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 .
Response to Amendment
This action is in response to amendments and remarks filed on 03/02/2026. Claim(s) 14, 16, 18, 20, 24, 26, 28, and 30 have been amended. Claim(s) 1-11 have been previously cancelled. Claim(s) 12-31 are pending examination. Objections to the abstract, specification, and drawings have been withdrawn in light of the instant amendments. Rejection to claim(s) 14-18, 20, 24-28, and 30 over the 35 USC 112(b) rejection has been withdrawn in light of the instant amendments. This action is made final.
Response to Arguments
Applicant presents the following argument(s) regarding the previous office action:
Applicant asserts that the 35 USC 101 rejection of the claims is improper. Applicant asserts that the claims as recited are not a mental process and therefore not subject to a judicial exception.
Applicant asserts that the 35 USC 103 rejection of independent claims 12 and 22 is improper with the prior cited art, Cserna, not teaching all claim limitations.
Applicant's arguments filed 03/02/2026 have been fully considered but they are not persuasive.
Regarding applicant’s argument A, the examiner respectfully disagrees. Applicant’s arguments appear to be centered on the idea that the claims cannot be reasonably performed in the human mind and certain limitations of the claims would be a practical application.
The first element of the applicant’s argument is that “The MPEP states, at section 2106.04(a)(2)(III)(A), that ‘A Claim With Limitation(s) That Cannot Practically be Performed in the Human Mind Does Not Recite a Mental Process.’ The MPEP further states, ‘Claims do not recite a mental process when they do not contain limitations that can practically be performed in the human mind, for instance when the human mind is not equipped to perform the claim limitations.’” (Page 33; Applicant’s arguments submitted on 03/02/2026) This is merely the title and first line of the MPEP section cited. Applicant does not add any reason that the claim could not be performed in the human mind, rather they merely assert it as fact, “Applicant respectfully submits that the identified steps of Applicant’s claims are not reasonably capable of being performed in the human mind and, as such, are not ‘mental processes.’” Merely asserting that something is not a mental process is not the same as showing how it is not a mental process. Additionally, the MPEP 2106.04(a)(2)(III)(C.) states, “Claims can recite a mental process even if they are claimed as being performed on a computer. The Supreme Court recognized this in Benson, determining that a mathematical algorithm for converting binary coded decimal to pure binary within a computer’s shift register was an abstract idea. The Court concluded that the algorithm could be performed purely mentally even though the claimed procedures "can be carried out in existing computers long in use, no new machinery being necessary." 409 U.S at 67, 175 USPQ at 675. See also Mortgage Grader, 811 F.3d at 1324, 117 USPQ2d at 1699 (concluding that concept of "anonymous loan shopping" recited in a computer system claim is an abstract idea because it could be "performed by humans without a computer").” (Emphasis added). The claims as recited are merely an abstract idea. The claims are carried out on a generic computer without new elements added. The MPEP states as well, “if the claimed invention is described as a concept that is performed in the human mind and applicant is merely claiming that concept performed 1) on a generic computer, or 2) in a computer environment, or 3) is merely using a computer as a tool to perform the concept. In these situations, the claim is considered to recite a mental process.” (Emphasis added). The independent claims do not recite any new computer elements, rather just generic computing elements, i.e. processor, sensors. The algorithm of the claims can be performed in the human mind using a computer. The algorithm is merely gathering data from sensors equipped on one or more vehicles, evaluating the data, generating a new track, and evaluating that track. A person could reasonably examine the data at a specific point on a route, as claimed, and evaluate the new track based on an efficiency metric.
The second element of applicant’s argument is that the claim recites specifically more which integrates the claims into a practical application. Again applicant merely asserts this after reciting the other elements and citing the MPEP. The elements recited by the applicant are not practical applications of the algorithm. Instead they are elements that further define certain elements of the abstract idea. It is not a practical application to define the data as, “data associated with a possible deceleration point,” or “resource efficiency of the first motor vehicle…is evaluated on the basis of efficiency of the braking electric recuperation system.” These are insignificant elements that define what types of data are gathered and how that data is evaluated. This is understood to be insignificant post solution activity. Applicant has not shown how the claims limitations they argue are a practical applicant would indeed amount to more than just data gathering/defining the types of data gathered.
