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 .
This Office action is responsive to the Request for Continued Examination (RCE) filed under 37 CFR §1.53(d) for the instant application on January 30, 2026. Applicants have properly set forth the RCE, which has been entered into the application, and an examination on the merits follows herewith.
Claims 1, 8 and 15 are amended; and claims 1-20 are pending and have been considered below.
Claim Rejections - 35 USC § 101
The 101 rejection of claims 1-20 has been withdrawn pursuant to Applicant amendment.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1-20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Liu et al. (U.S. Patent No. 10,772,068).
With regard to claim 1, Liu teaches an apparatus [abstract] comprising at least one processor (Fig. 12, processor 1201) and at least one non-transitory memory (Fig. 12, memory 1203) including computer program code instructions, the computer program code instructions configured to, when executed, cause the apparatus to at least:
aggregate observations ([col. 1, lines 35-50] a probe aggregator configured to construct a trajectory including the one or more probe data points having a same session identifier; [col. 13, lines 20-65] a probe data aggregator 1305…The probe data aggregator may be configured to construct trajectories from the probe data. A trajectory may include one or more probe data points. The probe data points in the trajectory may share a same session identifier) and vehicle paths from sensor data from one or more data sources ([col. 3, lines 30-47] The server 101 may be configured to receive probe data generated by position sensors 109 from the mobile devices 107 through the network 105…the server 101 may be configured to determine a traffic estimate or a navigation instruction for a vehicle; [col. 11, lines 45-65] the communication interface 1105 may form a connection to one or more position sensors or other sensors that are external to the mobile device 107. In another example, the communication interface may form a connection between the mobile device and a vehicle. In this way, the mobile device may send and receive data to the sensors and vehicles external to the mobile device. For example, the mobile device may receive location information from a position sensor that is part of the vehicle), wherein each observation of the observations comprises an identification an object along the vehicle path and properties associated with the object ([col. 16, lines 31-46] The geographic database 103 may include road segment data records 304 (or data entities) that describe features such as road objects 304(5). The road objects 304(5) may be stored according to location boundaries or vertices. The road objects 304(5) may be stored as a field or record using a scale of values such as from 1 to 100 for type or size. The road objects 304(5) may be stored using categories such as low, medium, or high. Additional schema may be used to describe the road objects 304(5));
determine observation counts for each of the one or more data sources ([col. 2, lines 34-60] By estimating a count of mobile devices in an area, the human (or “general”) population may be estimated…estimating the mobile device count and the population based on the probe data may improve the operation of a processor calculating the estimate);
collapse aggregated vehicle paths to road topology by travel direction ([col. 10, lines 21-47] a traffic estimate or a navigation instruction may be determined based on the number of mobile devices or the population. For example, once the population or count has been determined for a particular path (e.g. a road), a traffic estimate may be determined for the road. A portion or a link of a road topology may be selected);
assign the observation counts to a nearest road topology ([col. 10, lines 21-47] The traffic classification or label may be determined based on historical data. The database may be updated with the traffic classification or label. A request for a traffic report may be received that corresponds to the link or portion of the road topology. The request may be filled by sending the traffic classification or label for the link or portion of the road topology);
project, within a digital map database ([col. 10, lines 21-45] The road topology may be stored in a database. In some cases, the road topology may be retrieved from the database; [col. 16, lines 31-46] The geographic database 103), an observation count for each of the one or more data sources along a predetermined distance unit of the road topology to form observation intervals along the road topology ([col. 10, lines 21-47] a traffic estimate or a navigation instruction may be determined based on the number of mobile devices or the population. For example, once the population or count has been determined for a particular path (e.g. a road), a traffic estimate may be determined for the road. A portion or a link of a road topology may be selected), each observation interval comprising a respective observation count ([col. 10, lines 21-47] once the population or count has been determined for a particular path (e.g. a road), a traffic estimate may be determined for the road. A portion or a link of a road topology may be selected);
iterate over the road topology using the observation intervals to establish, for lengths of the road topology, observation intervals and their respective observation counts ([col. 10, lines 48-67] A navigation instruction may be determined based on the population or mobile device count. A navigation request may be received from a vehicle or mobile device. The request may correspond to one or more links of a road topology. In some cases, the request may include a current position and a destination for the vehicle or mobile device…the population may be associated with one or more links in the road topology); and
determine a value of the sensor data based on lengths of the observation intervals and their respective observation counts ([col. 11, lines 55-66] the communication interface 1105 may form a connection to one or more position sensors or other sensors that are external to the mobile device 107. In another example, the communication interface may form a connection between the mobile device and a vehicle).
