology or a wireless local area network radio technology, (Rubin: ¶ 118; implement secure gateways of V2V information over secondary, third-party, or insecure networks such as WiFi, cellular phone)
However, Rubin does not explicitly teach:
to a traffic information collecting center; and a receive module configured to wirelessly receive positioning information of the target vehicle, the positioning information of the target vehicle comprising differential data specifying a difference relative to the fusion data as wirelessly transmitted by the electronic control unit; but, Shashua teaches:
to a traffic information collecting center; (Shashua: ¶ 0581; Server 2230 may receive data collected by vehicles 2201 and 2202, including landmarks (e.g., 2205 and 2206) recognized by vehicles 2201 and 2202. Data collected by vehicles 2201 and 2202 regarding landmarks may include position data (e.g., location of the landmarks), physical size of the landmarks, distances between two sequentially recognized landmarks along road segment). (Shashua: ¶ 589) and a receive module configured to wirelessly receive positioning information of the target vehicle, from the traffic information collecting center,(Shashua: ¶ 532; [the server p]rocessor 2232 may distribute the updated autonomous vehicle road navigation model to a plurality of autonomous vehicles, such as vehicles 2201 and 2202, and other vehicles that travel along road segment 2200 at later times.) (Shashua: ¶ 616; as a vehicle travels along a particular road segment, processor 110 may access one or more local maps corresponding to the road segment being traversed. The local maps may be part of sparse data map 800 stored on a server located remotely with respect to the vehicle, and the one or more local maps may be wirelessly downloaded as needed.) the positioning information of the target vehicle comprising differential data specifying a difference relative (Shashua: ¶ 527; Landmarks may be stored in an autonomous vehicle road navigation model or a sparse map (e.g., sparse map 800).) (Shashua: ¶ 533; identifier may include a distance of the landmark relative to another landmark. For example, the identifier associated with landmark 2206 may include a distance d from landmark 2206 to landmark 2205. The distance d is shown as a distance between landmarks 2205 and 2206 along road segment 2200.) (Shashua: Fig. 22; [showing differential data]) to the fusion data as wirelessly transmitted by the electronic control unit (Shashua: ¶ 0581; Vehicles 2201 and 2202 may both pass landmark 2206, and may measure positions of landmark 2206 and transmit the measured positions to server 2230. Server 2230 may determine a refined position of a landmark based on the measured position data of the landmarks received from vehicles 2201 and 2202. . . . The target position of landmark 2206 may be used by other vehicles later) (Shashua: ¶ 527; landmarks included in sparse data map 800 may be used for locating vehicles 2201 and 2202 (e.g., determining locations of vehicles 2201 and 2202 along a target trajectory stored in the model or sparse map). as wirelessly transmitted by the electronic control unit) (Shashua: ¶ 0581; Server 2230 may receive data collected by vehicles 2201 and 2202, including landmarks (e.g., 2205 and 2206) recognized by vehicles 2201 and 2202. Data collected by vehicles 2201 and 2202 regarding landmarks may include position data (e.g., location of the landmarks), physical size of the landmarks, distances between two sequentially recognized landmarks along road segment).
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 Rubin with the teachings of Shashua because doing so would reduce the “sheer volume of data needed to store and update the map[s].” (Shashua: ¶ 005).
Regarding claim 14, as detailed above, combination Rubin teaches the invention as detailed with respect to claim 1. Rubin further teaches:
wherein the fusion data is wirelessly transmitted using the vehicle-to-vehicle system to another vehicle having its own vehicle-to-vehicle system (Rubin: ¶ 054; Local [to the vehicle] sensors, such as video, radar, and sonar are used by a first vehicle to determine relative speed, location and heading of a non-equipped, nearby, second, "subject" vehicle, to proxy.)
Regarding claim 16, Rubin teaches a:
computer program product for detection of a target vehicle without vehicle-to-vehicle capability, the computer program product comprising a non- transitory computer readable storage medium storing a computer code which, when run on processing circuitry of an electronic control unit of an ego vehicle, causes the electronic control unit to: (Rubin: Fig. 012; [showing an electronic control unit capable of running computer code and containing processing circuitry])
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obtain sensor of the ego vehicle, the at least one on-board sensor being configured to sense objects within a sensing range of the at least one on-board sensor, and the sensor (Rubin: ¶ 159; A vehicle may be known because it is "seen" by one or more sensors, such as a video camera, radar, sonar or lidar. This latter vehicle may or may not be equipped.)