In light of the above elements the examiner would contend that the claims are merely a mental process in a generic computing environment. In light of this the claims would remain rejected under 35 USC 101. Please see the section below titled, “Claims Rejections – 35 USC 101,” for detailed explanation.
Regarding applicant’s argument B, the examiner respectfully disagrees. Applicant asserts that the prior cited Cserna reference does not disclose, “collecting secondary data, which involves generating a track for the first motor vehicle, wherein said track is generated based on how the first motor vehicle passed the portion of the route, and wherein the electric recuperation system is activated when the first motor vehicle is braking while moving along a portion of the route and passing the possible deceleration point;” of the independent claims 12 and 22. Applicant asserts that [0032] of Cserna does not teach this. However, the examiner did not solely rely on [0032] to teach this limitation, rather the examiner cited, [0031]-[0032] and [0039]. Looking at [0031] it clearly states, “semantic map module 204 can be configured to generate and/or maintain semantic map information for one or more geographic regions. Semantic maps can, in various embodiments, be broadly defined to include any map having associated metadata and/or any other layered information associated with the map or elements contained within the map. Semantic map information for a geographic region can include, for example, names and locations of roads, locations of lane boundaries, curvature of roads, speed limits of roads, locations and descriptions of road constraints (e.g., stop signs, speed bumps, traffic lights, cross-walks, etc.), road inclination information (e.g., a degree of incline or decline for each road segment in the region), locations and descriptions of static obstacles (e.g., construction), traffic condition information, and the like… semantic maps can be utilized by the route planner module 206 to determine a route for a vehicle, by the trajectory planner module 208 to determine a trajectory for a vehicle, and/or by the vehicle management module 210 to make various vehicle management determinations for a vehicle.” (Emphasis added). As the applicant admits in their response [0032] further states that the semantic information can include historical power consumption trends. [0039] then adds that the power management system can make determinations that, “can include one or more of the following: whether to turn a gas engine on or off, and when to do so; whether to turn one or more electric motors on or off, and when to do so; whether to engage or disengage regenerative magnetic brakes, and when to do so; whether to use or not use friction brakes, and when to do so; what proportions of friction brakes versus magnetic brakes to use; what proportions of gas engine, electric motor, and engine brake to use; and the like.” (Emphasis added). Taken as a whole the cited portions of Cserna show that the vehicle computer can capture data about how a vehicle operates at a specific portion of road. This includes the vehicle management determinations, including whether or not to engage the regenerative braking system. In light of this the examiner would maintain that Cserna teaches the limitation the applicant alleges it does not teach. Therefore, the 35 USC 103 rejection of the claims would remain in place. Please see the section below titled, “Claim Rejections – 35 USC 103,” for detailed mapping and explanation.
Information Disclosure Statement
The information disclosure statement(s) (IDS) submitted on 04/14/2026, are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statements have been considered by the examiner.
Claim Rejections - 35 USC § 101
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claims 12-31 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Analysis of the claim(s) regarding subject matter eligibility utilizing the 2019 Revised Patent Subject Matter Eligibility Guidance is described below.
STEP 1: STATUTORY CATEGORIES
Claim(s) 12-32 do fall into at least one of the four statutory subject matter categories. Claim 12 and its dependents are directed to a method which is the statutory category of a process. Claims 22 and its dependents are directed to a non-transitory computer readable medium which is the statutory category of a manufacture.
STEP 2A: JUDICIAL EXCEPTIONS
PRONG 1: RECITATION OF A JUDICIAL EXCEPTION
The claim(s) recite(s):
- Claim 12 recite(s) an abstract idea belonging to the grouping of mental processes. Claim 12 recites, “collecting primary data, which involves obtaining data associated with a first motor vehicle…a portion of a route…and a second motor vehicle,” “collecting secondary data, which involves generating a track for the first motor vehicle,” “generating an estimated track for the second motor vehicle,” and “wherein the track for the first motor vehicle is generated by performing the following steps: generating a speed profile of the first motor vehicle…evaluating resource efficiency of the first motor vehicle.” The claim amounts to data gathering and processing. The data gathering and analysis is recited at a high level and would be a mental step, Electric Power Group v. Alstom, S.A., 830 F.3d 1350, 1353-54, 119 USPQ2d 1739, 1741-42 (Fed. Cir. 2016). A person could achieve this result in their mind using a generic computer in a generic computing environment could collect data to indicate where a vehicle is at any time. Compare that to a historical track of a different vehicle. Finally they could make a new track for the active vehicle. A person could achieve the results of taking their vehicle down the most resource efficient track for resource recuperation by using the previously gathered data and the data currently gathered. Claim 22 is substantially similar and would be rejected for the same reasoning.