With regard to claim 2, the limitations are addressed above and Liu teaches wherein in response to the observation intervals along the road topology overlapping, the apparatus is caused to supersede an observation interval having a lower observation count with an overlapping portion of an observation interval having a higher observation count ([col. 10, lines 25-47] A traffic classification or label may be determined based on the population corresponding to the link or path. In some cases, the population or count may be compared to historical data for the path to determine whether the current traffic (e.g. the current population or number of mobile devices traversing the path) is normal, below normal, or above normal for the path).
With regard to claim 3, the limitations are addressed above and Liu teaches wherein causing the apparatus to supersede an observation interval having a lower observation count with an overlapping portion of an observation interval having a higher observation count ([col. 10, lines 25-47] A traffic classification or label may be determined based on the population corresponding to the link or path. In some cases, the population or count may be compared to historical data for the path to determine whether the current traffic (e.g. the current population or number of mobile devices traversing the path) is normal, below normal, or above normal for the path) comprises causing the apparatus to reduce a length of the observation interval having the lower observation count by a length of the overlapping portion ([col. 10, lines 25-47] the population or count may be compared to historical data for the path to determine whether the current traffic (e.g. the current population or number of mobile devices traversing the path) is normal, below normal, or above normal for the path…A request for a traffic report may be received that corresponds to the link or portion of the road topology. The request may be filled by sending the traffic classification or label for the link or portion of the road topology).
With regard to claim 4, the limitations are addressed above and Liu teaches wherein the apparatus is further caused to determine, for a respective one of the one or more data sources, a value of the sensor data provided by the respective one of the one or more data sources ([col. 3, lines 35-45] The server 101 may be configured to receive probe data generated by position sensors 109 from the mobile devices 107 through the network 105. In some cases, the probe data may be cached or collected by another device (e.g. another server or computer) before being received by the server 101. The server 101 may store the probe data on the database 103… the geographic database may store information including maps and probe data generated by the mobile devices 107 and position sensors 109).
With regard to claim 5, the limitations are addressed above and Liu teaches wherein the apparatus is further caused to provide for compensation to the respective one of the one or more data sources based on the value of the sensor data ([col. 3, lines 35-45] The server 101 may be configured to receive probe data generated by position sensors 109 from the mobile devices 107 through the network 105. In some cases, the probe data may be cached or collected by another device (e.g. another server or computer) before being received by the server 101. The server 101 may store the probe data on the database 103… the geographic database may store information including maps and probe data generated by the mobile devices 107 and position sensors 109).
With regard to claim 6, the limitations are addressed above and Liu teaches wherein causing the apparatus to collapse aggregated vehicle paths to road topology by travel direction comprises causing the apparatus to merge redundant co-directed vehicle paths ([col. 6, lines 50-65] the normalized trajectory duration may be combined with the normalized trajectory areas to normalize a trajectory on the basis of duration and area; [col. 9, lines 44-49] the area may be approximated by a combination of one or more geometric shapes. The area of the shapes may be summed to approximate the area of the trajectory area; [claim 12] wherein the probe data aggregator is configured to order the one or more data points sequentially based on the timestamps, wherein the trajectory includes the probe data points in sequential order).
With regard to claim 7, the limitations are addressed above and Liu teaches wherein in response to a respective observation interval of the observation intervals extending through an intersection, cause the apparatus to divide the respective observation count of the respective observation interval between road topology intersecting at the intersection ([col. 5, lines 12-65] the duration of each trajectory is divided by a time bin or observation duration. For example, probe data points within an hour wide observation duration are grouped into trajectories. The duration of a trajectory may be the difference in time between a timestamp of the oldest probe data point in the trajectory and the newest probe data point in the trajectory. The trajectory may be normalized by dividing the trajectory duration by the observation duration… The area 203 may be divided into one or more observation areas 601. The observation areas 601 may correspond to a block, neighborhood, city, state, or country. Additionally or alternatively, the observation areas 601 may have correspond to an area delineated by latitude and longitude. The count or number of mobile devices may be estimated within an observation area 601).
