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 Non-final action is in response to the applicant’s filing on August 27th 2026.
Claims 1-14 are pending and examined below.
Response to Arguments
Applicant’s arguments filed on August 27th 2026 with respect to Final rejection have been fully considered and are persuasive and the final rejection has been withdrawn;
Further 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; obtaining predefined routes of the vehicles… 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… 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”. Therefore, the rejection has been withdrawn; However, upon further consideration a new grond(S) of rejection is made for claim 1 over Hauser (Patent No. US20210009160A1) in view of Wahde (“A method for real-time dynamic fleet mission planning for autonomous mining”) and Kanai (Patent No. US20230121070A1).
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 1-9 and 11-14 are rejected under 35 U.S.C. 103 as being unpatentable over Hauser (Patent No. US20210009160A1) in view of Wahde (“A method for real-time dynamic fleet mission planning for autonomous mining”) and Kanai (Patent No. US20230121070A1).
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 Wahde 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 Wahde section 3.3.1 and 6.1; “The first condition concerns the incoming missions2 aiming to reach the offloading site. When a vehicle is fully loaded, it should ideally be able to drive all the way to the offloading station … at maximum possible speed, without stopping. This is so, since the load on the gear box and engine of a fully loaded mining vehicle is typically so intense that any stop may cause mechanical failures…
two instances of this map were generated: One in which all terminals are non-prioritized (so that pause node visits are allowed for all vehicles), and one in which half of the terminals, namely those on the left side of the map, are prioritized, and the other half are non-prioritized. These two maps will be referred to as the non-prioritized map (hereafter: NPR map) and the semi-prioritized map (hereafter: SPR map), respectively. Note that, for the latter, as described in Sect. 4, half of the vehicles will be forced to move
along the shortest possible path, without any stops (except before starting the motion).”);
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 Wahde section 2, 6; “In order for a mine to operate autonomously, two crucial aspects must be considered: namely (i) multi-vehicle path planning and (ii) dynamic scheduling. The former part deals with the generation of conflict-free paths, whereas the latter is concerned with minimizing delays and waiting times… The method for dynamic fleet mission planning presented here involves both path planning and scheduling, where the latter part is of central importance… The static fleet mission planning algorithm was implemented in C# .NET and was evaluated using the map shown in Fig. 6. In fact, two instances of this map were generated: One in which all terminals are non-prioritized (so that pause node visits are allowed for all vehicles), and one in which half of the terminals, namely those on the left side of themap, are prioritized, and the other half are non-prioritized. These two maps will be referred to as the non-prioritized map (hereafter: NPR map) and the semi-prioritized map (hereafter: SPR map), respectively. Note that, for the latter, as described in Sect. 4, half of the vehicles will be forced to move along the shortest possible path, without any stops (except before starting the motion).”).
Both Hauser and Wahde 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 managing traffic of construction vehicles with Wahde subset of the planning nodes and scheduling the movements of the vehicles along said predefined routes while enforcing a no-stopping condition. No new functionality would arise from the combination and the combination would improve usability of Hauser by adding subset of the planning nodes and scheduling the movements of the vehicles along said predefined routes while enforcing a no-stopping condition, which will improve the scheduling process of 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 Kanai 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 Kanai paragraph 0045 0078 and figure 16; “…The map information 251 is provided in advance with information corresponding to sections required for the unmanned vehicle 20 to travel, and for example, an external control station or the like may set, for each unmanned vehicle 20, nodes of exclusive travel sections that prevent the unmanned vehicle 20 from interfering with another unmanned vehicle 20, and the nodes received via the wireless communication device 240 may be stored as needed… FIG. 16 illustrates a target track using an offset amount according to the load condition of the unmanned vehicle 20. In FIG. 16, the unmanned vehicle 20-1 is a vehicle (moving from the dumping place to the loading place) in the empty load state, and the unmanned vehicle 20-2 is a vehicle (moving from the loading place to the dumping place) in the loaded state. The load offset factor (i.e., the offset factor when the body weight is relatively large) is set larger than the empty-load offset factor (i.e., the offset factor when the body weight is relatively small), so that the unmanned vehicle 20 when loaded can more largely displace the target track 62 with respect to the travel path 60. In this case, it is required to set values of offset factors considering a road width and a distance to an opposite lane such that there is a sufficient distance, if offset, to the on-coming vehicle.”).
Both Hauser and Kanai 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 managing traffic of construction vehicles with Kanai node occupation and position of the vehicle along edges. No new functionality would arise from the combination and the combination would improve usability of Hauser by adding node occupation and position of the vehicle along edges, which will improve the scheduling process of 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.
Regarding claim 2 Hauser in view of Wahde and Kanai teaches the method of claim 1, Hauser does not explicitly teach but Wahde 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 Wahde section 3.3.1 and 6.1; “The first condition concerns the incoming missions2 aiming to reach the offloading site. When a vehicle is fully loaded, it should ideally be able to drive all the way to the offloading station … at maximum possible speed, without stopping. This is so, since the load on the gear box and engine of a fully loaded mining vehicle is typically so intense that any stop may cause mechanical failures…
two instances of this map were generated: One in which all terminals are non-prioritized (so that pause node visits are allowed for all vehicles), and one in which half of the terminals, namely those on the left side of the map, are prioritized, and the other half are non-prioritized. These two maps will be referred to as the non-prioritized map (hereafter: NPR map) and the semi-prioritized map (hereafter: SPR map), respectively. Note that, for the latter, as described in Sect. 4, half of the vehicles will be forced to move
along the shortest possible path, without any stops (except before starting the motion).”).