- Claim 13 recite(s) insignificant extrasolution activity. Claim 13 recites, “data associated with the first and/or second motor vehicle include at least one of the following,” and “wherein the data associated with the portion of the route to be passed by the first motor vehicle further include at least one of the following data obtained from external sources.” The claim is directed to the types of data that may be gathered. Claim 23 is substantially similar and would be rejected for the same reasoning.
- Claim 14 recite(s) an abstract idea belonging to the grouping of mental processes. Claim 14 recites, “when the first motor vehicle reaches the mandatory deceleration point, an estimated track for the first motor vehicle is generated,” “wherein the time that the first motor vehicle requires to pass said another portion of the road moving from the mandatory deceleration point to an end point of passing said another portion of the road is also calculated,” and “an estimated speed profile of the first motor vehicle for the estimated track for the first motor vehicle is generated.” This claim is directed at merely generating a path for the vehicle. A person in their mind and/or with a generic computer could look at the vehicle approaching an intersection, and beginning to slow down. The person could then determine the correct movement forward whether it is accelerating through the intersection or slowing to a stop. The claim does not require these actions to be carried out merely that a path is generated in the speed profile. Claim 24 is substantially similar and would be rejected for the same reasoning.
- Claim 15 recite(s) insignificant extrasolution activity. Claim 15 recites, “the estimated track for the first motor vehicle is generated taking into account one of the following: data associated with a motor vehicle…” The claim then recites various types of data taken into account that may be gathered. Claim 25 is substantially similar and would be rejected for the same reasoning.
- Claim 16 recite(s) an abstract idea belonging to the grouping of mental processes. Claim 16 recites, “when the first motor vehicle reaches the mandatory deceleration point, an estimated track for the first motor vehicle is generated, wherein the time when the traffic control means would again signal that it is allowed to intersect said another portion of the road without stopping is also calculated; and, based on the time calculation, the mandatory deceleration point is relocated so as to allow the first motor vehicle to move along a trajectory that intersects said another portion of the route without stopping.” The claim is recited in a way that it is merely generating a track and moving points of the track around. A person could gather the necessary data in a computing environment and looking at the data determine that moving the stopping point would allow the vehicle to continue without stopping. The claim does not recite vehicle control merely route generation, which a person could reasonably achieve in their mind and/or with a generic computing device. Claim 26 is substantially similar and would be rejected for the same reasoning.
- Claim 17 recite(s) an abstract idea belonging to the grouping of mental processes. Claim 17 recites, “wherein the steps of the aforementioned method are performed for each mandatory deceleration point so as to allow the first motor vehicle to move along the trajectories that intersect the other portion of the route without stopping.” The claim is related to route generation. There is no control of the vehicle, rather merely determining a route. The fact it is carried out at each intersection does not mean a person couldn’t reasonably achieve this effect as there may only be a limited number of intersections on a route and would not mean the computational burden is too intense for a person in a generic computing environment. Claim 27 is substantially similar and would be rejected for the same reasoning.
- Claim 18 recite(s) an abstract idea belonging to the grouping of mental processes. Claim 18 recites, “a track for the motor vehicle located on said another portion of the route is generated, wherein said track contains at least data associated with said another portion of the route that motor vehicle is moving along,” and “wherein said trajectory data include data associated with an intersection between the first motor vehicle's trajectory and that of the motor vehicle moving along said another portion of the route, the mandatory deceleration point is relocated so as to prevent the first motor vehicle and the motor vehicle moving along said another portion of the route from reaching said intersection at the same time.” The claim is merely route generation. A person using a generic computing device or in their own mind could determine that a vehicle in motion is approaching another vehicle in the environment. The person could then determine that the vehicle should adjust its speed in order to allow the ego vehicle to proceed without colliding with another vehicle while also maintaining a smooth driving experience. Claim 28 is substantially similar and would be rejected for the same reasoning.
