Response to Amendment
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1, 6-7, 11, and 13-14 is/are rejected under 35 U.S.C. 103 as being unpatentable over Raamot (US 20160027300 A1) in view of Ramamurthy et al. (US 20230316921 A1) and further in view of Jang et al. (US 20140303882 A1).
In regard to claim 1, Raamot teaches a method for delivering traffic information at an intersection by an intelligent intersection system comprising one or more environment sensors (Raamot, Fig. 1A, Trajectory sensors 120; Para. 56, The trajectory sensors may be radar (e.g., microwave), ultrasound, video camera, infrared sensors, or hybrid sensors) mounted on infrastructure at the intersection and an electronic processing device (Raamot, Fig. 1A), the method comprising: detecting via the one or more environment sensors first trajectories of a plurality of vehicles over one or more first time intervals corresponding to a first traffic light signal phase (Raamot, Para. 63, the traffic controller is run for the first time at block 304. With the traffic controller running, the traffic controller measures traffic trajectories at block 306 using, for example, the trajectory sensors described above; Fig. 1A, Trajectory sensors 120, each trajectory sensors monitors different sequence of phases; Para. 54, sequence of phases may be: phases 1&5 active at the same time, followed by phases 2&6 active at the same time, followed by phases 3&7 active at the same time, followed by phases 4&8 active at the same time, which completes a cycle (which then repeats possibly indefinitely)); detecting, via the one or more environment sensors, second trajectories of a plurality of vehicles over one or more second time intervals that do not overlap with the first time intervals, the second intervals corresponding to a second traffic light signal phase (Raamot, Fig. 1A, Trajectory sensors 120, each trajectory sensors monitors different sequence of phases; Para. 54, sequence of phases may be: phases 1&5 active at the same time, followed by phases 2&6 active at the same time, followed by phases 3&7 active at the same time, followed by phases 4&8 active at the same time, which completes a cycle (which then repeats possibly indefinitely); Para. 4, obtain, from the trajectory sensors, vehicle trajectory data associated with a plurality of vehicles approaching and traversing the intersection, the vehicle trajectory data including data regarding position, velocity, and acceleration of the plurality of vehicles; transform the vehicle trajectory data into data relative to a coordinate system derived from geometric information about the intersection stored in a memory device at the traffic controller; compute, from at least the vehicle trajectory data, a delay factor representing delay of the vehicles at the intersection, a stop factor representing a number of vehicles stopped at the intersection, a capacity of the intersection reflecting a number of vehicles per minute passing through green lights in each lane, estimated emissions of the vehicles, and a safety factor); identifying, by the electronic processing device, first paths, on the basis of a plurality of first trajectories in each case (Raamot, Para. 60, The trajectory calculator 212 can compute vehicle trajectories or a trajectory framework (described below) based on data received from trajectory sensors 220, in-road sensors 222, and adjacent intersections' traffic controllers 260. The trajectory calculator 212 may also base the trajectory information off of features of the intersection, including the geometry of the intersection, stored in a geographic information description 252 (which may be a database or the like) and/or in a trajectory framework database 254. The geographic information description 252 may include map components (such as data on the stop line, lane segment points, and the like). The geographic location of relevant attributes of the intersection may be extracted from various map data sources and stored in a geographic information description (GID) 252. This GID may then be converted by the ATMS 242 to reveal geometric constraints that will affect the vehicle trajectories as they drive through the roadway network. The geometric properties of the roadway network may be stored in a data structure referred to as the trajectory framework. This trajectory framework can include data that supports overlay of vehicle trajectory data relative to the roadway geometries, allowing modeling of past, present, and/or future vehicle trajectories relative to the traffic signalization; Para. 211, the traffic controller 210 obtains data regarding vehicle trajectories from one or more data sources. At block 804, the traffic controller 210 uses geographic information description (GID) to convert sensor data to a GID frame of reference or coordinate system. At block 806, the traffic controller 210 uses converted sensor data to calculate traffic flow parameters); identifying, by the electronic processing device, second paths on the basis of a plurality of second trajectories (Raamot, Para. 60, The trajectory calculator 212 can compute vehicle trajectories or a trajectory framework (described below) based on data received from trajectory sensors 220, in-road sensors 222, and adjacent intersections' traffic controllers 260. The trajectory calculator 212 may also base the trajectory information off of features of the intersection, including the geometry of the intersection, stored in a geographic information description 252 (which may be a database or the like) and/or in a trajectory framework database 254. The geographic information description 252 may include map components (such as data on the stop line, lane segment points, and the like). The geographic location of relevant attributes of the intersection may be extracted from various map data sources and stored in a geographic information description (GID) 252. This GID may then be converted by the ATMS 242 to reveal geometric constraints that will affect the vehicle trajectories as they drive through the roadway network. The geometric properties of the roadway network may be stored in a data structure referred to as the trajectory framework. This trajectory framework can include data that supports overlay of vehicle trajectory data relative to the roadway geometries, allowing modeling of