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 .
Drawings
The drawings were received on February 3rd 2026. These drawings are accepted.
Specification
The specification has not been checked to the extent necessary to determine the presence of all possible minor errors. Applicant’s cooperation is requested in correcting any errors of which applicant may become aware of, in the specification.
Status of the Claims
This Final action is in response to the applicant’s filing on February 3rd 2026.
Claims 1-14 are pending and examined below.
Response to Arguments
Applicant’s arguments with respect to the rejection of claims under 35 USC § 103 have been fully considered but are moot. Specifically, the Examiner agrees that Hauser does not explicitly teach; “defining a first subset of the planning nodes at which no loaded vehicle is allowed to stop … scheduling the movements of the vehicles along said predefined routes while enforcing a no- stopping condition”. Therefore, the rejection has been withdrawn; However, upon further consideration a new grond(S) of rejection is made for claim 1 over Hauser (Patent No. US20210009160A1) in view of Machida (Patent No. US11782446B2), Chen (paten No. US12626607B2) and Richardson (Patent No. US20130035978A1).
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-14 are rejected under 35 U.S.C. 103 as being unpatentable over Hauser (Patent No. US20210009160A1) in view of Machida (Patent No. US11782446B2), Chen (paten No. US12626607B2) and Richardson (Patent No. US20130035978A1).
Regarding claim 1 Hauser teaches a method of scheduling movements of a plurality of vehicles; (See Hauser paragraph 0033 and 0034;” … a vehicle assistance system takes care of managing traffic on a road network of construction or mining sites…The vehicle assistance system comprises a computer and a client device…The three vehicles from the example shown in the figures all have such a client device…”);
and- has a time-variable internal state of being either loaded or not-loaded, the method comprising; (See Hauser paragraph 0040; “At least one of generating the adaptation data and outputting the assistance signal is particularly based a vehicle category of the respective vehicle which gives knowledge about gross vehicle weight, dimensions, and/or engine power. By calculating this information in, the whole coordination gets even more precise. What can also be taken into account are vehicle state information of the vehicle(s), wherein the vehicle state information relates to at least one of an emergency state, a fuel state, a vehicle load state, a vehicle inclination state, speed state, and position state. The computer and/or the client device can be configured for obtaining the respective vehicle state information by (a) retrieving them from a database or from the respective vehicle in real time, or (b) determining them based on the identification reference of the respective vehicle, i.e. they can be retrieved from a database or they can be derived from the known planned route of the vehicle (e.g. from a loading area to a dumping area).”- (examiner notes – vehicle category of the respective vehicle which gives knowledge about gross vehicle weight, dimensions – stands for internal state of being either loaded or not-loaded )).
Hauser does not exclusively teach but Richardson teaches, defining a first subset of the planning nodes at which no loaded vehicle is allowed to stop; obtaining predefined routes of the vehicles; (See Richardson paragraph 0064; “In operation 504 of FIG. 5A, the current and/or forecast site conditions are defined and input into status determiner 220. In one embodiment, site conditions are optionally defined for system 200. As described above, site conditions can indicate whether a particular type of vehicle is better suited for a particular task on a site. For example, standard dump trucks operate well on paved or gravel roads, but are not well suited for hauling loads in muddy conditions. Instead, an articulated dump truck is typically better suited for muddy or rough terrain conditions. Thus, system 200 is configured to receive site condition data to facilitate determining the mix of vehicles of a vehicle pool at a site, as well as identifying tasks for those vehicles to perform and when those tasks should be performed. As an example, the current and/or forecast weather conditions can be defined. This can be based upon historical, or currently recorded weather data for that site. As an example of historical weather data, it can be determined that it rains at a site 30% of the period for which a particular project is scheduled”).
Both Hauser and Richardson are in the same field of scheduling and planning of vehicle routs. It would have been obvious for one ordinary skilled in the art before the effective filing date of present invention to modify Hauser a method of scheduling movements of vehicles with Richardson planning predefined routes of the vehicles based on load. No new functionality would arise from the combination and the combination would improve usability of Hauser by adding a planning predefined routes of the vehicles based on load, which will allow better use of construction routs. Further, finding that one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Hauser does not exclusively teach but Chen teaches, and scheduling the movements of the vehicles along said predefined routes while enforcing a no-stopping condition in the first subset of the planning nodes; (See Chen column 8, line 18-22; “Intelligent Control System makes judgment based on the principle that the Shuttle driving route and speed take the shortest time duration, no stopping en route and system resources are optimal, in order to optimize the utilization rate and balance of no stopping en route…”).