With regard to claim 8, the product claim corresponds to the apparatus claim 1, respectively, and therefore is rejected with the same rationale.
With regard to claim 9, the product claim corresponds to the apparatus claim 2, respectively, and therefore is rejected with the same rationale.
With regard to claim 10, the product claim corresponds to the apparatus claim 3, respectively, and therefore is rejected with the same rationale.
With regard to claim 11, the product claim corresponds to the apparatus claim 4, respectively, and therefore is rejected with the same rationale.
With regard to claim 12, the product claim corresponds to the apparatus claim 5, respectively, and therefore is rejected with the same rationale.
With regard to claim 13, the product claim corresponds to the apparatus claim 6, respectively, and therefore is rejected with the same rationale.
With regard to claim 14, the product claim corresponds to the apparatus claim 7, respectively, and therefore is rejected with the same rationale.
With regard to claim 15, the method claim corresponds to the apparatus claim 1, respectively, and therefore is rejected with the same rationale.
With regard to claim 16, the method claim corresponds to the apparatus claim 2, respectively, and therefore is rejected with the same rationale.
With regard to claim 17, the method claim corresponds to the apparatus claim 3, respectively, and therefore is rejected with the same rationale.
With regard to claim 18, the method claim corresponds to the apparatus claim 4, respectively, and therefore is rejected with the same rationale.
With regard to claim 19, the method claim corresponds to the apparatus claim 5, respectively, and therefore is rejected with the same rationale.
With regard to claim 20, the method claim corresponds to the apparatus claim 6, respectively, and therefore is rejected with the same rationale.
Response to Arguments
Applicant has overcome the 101 rejection as applied. Applicant also argues that the Liu reference fails to teach identifying any object along a vehicle path, and instead is concerned with an estimation of mobile device count within an observed area.
The Liu reference is still maintained as the art rejection. The Liu reference teaches an estimation of mobile device count by receiving one or more probe data points which include a location, a session identifier and a timestamp, and calculating trajectory duration for the timestamps of the one or more probe data points and determining a path of trajectory [abstract]. Liu teaches probe data that can include data points shown as circles in Figure 2. The probe data can be generated by mobile devices and may be aggregated over a geographic area for a duration [col. 4, lines 20-30]. Liu teaches that a path of a trajectory can be determined based on the location of one or more probe data points [col. 1, lines 35-60]. Liu also teaches a traffic estimate or a navigation instruction for a vehicle ([col. 11, lines 45-65]) and a mobile device can send and receive data to sensors and vehicles of the device ([col. 11, lines 45-65]). Liu states that objects can be detected (road objects) in the road that include road segment data and that they can be stored based on size as well as have location boundaries or vertices ([col. 16, lines 31-46] The geographic database 103 may include road segment data records 304 (or data entities) that describe features such as road objects 304(5). The road objects 304(5) may be stored according to location boundaries or vertices. The road objects 304(5) may be stored as a field or record using a scale of values such as from 1 to 100 for type or size. The road objects 304(5) may be stored using categories such as low, medium, or high. Additional schema may be used to describe the road objects 304(5)). Therefore a determination is made if any object along a path of a vehicle is considered in the road. Additionally, Liu teaches determining a count of the number of mobile devices in an area and how this can provide a tool for estimating the population. Estimating a count of vehicles in the area can be synonymous to determining the number of mobile devices in the area. For each data source (the mobile devices) an estimation of the number of mobile devices in the area can be considered as determining observation counts. The estimated mobile device count can determine the population count, and probe data is collected based on such, to improve the operation of a processor calculating the estimate [col. 2, lines 34-60]. Based on the mobile device count, the observation count can be determined. As such, the Liu reference provides that determination, as well as other significant language to mirror the claim language, and is therefore rejected with the same rationale. Therefore, the Examiner asserts that the Liu reference teaches the claim limitations.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Zhang et al. (US Patent No. 10,755,118) teaches a system for identifying a type of road sign for unsupervised learning of road signs using vehicle sensor data and map data.
Fowe (U.S. Patent No. 9,349,285) teaches a traffic classification system based on spatial neighbor models.
Tatsubori (U.S. 2018/0121741) teaches a system and method for moving traffic obstacle detection and characterizing system.
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/ANDREA C LEGGETT/Primary Examiner, Art Unit 2171