past, present, and/or future vehicle trajectories relative to the traffic signalization; Para. 211, the traffic controller 210 obtains data regarding vehicle trajectories from one or more data sources. At block 804, the traffic controller 210 uses geographic information description (GID) to convert sensor data to a GID frame of reference or coordinate system. At block 806, the traffic controller 210 uses converted sensor data to calculate traffic flow parameters); and providing the second paths and/or second information derived from the second paths as second traffic information (Raamot, Para. 176, traffic flow parameters can be derived from highway capacity manual and other industry standardized estimates for stage 1 configuration. Under stage 2 operation, these parameters can be verified by real world measurement from the vehicle trajectories within the traffic controller 210. These real world parameters can then be fed back into to re-compute the pre-configuration data by the traffic controller 210 Configuration Generator. These assumed traffic flow parameters may include startup lost time, vehicle acceleration rate, and vehicle deceleration rate; Para. 248, the traffic controller 210 can provide a fusion of these detection inputs and other data sources into a collective set of vehicle trajectories within the GID); providing the first paths and/or first information derived from the first paths as first traffic information (Raamot, Para. 176, traffic flow parameters can be derived from highway capacity manual and other industry standardized estimates for stage 1 configuration. Under stage 2 operation, these parameters can be verified by real world measurement from the vehicle trajectories within the traffic controller 210. These real world parameters can then be fed back into to re-compute the pre-configuration data by the traffic controller 210 Configuration Generator. These assumed traffic flow parameters may include startup lost time, vehicle acceleration rate, and vehicle deceleration rate; Para. 248, the traffic controller 210 can provide a fusion of these detection inputs and other data sources into a collective set of vehicle trajectories within the GID); providing the second paths and/or second information derived from the second paths as second traffic information (Raamot, Para. 176, traffic flow parameters can be derived from highway capacity manual and other industry standardized estimates for stage 1 configuration. Under stage 2 operation, these parameters can be verified by real world measurement from the vehicle trajectories within the traffic controller 210. These real world parameters can then be fed back into to re-compute the pre-configuration data by the traffic controller 210 Configuration Generator. These assumed traffic flow parameters may include startup lost time, vehicle acceleration rate, and vehicle deceleration rate; Para. 248, the traffic controller 210 can provide a fusion of these detection inputs and other data sources into a collective set of vehicle trajectories within the GID);
Raamot does not specifically teach identifying, by the electronic processing device, first paths, on the basis of a plurality of first trajectories in each case by averaging the first trajectories over the first time intervals; and identifying, by the electronic processing device, second paths on the basis of a plurality of second trajectories by averaging the second trajectories over the second time intervals; creating an electronic interconnection map of the intersection comprising the first and second paths; identifying, within the interconnection map, one or more intersection points at which a first path and a second path intersect, each said intersection point being designated as a critical point associated with an increased risk of collision for corresponding traffic light phases; and wherein providing the first traffic information comprises providing the interconnection map including at least one said critical point as part of the first traffic information, and transmitting the first traffic information to one or more vehicles via a vehicle-to-X communication link to directly control vehicle operations.
However, Ramamurthy teaches identifying, by the electronic processing device, first paths, on the basis of a plurality of first trajectories in each case by averaging the first trajectories over the first time intervals (Ramamurthy, Para. 142, The turning paths may be determined based on stored locations of vehicles in the intersection moving from the ingress lanes 1406, 1408 to the egress lanes 1410, 1412. The paths may be generated based on nodal points and/or radii of curvature of lines (or paths) connecting the nodal points. The control module may average trajectories of the vehicles to create a set of nodes or a turning radius to determine each of the dynamic paths. The control module is configured to adjust a window duration for tracking the vehicles to determine the dynamic paths); and identifying, by the electronic processing device, second paths on the basis of a plurality of second trajectories by averaging the second trajectories over the second time intervals (Ramamurthy, Para. 142, The turning paths may be determined based on stored locations of vehicles in the intersection moving from the ingress lanes 1406, 1408 to the egress lanes 1410, 1412. The paths may be generated based on nodal points and/or radii of curvature of lines (or paths) connecting the nodal points. The control module may average trajectories of the vehicles to create a set of nodes or a turning radius to determine each of the dynamic paths. The control module is configured to adjust a window duration for tracking the vehicles to determine the dynamic paths); and transmitting the first traffic information to one or more vehicles via a vehicle-to-X communication link to directly control vehicle operations (Ramamurthy, Para. 85, The V2X map message modules may generate map messages including path information, which may be broadcast to the connected vehicles 102 and/or the VRU devices 112. V2X communication referred to herein includes transmission of map messages and other messages, such as basic safety messages and personal safety messages)
Raamot and Ramamurthy are analogous art because they both pertain to collecting vehicle trajectories at an intersection.
Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to use average vehicle trajectories to determine vehicle paths (as taught by Ramamurthy) resulting in predictable result of providing paths of vehicles on roadways and between intersections.
Combination of Raamot and Ramamurthy do not specifically teach creating an electronic interconnection map of the intersection comprising the first and second paths; identifying, within the interconnection map, one or more intersection points at which a first path and a second path intersect, each said intersection point being designated as a critical point associated with an increased risk of collision for corresponding traffic light phases; and wherein providing the first traffic information comprises providing the interconnection map including at least one said critical point as part of the first traffic information.
However, Jang teaches creating an electronic interconnection map of the intersection comprising the first and second paths (Jang, Fig. 4); identifying, within the interconnection map, one or more intersection points at which a first path and a second path intersect (Jang, Para. 68, the collision probability calculation unit 220 may select the predicted collision points using a collision matrix indicating whether there are trajectory overlaps between the vehicle trajectories of a first vehicle that enters a first access road and the vehicle trajectories of a second vehicle that enters a second access road), each said intersection point being designated as a critical point associated with an increased risk of collision for corresponding traffic light phases (Jang, Para. 76, the degree-of-collision risk calculation unit 230 may calculate a value obtained by adding the products of the vehicle turning probability and the vehicle collision probability at the predicted collision points as the degree of vehicle collision risk); and wherein providing the first traffic information comprises providing the interconnection map including at least one said critical point as part of the first traffic information (Jang, Para. 81, the collision-related information provision unit 130 may provide highly risky point information and highly risky time span information at the intersection using the intersection collision-related information corresponding to each of the vehicles that enter the intersection).
Raamot, Ramamurthy, and Jang are analogous art because they all pertain to collecting vehicle trajectories at an intersection.
Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to identify and provide the highly risky point information (as taught by Jang) allowing a user to become aware of the degree of risk in advance before the user passes through the intersection.
In regard to claim 6, Combination of Raamot, Ramamurthy, and Jang teach the method as claimed in claim 1, wherein the first time intervals and the second time intervals are assigned to a time of day and/or to a time span extending over more than one day (Raamot, Para. 251, The traffic controller 210 begins in one embodiment by determining the historic average volume per cycle for each approach. This volume can be defined as a rolling average volume taken over the prior 5 cycles (other numbers may be chosen). In the event that this data does not exist (controller restart) the average volume can be taken by averaging the approach volume for the prior 4 weeks (for example) during the same day of week and hour of day).
In regard to claim 7, Combination of Raamot, Ramamurthy, and Jang teach the method as claimed in claim 6, wherein the plurality of first time intervals are assigned to a first time of day and/or to a first time span extending over more than one day, and wherein the plurality of second time intervals are assigned to a second time of day and/or to a second time span extending over more than one day (Raamot, Para. 251, The traffic controller 210 begins in one embodiment by determining the historic average volume per cycle for each approach. This volume can be defined as a rolling average volume taken over the prior 5 cycles (other numbers may be chosen). In the event that this data does not exist (controller restart) the average volume can be taken by averaging the approach volume for the prior 4 weeks (for example) during the same day of week and hour of day).
In regard to claim 11, Combination of Raamot, Ramamurthy, and Jang teach the method as claimed in claim 1, wherein the traffic information is provided to one or more vehicles and/or to a database (Ramamurthy, Para. 85, The V2X map message modules may generate map messages including path information, which may be broadcast to the connected vehicles 102 and/or the VRU devices 112. V2X communication referred to herein includes transmission of map messages and other messages, such as basic safety messages and personal safety messages).
In regard to claim 13, Combination of Raamot, Ramamurthy, and Jang teach the method as claimed in claim 1, wherein the one or more environment sensors are cameras, radars, lidars, or contact loops (Raamot, Fig. 1A, Trajectory sensors 120; Para. 56, The trajectory sensors may be radar (e.g., microwave), ultrasound, video camera, infrared sensors, or hybrid sensors).
In regard to claim 14, Combination of Raamot, Ramamurthy, and Jang teach the method as claimed in claim 13, wherein detecting the trajectories comprises obtaining, from one or more vehicles via vehicle-to-X communication, dynamic position data for the vehicles and using said position data in detecting the first and/or second trajectories (Raamot, Fig. 2, Connected vehicles 224; Para. 59, the traffic controller 210 can receive trajectory information from connected vehicles 224 and user devices 226 of drivers or pedestrians (such as cell phones, smartphones, tablets, laptops, smart watches, other wearable computing devices, and the like; Para. 51, A vehicle's trajectory may include position, speed, or acceleration data on an approach to an intersection, within an intersection itself, or exiting the intersection).
Response to Arguments
Response to amended claims is considered above in claim Rejections.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any extension fee pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the date of this final action.
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/SHARMIN AKHTER/
Examiner, Art Unit 2689
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