Both Hauser and Wahde 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 managing traffic of construction vehicles with Wahde subset of the planning nodes and scheduling the movements of the vehicles along said predefined routes while enforcing a no-stopping condition. No new functionality would arise from the combination and the combination would improve usability of Hauser by adding subset of the planning nodes and scheduling the movements of the vehicles along said predefined routes while enforcing a no-stopping condition, which will improve the scheduling process of 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.
Regarding claim 3 Hauser in view of Wahde and Kanai teaches the 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 Wahde and Kanai teaches the method of claim 2, Hauser does not explicitly teach but Wahde 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 Wahde section 4 and figure 3; “…in the case of a mine of the kind considered for the dynamic case (see Fig. 1), there is typically a single offloading site meaning, for example, that for inbound missions, only one vehicle can proceed directly to its primary destination, whereas the others must plan a route to a secondary target, i.e. a pause node near the offloading site. For the purpose of evaluating the performance of the static fleet mission optimization...”).
Both Hauser and Wahde 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 managing traffic of construction vehicles with Wahde subset of the planning nodes and scheduling the movements of the vehicles along said predefined routes while enforcing a no-stopping condition. No new functionality would arise from the combination and the combination would improve usability of Hauser by adding subset of the planning nodes and scheduling the movements of the vehicles along said predefined routes while enforcing a no-stopping condition, which will improve the scheduling process of 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.
Regarding claim 5 Hauser in view of Wahde and Kanai 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 Wahde and Kanai 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 Wahde and Kanai teaches the method of claim 1, Hauser does not explicitly teach but Wahde teaches, wherein the scheduling is performed while enforcing a rule that not-loaded vehicles shall yield to loaded vehicles; (See Wahde section 3.3; “…goal is to make those missions as efficient (i.e. with short duration) as possible. As for the missions, an incoming (loaded) vehicle will always have the prioritized offloading site as its primary destination (i.e. the end node of the mission)…”).
Both Hauser and Wahde 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 managing traffic of construction vehicles with Wahde subset of the planning nodes and scheduling the movements of the vehicles along said predefined routes while enforcing a no-stopping condition. No new functionality would arise from the combination and the combination would improve usability of Hauser by adding subset of the planning nodes and scheduling the movements of the vehicles along said predefined routes while enforcing a no-stopping condition, which will improve the scheduling process of 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.
Regarding claim 8 Hauser in view of Wahde and Kanai teaches the method of claim 1, Hauser does not explicitly teach but Wahde teaches, wherein the scheduling includes executing an optimization process tending to increase productivity and/or to minimize route completion time; (See Wahde section 1; “…the planning involves both determining a vehicle’s route and the duration of its motion along the route, a unit that will be collectively referred to as the trajectory of a vehicle. The planning algorithm introduced in this paper operates on topological maps, rather than metric maps. With topological maps, one can logically separate the problem of low-level vehicle control, i.e. applying control actions in order to follow a specific path, from the problem of planning the trajectory of the vehicle. Since the planning is topological, the algorithm does not specify the speed variation within a given segment (defined below). Instead, it simply specifies the total duration, which should be bounded from below by the minimum possible duration for traversing the segment in question...”).
Both Hauser and Wahde 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 managing traffic of construction vehicles with Wahde subset of the planning nodes and scheduling the movements of the vehicles along said predefined routes while enforcing a no-stopping condition. No new functionality would arise from the combination and the combination would improve usability of Hauser by adding subset of the planning nodes and scheduling the movements of the vehicles along said predefined routes while enforcing a no-stopping condition, which will improve the scheduling process of 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.
Regarding claim 9 Hauser in view of Wahde and Kanai 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 11 Hauser in view of Wahde and Kanai teaches the e 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 Wahde and Kanai 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 Wahde and Kanai; (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 teaches by Hauser in view of Wahde and Kanai; (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.”).
Claims 10 are rejected under 35 U.S.C. 103 as being unpatentable over Hauser (Patent No. US20210009160A1) in view of Wahde (“A method for real-time dynamic fleet mission planning for autonomous mining”), Kanai (Patent No. US20230121070A1) and Machida (Patent No. US11782446B2).
Regarding claim 10 Hauser in view of Wahde and Kanai 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.”).
PNG
media_image1.png
838
582
media_image1.png
Greyscale
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.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to LIDIA KWIATKOWSKA whose telephone number is (571)272-5161. The examiner can normally be reached Monday-Friday 8:00-5:00.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Scott A. Browne can be reached at (571) 270-0151. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/L.K./Examiner, Art Unit 3666
/SCOTT A BROWNE/Supervisory Patent Examiner, Art Unit 3666
Prosecution Insights