- Claim 19 recite(s) an abstract idea belonging to the grouping of mental processes. Claim 19 recites, “generate an estimated track for the first motor vehicle that would correspond to the estimated track for the motor vehicle on the portion of the route at the mandatory deceleration point or in its vicinity, wherein the first motor vehicle is moving along the portion of the route at a lesser speed than the motor vehicle on the portion of the route at the mandatory deceleration point or in its vicinity.” The claim is merely route generation. A person using a generic computing device or in their own mind could determine that a vehicle in motion is approaching another vehicle in the environment. The person could then determine that the vehicle should adjust its speed in order to allow the ego vehicle to proceed without colliding with another vehicle while also maintaining a smooth driving experience. Claim 29 is substantially similar and would be rejected for the same reasoning.
- Claim 20 recite(s) an abstract idea belonging to the grouping of mental processes. Claim 20 recites, “a track for the motor vehicle located on said another portion of the route is generated, wherein said track contains at least data associated with said another portion of the route that motor vehicle is moving along,” and “wherein said trajectory data include data associated with an intersection between the first motor vehicle's trajectory and that of the motor vehicle moving along said another portion of the route, the mandatory deceleration point is relocated so as to prevent the first motor vehicle and the motor vehicle moving along said another portion of the route from reaching said intersection at the same time,” and “generate an estimated track for the first motor vehicle that would correspond to the estimated track for the motor vehicle on the portion of the route at the mandatory deceleration point or in its vicinity, wherein the first motor vehicle is moving along the portion of the route at a lesser speed than the motor vehicle on the portion of the route at the mandatory deceleration point or in its vicinity.” The claim is merely route generation. A person using a generic computing device or in their own mind could determine that a vehicle in motion is approaching another vehicle in the environment. The person could then determine that the vehicle should adjust its speed in order to allow the ego vehicle to proceed without colliding with another vehicle while also maintaining a smooth driving experience. Claim 30 is substantially similar and would be rejected for the same reasoning.
- Claim 21 recite(s) insignificant extrasolution activity. Claim 21 recites, “characterized in that the possible deceleration point on the portion of the route is located in accordance with the data associated with the first motor vehicle.” The claim is directed to the types of data that may be gathered. Claim 31 is substantially similar and would be rejected for the same reasoning.
PRONG 2: INTEGRATION INTO A PRACTICAL APPLICATION
The additional element(s) recited in the claim(s) beyond the judicial exception are various types of data gathered and insignificant uses of the data. The additional element(s) do not integrate the judicial exception into a practical application because the additional element(s) do not apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception and add insignificant extra-solution activity to the judicial exception. The computer elements are merely used as a tool to perform the abstract idea, and the use of the judicial exception is generally linked to the particular technological environment of autonomous vehicle driving without using the judicial exception in some other meaningful way (MPEP 2106.04(d)).
STEP 2B: INVENTIVE CONCEPT/SIGNIFICANTLY MORE
The additional elements recited in the claim(s) are not sufficient to amount to significantly more than the judicial exception because they do not add more than insignificant extra-solution activity to the judicial exception (MPEP 2106.05(g)), and the computer functions of receiving and transmitting data have been recognized by the courts as well-understood, routine, and conventional functions when they are claimed in a merely generic manner or as insignificant extra-solution activity (MPEP 2106.05(d)). Further, the additional elements of a “memory” and a “processor” recited in the claim(s) are well-understood, routine, and conventional activities previously known to the industry, specified at a high level of generality (MPEP2106.05 (d)).
Based on the above analysis, claim(S) 12-31 is/are not eligible subject matter and is/are rejected under 35 U.S.C 101.
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.
Claim(s) 12-31 is/are rejected under 35 U.S.C. 103 as being unpatentable over Cserna (US PG Pub 2020/0122588) in view of Kibalama (US PG Pub 2023/0160707).