While Rubin does not explicitly teach:
determine that the target vehicle is without vehicle-to-vehicle capability by comparing the sensor data to output data from a vehicle-to-vehicle system of the ego vehicle; Rubin does teach:
A system in which vehicle-based sensors detect nearby vehicles that are not transmitting their presence on a local V2V network are identified and then have their presence transmitted to other parties, but those vehicles detected by vehicle-based sensors and are transmitting their positions do not have their transmitted to other parties (Rubin: ¶ 171; vehicles in the proxy candidate list [which are identified by local sensors] that are properly transmitting are not proxied. Thus, there is minimum duplication of transmitted messages.) (Rubin: ¶ 162; detection of nearby non-equipped vehicles [after which] the transmission of data about that vehicle [is affected]).
Therefore, before the effective filing date of the claimed invention, it would be obvious to one of ordinary skill in the art that Rubin teaches the above limitation based on the logic that In order for the Rubin's teachings to be implemented, it is required that Rubin compare the list of vehicles identified by sensors with the list of vehicles transmitting because Rubin teaches treating these two categories of vehicles distinctly differently, in one case transmitting their information, in the other not transmitting their information and the only way to treat them differently is to discern which category to which they belong.
determine, based on determining that the target vehicle is without vehicle-to-vehicle capability and based on the sensor data and on current positioning data of the ego vehicle, fusion data representing at least one of a current position, a current direction and a current speed of the target vehicle (Rubin: ¶ 054; Local [to the vehicle] sensors, such as video, radar, and sonar are used by a first vehicle to determine relative speed, location and heading of a non-equipped, nearby, second, "subject" vehicle, to proxy.) (Rubin ¶ 047; situation with a first vehicle stopped at a light in a lane, with a second vehicle directly in front, a third vehicle directly behind and a fourth vehicle directly to the left. Using local sensors such as sonar, radar, and video, it is easy for vehicle one to compute the position of vehicles two, three and four, with respect to vehicle one, within a few cm or better. Each of these four vehicles, if equipped, is regularly transmitting the location of each respective vehicle. By comparing the V2V received locations from vehicles two, three and four and comparing these locations to the locations observed by the local sensors, it is possible to achieve with 100% confidence a one-to-one relationship between the received messages and the locally observed vehicles, even though the locations in the received messages are not precisely the observed locations of the vehicles.) (Rubin:¶ 473; There are numerous ways to use local sensors to improve position matching, or calibration. Consider, for example, a situation with a first vehicle stopped at a light in a lane, with a second vehicle directly in front, a third vehicle directly behind and a fourth vehicle directly to the left. Using local sensors such as sonar, radar, and video, it is easy for vehicle one to compute the position of vehicles two, three and four, with respect to vehicle one, within a few cm or better. Each of these four vehicles, if equipped, is regularly transmitting the location of each respective vehicle. By comparing the V2V received locations from vehicles two, three and four and comparing these locations to the locations observed by the local sensors, it is possible to achieve with 100% confidence a one-to-one relationship between the received messages and the locally observed vehicles, even though the locations in the received messages are not precisely the observed locations of the vehicles.) (Rubin:¶ 482; [an] embodiment where the lane-map-determined location is averaged with the location consensus location, each with 50% weighting.) (Rubin:¶ 747; embodiments of this invention are readily "wrapped" into any ISO data unit. For example, they could be sent via Ethernet or Frame Relay. They could be sent via TCP/IP. They could be sent via 802.11 wireless protocols, including 802.11a/b/g/n. They could be sent via 802.11p layer 1 and layer 2.) (Rubin:¶ 583; traffic signal controllers ("signals") listening to V2V messages of vehicle approaching the intersection, then altering its timing for improved or optimized performance) (Rubin: ¶ 732; the V2V system communicates the API via another communications protocol to another computing device. For example, Bluetooth may be used to communicate with a mobile tablet or smart phone. As another example, 802.11 WiFi may be used to communicate with a computing device outside the vehicle. This secondary communication mode for the API allows apps to run on a tablet, for example, being used by an occupant of the vehicle, where now that tablet app has access to all the V2V features and resources.)