Both Hauser and Chen are in the same field of scheduling and planning of vehicle routs. It would have been obvious for one ordinary skilled in the art before the effective filing date of present invention to modify Hauser a method of scheduling movements of vehicles with Chen no-stopping condition. No new functionality would arise from the combination and the combination would improve usability of Hauser by adding no-stopping condition, which will allow better movement of vehicles in the construction area. Further, finding that one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Hauser does not teach but Machida teaches, wherein each vehicle - occupies one node in a shared set of planning nodes and is movable to other nodes along edges between pairs of the nodes; (See Machida column 10, line 58-67; “The nodes corresponding to the grids in FIG. 10B represent the positions of the grids, and the arrow lines represent the adjacent relationship of the grid.Next, as shown in FIG. 10C, the nodes (a1), (c1), (a2), (b2), and (c2) are arranged for each time t=0, 1, and 2, and the same nodes and the adjacent nodes at the subsequent times are connected by edges (arrow lines). Next, the intersecting edges (dotted arrow lines) shown in FIG. 11A are converted into the graph shown in FIG. 11B using time expanded graph processing…”).
Both Hauser and Machida are in the same field of scheduling and planning of vehicle routs. It would have been obvious for one ordinary skilled in the art before the effective filing date of present invention to modify Hauser a method of scheduling movements of vehicles with Machida set of planning nodes movable to other nodes along edges. No new functionality would arise from the combination and the combination would improve usability of Hauser by adding a set of planning nodes movable to other nodes along edges, which will allow better scheduling of vehicle movement on the planned routs. Further, finding that one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Regarding claim 2 Hauser in view of Machida, Chen and Richardson teaches the method of claim 1, Hauser also teaches, further comprising: defining a second subset of the planning nodes at which no vehicle is allowed to stop, wherein the movements are scheduled while further enforcing the no-stopping condition in the second subset of the planning nodes; (See Hauser paragraph 0050; “At the problematic junctions, the system controls the right of way. For example, the heavy-duty truck has priority because it would cost a lot of time and fuel to have it stop and wait for the mid-size truck. Therefore, the system instructs the driver of the mid-size truck to slow down or to wait for a while until the heavy truck passed the crossroads. In the second case, the system could indicate to the driver of the small and speedy vehicle that if it continued to drive as it currently drives (given that it could actually drive faster because its top speed and/or the permitted speed is not reached), then there could be a conflict at the fifth-next junction. Additionally, or alternatively, the mid-size truck could be instructed to slow down a bit.”).
Regarding claim 3 Hauser in view of Machida, Chen and Richardson teaches the method of claim 2, Hauser also teaches, wherein the second subset is defined before the first subset is defined; (See Hauser paragraph 0050; “…In the second case, the system could indicate to the driver of the small and speedy vehicle that if it continued to drive as it currently drives (given that it could actually drive faster because its top speed and/or the permitted speed is not reached), then there could be a conflict at the fifth-next junction. Additionally, or alternatively, the mid-size truck could be instructed to slow down a bit.”).
Regarding claim 4 Hauser in view of Machida, Chen and Richardson teaches the method of claim 2, Hauser does not explicitly teach but Machida teaches, wherein the defining of the second subset of the planning nodes includes: analyzing the set of planning nodes and edges with respect to the number of oncoming vehicle movements each planning node blocks when the planning node is occupied; (See Machida column 11, line 10-19; “…the demand-and-supply b for which the demand of the node (g′) is set such that the sum of the demand and supply is 0 is obtained, with the node corresponding to the position of the moving object 20 at the time t=0 as the node of supply 1, and the nodes other than the node (g′) as the nodes of with supply 0. Also, the capacity u for which the capacity of each edge is 1, and the cost c for which the costs of the edges that are input to nodes (a1), (c1), (a2), (b2), and (c2) at the time t=0 are 1 and the remaining costs are 0 are obtained.”).