Regarding claim 12, Cserna teaches a method for generating a recuperation resource-efficient track for a vehicle in operation equipped with a braking electric recuperation system moving along a portion of a route that includes a possible deceleration point, ([0027]-[0028] teaches a vehicle with regenerative breaks) that is performed by a computer's CPU, ([0064] teaches a computer with a CPU controlling the method) the method comprising at least the following steps:
collecting primary data, which involves obtaining data associated with a first motor vehicle equipped with the braking electric recuperation system; ([0025] and [0032] teach capturing data for a vehicle as it travels, this data includes power usage data. The vehicle is equipped with regenerative braking devices) data associated with a portion of a route to be passed by the first motor vehicle, ([0026]-[0027] teach data about a passed portion of the route being captured. [0031]-[0032]further this by determining more precise data such as slow down points and power levels at certain areas of the map) and data associated with a second motor vehicle, ([0030] teaches capturing data for a fleet of vehicles) wherein the second motor vehicle is also the vehicle in operation and passes the portion of the route after the first motor vehicle, ([0032]-[0033] teaches the system as able to configure a route for a vehicle in operation and detect sensor data about that vehicle. [0032] furthers this by teaches that the system can determine that the second vehicle is about to pass an area that it has historical pathing data from) and wherein the data associated with the portion of the route include at least data associated with a possible deceleration point; ([0031] and [0036] teach determining that a certain area will have “constraints” these include road points that would require the slowing of the vehicle)
collecting secondary data, which involves generating a track for the first motor vehicle, wherein said track is generated based on how the first motor vehicle passed the portion of the route, and wherein the electric recuperation system is activated when the first motor vehicle is braking while moving along a portion of the route and passing the possible deceleration point; ([0031]-[0032] and [0039] teach the system capturing data and generating information about the use of a vehicle’s regenerative braking system as it travels through a particular portion of the route.)
generating an estimated track for the second motor vehicle, wherein said estimated track is generated based on the track generated for the first motor vehicle; ([0030]-[0033] teach the generation of a vehicle track based on historical vehicle data gathered by previous vehicles) wherein the track for the first motor vehicle is generated by performing the following steps:
and evaluating resource efficiency of the first motor vehicle on the passed portion of the route; ([0032]-[0033] teach the system determining the efficiency of a vehicle as it passes through a portion of the route)
wherein resource efficiency of the first motor vehicle on the passed portion of the route is evaluated on the basis of efficiency of the braking electric recuperation system of the first motor vehicle; ([0048] teaches the system determining an efficient travel route with the basis of the use of regenerative braking to maintain resources effectively)
wherein the data associated with a possible deceleration point include one of the following: data associated with a mandatory deceleration point, data associated with a non-mandatory deceleration point, and/or a combination thereof; ([0031] and [0036] teach the system determining a series of possible deceleration points that are mandatory or non-mandatory)
wherein the data associated with a mandatory deceleration point include one of the following: data associated with a mandatory deceleration point on a portion of a route that is adjoined or intersected by another portion of a route, data associated with a mandatory deceleration point on a portion of a route containing an infrastructure element, which controls a movement of motor vehicles on this portion of the route, data associated with a mandatory deceleration point on a portion of a route containing a traffic sign providing a speed limit for motor vehicles on this portion of the route, data associated with a mandatory deceleration point on a portion of a route containing an obstacle, data associated with a mandatory deceleration point on a portion of a route containing a turn, and/or a combination thereof; ([0031] and [0036] teach a mandatory stopping point for a vehicle as a “road constraint” this includes stop signs, traffic lights, etc.)
and wherein the data associated with a non-mandatory deceleration point include one of the following: data associated with a non-mandatory deceleration point on a portion of a route containing an incline, data associated with a non-mandatory deceleration point on a portion of a route containing a visual obstruction, and/or a combination thereof. ([0031] and [0036] teach the route may be subject to non-mandatory deceleration points, these can be road grade, obstacles, etc.)
Cserna does not teach generating a speed profile of the first motor vehicle on the passed portion of the route.
However, Kibalama teaches “generating a speed profile of the first motor vehicle on the passed portion of the route,” ([0044] and [0101]-[0102] teaches determining a vehicle speed/propulsion profile for a particular road section)
It would have been prima facie obvious to one of ordinary skill in the art, before the effective filing date, to incorporate the teachings of Cserna with Kibalama; and have a reasonable expectation of success. Both relate to the generation of vehicle routes and controls for the vehicle in response to regenerative braking controls and its environment. As Kibalama teaches in [0037]-[0038] the use of vehicle profiles allows for the data of the vehicle to be monitored for and adjusted. This in turn allows for a maximizing of efficiency of the vehicle’s propulsion and energy system, [0044]. This would improve upon systems that are looking to be the most efficient system possible and ensure the system/method is optimal.