wirelessly transmit the fusion data of the target vehicle, (Rubin: ¶ 162; detection of nearby non-equipped vehicles [after which] the transmission of data about that vehicle [is affected])
using a cellular network radio technology or a wireless local area network radio technology, (Rubin: ¶ 118; implement secure gateways of V2V information over secondary, third-party, or insecure networks such as WiFi, cellular phone)
However, Rubin does not explicitly teach:
to a traffic information collecting center; and wirelessly receive positioning information of the target vehicle, the positioning information of the target vehicle comprising differential data specifying a difference relative to the fusion data as wirelessly transmitted by the electronic control unit; but Shashua does teach:
to a traffic information collecting center; (Shashua: ¶ 0581; Server 2230 may receive data collected by vehicles 2201 and 2202, including landmarks (e.g., 2205 and 2206) recognized by vehicles 2201 and 2202. Data collected by vehicles 2201 and 2202 regarding landmarks may include position data (e.g., location of the landmarks), physical size of the landmarks, distances between two sequentially recognized landmarks along road segment). (Shashua: ¶ 589) and wirelessly receive positioning information of the target vehicle, (Shashua: ¶ 527; landmarks included in sparse data map 800 may be used for locating vehicles 2201 and 2202 (e.g., determining locations of vehicles 2201 and 2202 along a target trajectory stored in the model or sparse map). as wirelessly transmitted by the electronic control unit) the positioning information of the target vehicle comprising differential data (Shashua: ¶ 533; identifier may include a distance of the landmark relative to another landmark. For example, the identifier associated with landmark 2206 may include a distance d from landmark 2206 to landmark 2205. The distance d is shown as a distance between landmarks 2205 and 2206 along road segment 2200.) (Shashua: Fig. 22; [showing differential data]) (Shashua: ¶ 527; landmarks included in sparse data map 800 may be used for locating vehicles 2201 and 2202 (e.g., determining locations of vehicles 2201 and 2202 along a target trajectory stored in the model or sparse map)) specifying a difference relative to the (Shashua: ¶ 527; Landmarks may be stored in an autonomous vehicle road navigation model or a sparse map (e.g., sparse map 800).) (Shashua: ¶ 533; identifier may include a distance of the landmark relative to another landmark. For example, the identifier associated with landmark 2206 may include a distance d from landmark 2206 to landmark 2205. The distance d is shown as a distance between landmarks 2205 and 2206 along road segment 2200.) (Shashua: Fig. 22; [showing differential data]) fusion data as wirelessly transmitted by the electronic control unit (Shashua: ¶ 0581; Vehicles 2201 and 2202 may both pass landmark 2206, and may measure positions of landmark 2206 and transmit the measured positions to server 2230. Server 2230 may determine a refined position of a landmark based on the measured position data of the landmarks received from vehicles 2201 and 2202. . . . The target position of landmark 2206 may be used by other vehicles later) (Shashua: ¶ 527; landmarks included in sparse data map 800 may be used for locating vehicles 2201 and 2202 (e.g., determining locations of vehicles 2201 and 2202 along a target trajectory stored in the model or sparse map). as wirelessly transmitted by the electronic control unit) (Shashua: ¶ 0581; Server 2230 may receive data collected by vehicles 2201 and 2202, including landmarks (e.g., 2205 and 2206) recognized by vehicles 2201 and 2202. Data collected by vehicles 2201 and 2202 regarding landmarks may include position data (e.g., location of the landmarks), physical size of the landmarks, distances between two sequentially recognized landmarks along road segment).
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 Rubin with the teachings of Shashua because doing so would reduce the “sheer volume of data needed to store and update the map[s].” (Shashua: ¶ 005).