Both Hauser and Machida are in the same field of scheduling and planning of vehicle routs. It would have been obvious for one ordinary skilled in the art before the effective filing date of present invention to modify Hauser a method of scheduling movements of vehicles with Machida analyzing the set of planning nodes and edges with respect to the number of oncoming vehicle movements. No new functionality would arise from the combination and the combination would improve usability of Hauser by adding an analyzing the set of planning nodes and edges with respect to the number of oncoming vehicle movements, which will allow better scheduling of vehicle movement on the planned routs. Further, finding that one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Regarding claim 5 Hauser in view of Machida, Chen and Richardson teaches the method of claim 1, Hauser also teaches, wherein the defining of the first subset of the planning nodes includes: obtaining topographical information associated with the planning nodes, and analyzing the set of planning nodes and edges with respect to the operational cost of stopping and/or starting a vehicle when loaded; (See Hauser paragraph 0036; “…the computer can now generate adaptation data which are indicative for an adaptation of either: (a) a route parameter of any vehicle's route, such as a redirection, offerings of alternative route(s) or a waiting position; or (b) a driving parameter of any vehicle, such as the travel speed or the steering angle. These adaptation data are then sent to the client device which interprets them to output an assistance signal. The adaptation of the route parameter or the driving parameter can aim at reducing a risk of a potential threat (like a collision) and/or at increasing an efficiency of travel. Efficiency can be measured by time, fuel and/or load.”).
Regarding claim 6 Hauser in view of Machida, Chen and Richardson teaches the method of claim 5, Hauser also teaches, wherein the topographical information includes elevation; (See Hauser paragraph 0041; “Both detecting the expected location and detecting the expected time can be based on a slope and/or width of a road laying on the route of the vehicles. For example, in FIG. 5 (route of the mid-size truck) and FIG. 6 (route of the heavy truck) it can be seen that both vehicles need to slow down at the first road segment after the junction. The reason might be that this road goes quite steeply up or down. The light vehicle is not affected by this slope can travel with a substantially constant speed (see FIG. 4).”).
Regarding claim 7 Hauser in view of Machida Hauser in view of Machida, Chen and Richardson teaches the method of claim 1, Hauser also teaches, wherein the scheduling is performed while enforcing a rule that not-loaded vehicles shall yield to loaded vehicles; (See Hauser paragraph 0050; “At the problematic junctions, the system controls the right of way. For example, the heavy-duty truck has priority because it would cost a lot of time and fuel to have it stop and wait for the mid-size truck. Therefore, the system instructs the driver of the mid-size truck to slow down or to wait for a while until the heavy truck passed the crossroads. In the second case, the system could indicate to the driver of the small and speedy vehicle that if it continued to drive as it currently drives (given that it could actually drive faster because its top speed and/or the permitted speed is not reached), then there could be a conflict at the fifth-next junction. Additionally, or alternatively, the mid-size truck could be instructed to slow down a bit.”).
Regarding claim 8 Hauser in view of Machida, Chen and Richardson teaches the method of claim 1, Hauser also teaches, wherein the scheduling includes executing an optimization process tending to increase productivity and/or to minimize route completion time; (See Hauser paragraph 0043; “…(a) both detecting an expected location and detecting an expected time ramps, or (b) generating adaptation data can be based on a condition of the road or the junction which are on the route of the vehicles or on an efficiency evaluation of the roads. The condition can be expressed in machine-interpretable condition data and can be retrieved from a database which can be updated. For example, the drivers can input condition data in order to notify the server of new obstacles or potholes, etc. The efficiency valuations can additionally or alternatively be based on a history of speeds and/or speed variances with which other vehicles have been driving on the roads, wherein the computer is configured for storing, retrieving, or generating said evaluations. The evaluations could especially be deducted from the map generation method described in context of FIGS. 1 and 2: From these data, it can be recognised when, statistically, many vehicles drive slower than they actually could in a specific location (inefficient road), or when they can reach their top speed or the speed limit (efficient road). To find this out, knowledge about the vehicle category is again necessary to find out what are the specifics of the vehicle.”).
Regarding claim 9 Hauser in view of Machida, Chen and Richardson teaches the method of claim 1, Hauser also teaches, wherein a planning node represents a shared trafficable resource, which can be occupied by at most one vehicle at a time; (See Hauser paragraph 0033; “…a vehicle assistance system takes care of managing traffic on a road network of construction or mining sites and significantly reduces risks and increases operative efficiency. The vehicle assistance system comprises a computer and a client device. The client device is carried by a vehicle. In particular, there are at least two vehicles each carrying such a client device. At least part of the computer can be part of the client device(s). However, preferably the computer is embodied as a remote server which is wirelessly connected to the client device(s).”).