Claim 22 is substantially similar and would be rejected for the same reasoning.
Regarding claim 13 Cserna teaches the method of claim 12, characterized in that the data associated with the first and/or second motor vehicle include at least one of the following: the type and model of the first motor vehicle, its mass, its aerodynamic characteristics, its wheel formula, its estimated and/or actual resource consumption and its estimated and/or actual VHI, data from its positioning sensors, weight sensors, and wheel speed sensors, or a combination thereof; ([0063] teaches the system can capture data about the vehicle including its location, kinetic information, wheel information, etc. [0032] teaches the system recording actual and/or estimated energy consumption) wherein the data associated with the portion of the route to be passed by the first motor vehicle further include at least one of the following data obtained from external sources: ([0030] teaches the system may communicate with an external data storage device that stores semantic map information) the geometry of the portion of the route, the road grade of the portion of the route, the allowed speed on the portion of the route, the quality of road surface of the portion of the route, speed limits on the portion of the route, turns on the portion of the route, weather conditions on the portion of the route, its infrastructure, data associated with a motor vehicle located on another portion of the route, data associated with a motor vehicle located on the portion of the route at the mandatory deceleration point or in its vicinity, estimation of a motor vehicle being present on another portion of the route, estimation of a motor vehicle being present on the portion of the route at the mandatory deceleration point or in its vicinity, and/or a combination thereof. ([0031] teaches the system having a combination of the data required, including incline data, speed limits, curvature, infrastructure elements, lane boundaries, rad conditions, obstacle information, etc.)
Claim 23 is substantially similar and would be rejected for the same reasoning.
Regarding claim 14 Cserna teaches the method of claim 13, characterized in that in case when the data associated with the mandatory deceleration point are the data associated with the mandatory deceleration point located on the portion of the road intersected by another portion of the road ([0031] and [0035]-[0036] teach that the system can determine that the deceleration point is associated with an intersection crossing at the road) ([0036] teaches generating the trajectory for thew vehicle in relation to a stopping point) ([0035] teaches that the vehicle trajectory would be straight through the intersection therefore the endpoint would not be on the crossing road) ([0035] teaches that the vehicle trajectory would be straight through the intersection therefore the endpoint would not be on the crossing road)
Cserna does not teach and when the infrastructure data of the portion of the road contain data obtained from a traffic control means signaling that it is allowed to cross said another portion of the road without stopping; wherein the time that the first motor vehicle requires to pass said another portion of the road moving from the mandatory deceleration point to an end point of passing said another portion of the road is also calculated; and, based on the time calculation, an estimated speed profile of the first motor vehicle for the estimated track for the first motor vehicle is generated, wherein the estimated speed profile contains at least the first motor vehicle moving through the mandatory deceleration point while decreasing its speed to full stop in the mandatory stop point.
However, Kibalama teaches “and when the infrastructure data of the portion of the road contain data obtained from a traffic control means signaling that it is allowed to cross said another portion of the road without stopping” ([0077]-[0080] teaches receiving broadcasted signal information from the intersection signal that includes the timing and current sequence of the light ) “wherein the time that the first motor vehicle requires to pass said another portion of the road moving from the mandatory deceleration point to an end point of passing said another portion of the road is also calculated” ([0083]-[0085] teach generating a speed profile of a vehicle to determine its possibility to pass through an intersection based on the vehicle’s motion characteristics and the intersection timing) and “and, based on the time calculation, an estimated speed profile of the first motor vehicle for the estimated track for the first motor vehicle is generated, wherein the estimated speed profile contains at least the first motor vehicle moving through the mandatory deceleration point while decreasing its speed to full stop in the mandatory stop point.” ([0083]-[0085] teach generating a speed profile of a vehicle to determine its possibility to pass through an intersection based on the vehicle’s motion characteristics and the intersection timing [0088] furthers this teaching by ensuring that the vehicle must stop at the intersection before continuing through)
It would have been prima facie obvious to one of ordinary skill in the art, before the effective filing date, to incorporate the teachings of Cserna with Kibalama; and have a reasonable expectation of success. Both relate to the generation of vehicle routes and controls for the vehicle in response to regenerative braking controls and its environment. As Kibalama teaches in [0037]-[0038] the use of vehicle profiles allows for the data of the vehicle to be monitored for and adjusted. This in turn allows for a maximizing of efficiency of the vehicle’s propulsion and energy system, [0044]. This would improve upon systems that are looking to be the most efficient system possible and ensure the system/method is optimal. The reception of information from infrastructure allows for a more precise control. As [0029] teaches the use of V2I data transmission allows for optimal solution figuring and look-ahead optimization.