Regarding claim 18, as detailed above, combination Rubin teaches the invention as detailed with respect to claim 1. Rubin further teaches:
wherein the target object class information is selected from a list of target object classes including cars, lorries, trucks, motorcycles, bicycles, horses, and horse carriages (Rubin: ¶ 153; [shared] "Core information" refers generally to a vehicle's position, speed, direction and size [but] may be include[] vehicle type designation) (Rubin: Table 8; Vehicle Type [can include] private car, pickup, or van, type size 9 private vehicle, small size 10 private car, pickup, or van, large 11 motorcycle 12 limousine -- long or stretch 13 commercial pickup or van, large 14 medium size commercial truck 15 stopped medium size delivery vehicle 16 semi-tractor only 17 semi, one trailer 18 semi, two trailers 19 semi, three trailers 20 semi, oversize width 21 short bus 22 full-size bus or RV 23 emergency vehicle, small or medium 24 emergency vehicle, large 25 farm vehicle 26 oversize vehicle 27 in roadway still equipment 28 in roadway still obstruction or barrier 29 in roadway debris 30 accident 31 bicyclist 32 bicyclist, double or trailer 33 pedestrian, upright 34 pedestrian, high speed, e.g. runner 35 handicapped person, e.g. wheelchair 36 person down on roadway 37 crowd on roadway 38 event on roadway, e.g. crafts fair 39 domestic animal, e.g. guide dog 40 non-domestic animal, e.g. livestock 41 wild animal, e.g. deer 42 other tiny (size TBD) 43 other small (size TBD) 44 other medium (size TBD) 45 other large (size TBD) 46 other very large (size TBD) 47 other oversize (size TBD) 48 reserved 49-62 unknown vehicle type 63)
Regarding claim 19, as detailed above, combination Rubin teaches the invention as detailed with respect to claim 1. Shashua further teaches:
wherein the sensor data are obtained from the at least one on-board sensor, wherein a type of each of the at least one on-board sensor is other than a satellite positioning system sensor, and other than a radio (Shashua: ¶ 506; using Light Detection And Ranging (LIDAR) measurements may be used to accurately match world positions in different drives)
Regarding claim 20, as detailed above, combination Rubin teaches the invention as detailed with respect to claim 1. Shashua teaches:
wherein the differential data(Shashua: ¶ 527; Landmarks may be stored in an autonomous vehicle road navigation model or a sparse map (e.g., sparse map 800).) (Shashua: ¶ 533; identifier may include a distance of the landmark relative to another landmark. For example, the identifier associated with landmark 2206 may include a distance d from landmark 2206 to landmark 2205. The distance d is shown as a distance between landmarks 2205 and 2206 along road segment 2200.) (Shashua: Fig. 22; [showing differential data]) is determined using fusion data (Shashua: ¶ 0581; Vehicles 2201 and 2202 may both pass landmark 2206, and may measure positions of landmark 2206 and transmit the measured positions to server 2230. Server 2230 may determine a refined position of a landmark based on the measured position data of the landmarks received from vehicles 2201 and 2202. . . . The target position of landmark 2206 may be used by other vehicles later) (Shashua: ¶ 527; landmarks included in sparse data map 800 may be used for locating vehicles 2201 and 2202 (e.g., determining locations of vehicles 2201 and 2202 along a target trajectory stored in the model or sparse map). as wirelessly transmitted by the electronic control unit) for the target vehicle from the ego vehicle and from at least one other vehicle (Shashua: ¶ 0581; Server 2230 may receive data collected by vehicles 2201 and 2202, including landmarks (e.g., 2205 and 2206) recognized by vehicles 2201 and 2202. Data collected by vehicles 2201 and 2202 regarding landmarks may include position data (e.g., location of the landmarks), physical size of the landmarks, distances between two sequentially recognized landmarks along road segment)
Regarding claim 21, as detailed above, combination Rubin teaches the invention as detailed with respect to claim 13. Shashua teaches:
wherein the differential data (Shashua: ¶ 527; Landmarks may be stored in an autonomous vehicle road navigation model or a sparse map (e.g., sparse map 800).) (Shashua: ¶ 533; identifier may include a distance of the landmark relative to another landmark. For example, the identifier associated with landmark 2206 may include a distance d from landmark 2206 to landmark 2205. The distance d is shown as a distance between landmarks 2205 and 2206 along road segment 2200.) (Shashua: Fig. 22; [showing differential data]) data is based on fusion data(Shashua: ¶ 0581; Vehicles 2201 and 2202 may both pass landmark 2206, and may measure positions of landmark 2206 and transmit the measured positions to server 2230. Server 2230 may determine a refined position of a landmark based on the measured position data of the landmarks received from vehicles 2201 and 2202. . . . The target position of landmark 2206 may be used by other vehicles later) (Shashua: ¶ 527; landmarks included in sparse data map 800 may be used for locating vehicles 2201 and 2202 (e.g., determining locations of vehicles 2201 and 2202 along a target trajectory stored in the model or sparse map). as wirelessly transmitted by the electronic control unit) for the target vehicle from the ego vehicle and from at least one other vehicle (Shashua: ¶ 0581; Server 2230 may receive data collected by vehicles 2201 and 2202, including landmarks (e.g., 2205 and 2206) recognized by vehicles 2201 and 2202. Data collected by vehicles 2201 and 2202 regarding landmarks may include position data (e.g., location of the landmarks), physical size of the landmarks, distances between two sequentially recognized landmarks along road segment)