Regarding claim 10 Hauser in view of Machida, Chen and Richardson teaches the method of claim 1, Hauser does not explicitly teach but Machida teaches, wherein the edges are unidirectional; (See Machida column 10-11 line 61-2 and Figure 11A-B; “as shown in FIG. 10C, the nodes (a1), (c1), (a2), (b2), and (c2) are arranged for each time t=0, 1, and 2, and the same nodes and the adjacent nodes at the subsequent times are connected by edges (arrow lines). Next, the intersecting edges (dotted arrow lines) shown in FIG. 11A are converted into the graph shown in FIG. 11B using time expanded graph processing. Here, the time t=0, 1, and 2 is information indicating time period required for the moving object 20 to move to the next grid.”).
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Both Hauser and Machida are in the same field of scheduling and planning of vehicle routs. It would have been obvious for one ordinary skilled in the art before the effective filing date of present invention to modify Hauser a method of scheduling movements of vehicles with Machida unidirectional edges. No new functionality would arise from the combination and the combination would improve usability of Hauser by adding a unidirectional edge, which will allow better scheduling of vehicle movement on the planned routs. Further, finding that one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Regarding claim 11 Hauser in view of Machida, Chen and Richardson teaches the method of claim 1, Hauser also teaches, wherein the vehicles are autonomous; (See Hauser paragraph 0037; “… the vehicle can be… Driving fully autonomously…”).
Regarding claim 12 Hauser in view of Machida, Chen and Richardson teaches the method of claim 1, Hauser also teaches, further comprising: feeding motion commands to said plurality of vehicles for realizing the routes as scheduled; (See Hauser paragraph 0038; “The vehicle assistance system can also comprise a user interface (UI), such as a screen, a head-up-display, warning lamps, indicating lamps, a loudspeaker, or force-feedback vibration motors (e.g. in the steering wheel). The assistance signal can accordingly comprise a user interface command which is interpretable by said user interface. The user interface can then output a visual, acoustical, or haptic signal that the user understands as recommendation to adjust a driving speed and/or a steering angle in order to avoid congestion or a collision. That is, in a particular embodiment, the adaptation data which can be considered raw data are processed into the assistance signal (UI command) which can be interpreted by the UI.”).
Regarding claim 13 Hauser teaches traffic planner configured to schedule movements of a plurality of vehicles, the traffic planner comprising memory and processing circuitry configured to perform the method of claim 1 teaches by Hauser in view of Machida, Chen and Richardson (See Hauser paragraph 0043; “…The efficiency valuations can additionally or alternatively be based on a history of speeds and/or speed variances with which other vehicles have been driving on the roads, wherein the computer is configured for storing, retrieving, or generating said evaluations. The evaluations could especially be deducted from the map generation method described in context of FIGS. 1 and 2: From these data, it can be recognised when, statistically, many vehicles drive slower than they actually could in a specific location (inefficient road), or when they can reach their top speed or the speed limit (efficient road). To find this out, knowledge about the vehicle category is again necessary to find out what are the specifics of the vehicle.”).
Regarding claim 14 Hauser teaches a non-transitory computer readable medium storing a computer program comprising instructions to cause a computer to execute the steps of the method of claim 1 teached by Hauser in view of Machida; (See Hauser paragraph 0043; “…The efficiency valuations can additionally or alternatively be based on a history of speeds and/or speed variances with which other vehicles have been driving on the roads, wherein the computer is configured for storing, retrieving, or generating said evaluations. The evaluations could especially be deducted from the map generation method described in context of FIGS. 1 and 2: From these data, it can be recognised when, statistically, many vehicles drive slower than they actually could in a specific location (inefficient road), or when they can reach their top speed or the speed limit (efficient road). To find this out, knowledge about the vehicle category is again necessary to find out what are the specifics of the vehicle.”).
Conclusion
THIS ACTION IS MADE FINAL. 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 nonprovisional extension fee (37 CFR 1.17(a)) 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 mailing date of this final action.
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/L.K./Examiner, Art Unit 3666
/SCOTT A BROWNE/Supervisory Patent Examiner, Art Unit 3666
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