Claim 24 is substantially similar and would be rejected for the same reasoning.
Regarding claim 15 Cserna teaches the method of claim 14, characterized in that the estimated track for the first motor vehicle is generated taking into account one of the following: data associated with a motor vehicle located on another portion of the route, data associated with a motor vehicle located on the portion of the route at the mandatory deceleration point or in its vicinity, estimation of a motor vehicle being present on another portion of the route, estimation of a motor vehicle being present on the portion of the route at the mandatory deceleration point or in its vicinity, or a combination thereof. ([0031] teaches taking into account traffic conditions would be analogous to vehicles around the ego vehicle when making a vehicle track. [0036] furthers this teaching by ensuring the vehicle uses sensor data to determine the plethora of obstacles, i.e. vehicles, around or near the ego vehicle)
Claim 25 is substantially similar and would be rejected for the same reasoning.
Regarding claim 16 Cserna teaches the method of claim 13, characterized in that in case when the data associated with the mandatory deceleration point are the data associated with the mandatory deceleration point located on the portion of the road intersected by another portion of the road ([0031] and [0035]-[0036] teach that the system can determine that the deceleration point is associated with an intersection crossing at the road) point, an estimated track for the first motor vehicle is generated, ([0036] teaches generating the trajectory for thew vehicle in relation to a stopping point)
Cserna does not teach and when the infrastructure data of the portion of the road contain data obtained from a traffic control means signaling that it is not allowed to cross said another portion of the road without stopping; wherein the time when the traffic control means would again signal that it is allowed to intersect said another portion of the road without stopping is also calculated; and, based on the time calculation, the mandatory deceleration point is relocated so as to allow the first motor vehicle to move along a trajectory that intersects said another portion of the route without stopping, when the traffic control means signals that it is allowed to cross said another portion of the road without stopping.
However, Kibalama teaches “and when the infrastructure data of the portion of the road contain data obtained from a traffic control means signaling that it is not allowed to cross said another portion of the road without stopping;” ([0077]-[0080] teaches receiving broadcasted signal information from the intersection signal that includes the timing and current sequence of the light, this includes whether or not it would be possible to cross. [0089]-[0094] teach the vehicle approaching at a red or yellow light, which would indicate the vehicle is not allowed to cross) “wherein the time when the traffic control means would again signal that it is allowed to intersect said another portion of the road without stopping is also calculated;” ([0083]-[0085] teach generating a speed profile of a vehicle to determine its possibility to pass through an intersection based on the vehicle’s motion characteristics and the intersection timing. [0089]-[0090] further determines the amount of time remaining in the light cycle) and “and, based on the time calculation, the mandatory deceleration point is relocated so as to allow the first motor vehicle to move along a trajectory that intersects said another portion of the route without stopping, when the traffic control means signals that it is allowed to cross said another portion of the road without stopping.” ([0083]-[0087] teaches the vehicle adjusting its route to enable the stop point to be moved based on the estimated time remaining in the light cycle, the speed profile, etc. [0089]-[0094] further determine that the vehicle can adjust its deceleration profile in order to ensure that the vehicle can arrive at an intersection in a way that allows it to move without stopping based on received information)
It would have been prima facie obvious to one of ordinary skill in the art, before the effective filing date, to incorporate the teachings of Cserna with Kibalama; and have a reasonable expectation of success. Both relate to the generation of vehicle routes and controls for the vehicle in response to regenerative braking controls and its environment. As Kibalama teaches in [0037]-[0038] the use of vehicle profiles allows for the data of the vehicle to be monitored for and adjusted. This in turn allows for a maximizing of efficiency of the vehicle’s propulsion and energy system, [0044]. This would improve upon systems that are looking to be the most efficient system possible and ensure the system/method is optimal. The reception of information from infrastructure allows for a more precise control. As [0029] teaches the use of V2I data transmission allows for optimal solution figuring and look-ahead optimization.