Regarding claim 22, as detailed above, combination Rubin teaches the invention as detailed with respect to claim 16. Shashua teaches:
wherein the differential data (Shashua: ¶ 527; Landmarks may be stored in an autonomous vehicle road navigation model or a sparse map (e.g., sparse map 800).) (Shashua: ¶ 533; identifier may include a distance of the landmark relative to another landmark. For example, the identifier associated with landmark 2206 may include a distance d from landmark 2206 to landmark 2205. The distance d is shown as a distance between landmarks 2205 and 2206 along road segment 2200.) (Shashua: Fig. 22; [showing differential data])is based on fusion data (Shashua: ¶ 0581; Vehicles 2201 and 2202 may both pass landmark 2206, and may measure positions of landmark 2206 and transmit the measured positions to server 2230. Server 2230 may determine a refined position of a landmark based on the measured position data of the landmarks received from vehicles 2201 and 2202. . . . The target position of landmark 2206 may be used by other vehicles later) (Shashua: ¶ 527; landmarks included in sparse data map 800 may be used for locating vehicles 2201 and 2202 (e.g., determining locations of vehicles 2201 and 2202 along a target trajectory stored in the model or sparse map). as wirelessly transmitted by the electronic control unit)for the target vehicle from the ego vehicle and from at least one other vehicle (Shashua: ¶ 0581; Server 2230 may receive data collected by vehicles 2201 and 2202, including landmarks (e.g., 2205 and 2206) recognized by vehicles 2201 and 2202. Data collected by vehicles 2201 and 2202 regarding landmarks may include position data (e.g., location of the landmarks), physical size of the landmarks, distances between two sequentially recognized landmarks along road segment)
Claims 5 is rejected under 35 U.S.C. 103 as being unpatentable over Rubin in view of Shashua as applied to claim 1 above and in further view of Gignac et al. (US 20170025001 A1). As regards the individual claims:
Regarding claim 5, combination Rubin teaches the invention as detailed with respect to claim 1. Combination Rubin does not explicitly teach:
further comprising determining, based on the sensor data, target object class information associated with the target vehicle; however, Gignac does teach:
further comprising determining, based on the sensor data, target object class information associated with the target vehicle; (Gignac: ¶ 006; An imaging device collects object imaging data representing objects within a visible detection range of the imaging device. An object detection and classification system module has an object classification sub-module used to classify the objects within the visible detection range of the imaging device as a vehicle type or a pedestrian and to output each as an object attribute data. A target fusion module receives the object attribute data from the object detection and classification system module, fuses the object attribute data with the vehicle attribute data to create the fused object attribute data, and forwards the fused object attribute data to the communication system module for transmission.) wherein the target object class information is selected from a set of target object classes each of which is associated with a label, and wherein the fusion data comprises the label of the target object class (Gignac: ¶ 043; imaging device 36 collects object imaging data 70 representing objects within a visible detection range 28 of the imaging device 36. An object detection and classification system module 54 has an object classification sub-module 64 used to classify the objects within the visible detection range 28 as a vehicle type or a pedestrian and to output each as an object attribute data 70.)
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 Rubin with the teachings of Gignac because the use of a known technique to improve similar methods in the same way is obvious (KSR Int'l Co. v. Teleflex Inc., 550 U.S. at 417, 82 USPQ2d at 1396.) In the instant case, both Rubin and Gignac’s base methods are similar methods of sharing local-area information collected by sensors and fused between vehicles to improve safety and performance; however, Gignac’s method has been improved by sharing object classification data. Before the time of filing of the claimed invention, one of ordinary skill in the art could have applied Gignac’s known improvement to Rubin using known methods and recognized that the results of the combination were predictable because each element merely performs the same function as it does separately. Further, such a combination would predictably create an expectation of advantage because it provides the most complete situational awareness to all vehicles.
Response to Arguments
Applicant’s arguments with respect to claim(s) January 9, 2026 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. Applicant argues that the:
FOA reads that "target-vehicle location data fused at Dedes's processor (A) would be differential data in that it is both (as) fused and (b) differential to the host vehicle's predicted location of the target vehicle." Id. Dedes or Rubin in view of Dedes, however, does not teach or suggest wirelessly receiving, at an ego vehicle from a traffic information collecting center, positioning information of the target vehicle, the positioning information of the target vehicle comprising differential data specifying a difference relative to the fusion data as wirelessly transmitted by the electronic control unit. Paragraphs [0016, 0017] and claim 4 discuss receiving information including GNSS carrier phases, GNSS pseudo-ranges, orientation, acceleration, radar measurements, video data, compass measurements, and inclinometer measurements, and determining position of a vehicle therefrom. The Response to Arguments of the FOA asserts that Dedes's processor fuses target-vehicle location data that is different from the host vehicle's predicted location. Dedes does not teach or suggest receiving, from a traffic information collecting center, positioning information specifying a difference relative to fusion data (including position, direction, and/or speed) transmitted to the traffic information collecting center. Determining (fusing) location data that is (happens to be) different from other data does not teach or suggest receiving positioning data, from an entity, specifying a difference relative to fusion data transmitted to that entity. For at least these reasons, independent claim 1 is patentable in view of Rubin in view of Dedes. (Applicant’s Arguments filed Jan. 6, 2026, pg. 8)
Newly applied art Shashua et al. (US 20170010618 A1 ) teaches a method of vehicle navigation where “a [s]erver 2230 may receive data collected by vehicles 2201 and 2202, including landmarks (e.g., 2205 and 2206) recognized by vehicles” (Shashua: ¶ 0581) after which the “[s]erver 2230 may determine a refined position of a landmark based on the [plurality of] measured position data of the landmarks received from vehicles 2201 and 2202” (Shashua: ¶ 0581). In other words, the server fuses a plurality of location data together to form an integrated map of fused data.
Then the “[l]andmarks may be stored in an autonomous vehicle road navigation model or a sparse map (e.g., sparse map 800) (Shashua: ¶ 527) in a format wherein each “landmark [is] relative to another landmark [such that] the identifier associated with landmark 2206 may include a distance d from landmark 2206 to landmark 2205” (Shashua: ¶ 533) which can include vehicles (Shashua: ¶ 527) as shown on Fig. 22. In other words, a map is created consisting of relative distances between the calculated fused data for each landmark wherein a vehicle can be a landmark
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These fused differential data maps “may be part of sparse data map 800 stored on a server located remotely with respect to the vehicle, and the one or more local maps may be wirelessly downloaded as needed” (Shashua: ¶ 616). In other words, the Shashua’s server is transmitting the fused differential data maps [800] to vehicles for real time navigation.
Finally, Shashua teaches that the refined “position of landmark 2206 may be used by other vehicles later” (Shashua: ¶ 0581) including that the “landmarks included in sparse data map 800 may be used for locating vehicles 2201 and 2202 (e.g., determining locations of vehicles 2201 and 2202” (Shashua: ¶ 527)
Consequently, Applicants arguments are not persuasive because Shashua teaches wirelessly receiving, at an ego vehicle from a traffic information collecting center, positioning information of the target vehicle, the positioning information of the target vehicle comprising differential data specifying a difference relative to the fusion data as wirelessly transmitted by the electronic control unit.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure Miller (US 9646496 B1) which discloses a connected traffic safety system which sends at least one of vehicle location data, direction heading data, elevation data and speed data from the OBU-equipped vehicle to a traffic signal controller generated for at least one non-Onboard Unit (OBU)-equipped vehicle. Also made of record is Al-Stouhi (US 10225717 B2) which describes “ . . . DSRC device 205 is any device capable of transmitting and/or receiving messages using the dedicated short-range communication protocol. For example, DSRC device 205 may be included in a vehicle (not shown), may be part of a cell phone or other mobile electronic device, may be part of a non-portable infrastructure device, such as a part of a toll booth, and may be part of a portable infrastructure device, such as a portable traffic conditions sign. Also made of record is Cvijetic (US 20180364366 A1) which teaches an invention that improve positioning accuracy by determining and applying relative offsets from a reference station.
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/C.P./Examiner, Art Unit 3663
/ANGELA Y ORTIZ/Supervisory Patent Examiner, Art Unit 3663
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