Claim 26 is substantially similar and would be rejected for the same reasoning.
Regarding claim 17 Cserna teaches the method of claim 16, characterized in that the data associated with the portion of the route include at least data associated with several mandatory deceleration points, ([0031] and [0036] teach several stopping points on a route) wherein the data associated with mandatory deceleration points are data associated with mandatory deceleration points on the portion of the route that are located, respectively, before other portions of the route intersecting said portion of the route, ([0031] and [0036] teach the system determining the stopping points are along the route associated with various portions of intersections signals, etc. all along the route passage area)
Cserna does not teach wherein the data obtained from traffic control means are associated with each respective other portion of the route; and wherein the steps of the aforementioned method are performed for each mandatory deceleration point so as to allow the first motor vehicle to move along the trajectories that intersect the other portion of the route without stopping, when the traffic control means of each respective other portion of the route signal that it is allowed to cross said other portion of the route without stopping
However, Kibalama teaches “wherein the data obtained from traffic control means are associated with each respective other portion of the route;” ([0059] teaches determining and linking information between a signal and the signal location in the world on the estimated route) and “wherein the steps of the aforementioned method are performed for each mandatory deceleration point so as to allow the first motor vehicle to move along the trajectories that intersect the other portion of the route without stopping, when the traffic control means of each respective other portion of the route signal that it is allowed to cross said other portion of the route without stopping” ([0081] teaches that the vehicle can process this information for each intersection as the vehicle travels and can ensure to the best of its ability the possibility of not stopping for each intersection)
It would have been prima facie obvious to one of ordinary skill in the art, before the effective filing date, to incorporate the teachings of Cserna with Kibalama; and have a reasonable expectation of success. Both relate to the generation of vehicle routes and controls for the vehicle in response to regenerative braking controls and its environment. As Kibalama teaches in [0037]-[0038] the use of vehicle profiles allows for the data of the vehicle to be monitored for and adjusted. This in turn allows for a maximizing of efficiency of the vehicle’s propulsion and energy system, [0044]. This would improve upon systems that are looking to be the most efficient system possible and ensure the system/method is optimal. The reception of information from infrastructure allows for a more precise control. As [0029] teaches the use of V2I data transmission allows for optimal solution figuring and look-ahead optimization.
Claim 27 is substantially similar and would be rejected for the same reasoning.
Regarding claim 18 Cserna teaches the method of claim 13, characterized in that in case the data associated with the portion of the route to be passed by the first motor vehicle further include at least data associated with a motor vehicle located on said another portion of the route, ([0031] and [0036] teach taking other motor vehicles into account when monitoring the route to be passed) , wherein the data associated with the portion of the route to be passed by the first motor vehicle further include data associated with a trajectory of the first motor vehicle ([0028] teaches the vehicle system determining a trajectory for a vehicle for an upcoming portion of the road. [0034] furthers this teaching with the use of a trajectory planning module),, .
Cserna does not teach a track for the motor vehicle located on said another portion of the route is generated, wherein said track contains at least data associated with said another portion of the route that motor vehicle is moving along; wherein the data associated with said another portion of the route include data associated with a trajectory of the motor vehicle moving along said another portion of the route; and wherein said trajectory data include data associated with an intersection between the first motor vehicle's trajectory and that of the motor vehicle moving along said another portion of the route; and the mandatory deceleration point is relocated so as to prevent the first motor vehicle and the motor vehicle moving along said another portion of the route from reaching said intersection at the same time, while also enabling the first motor vehicle to move along its trajectory without stopping.
However, Kibalama teaches “a track for the motor vehicle located on said another portion of the route is generated, wherein said track contains at least data associated with said another portion of the route that motor vehicle is moving along;” ([0051]-[0052] teaches receiving data to generate an indication of another vehicle in the path and determining the trajectory of the another vehicle. [0061] teaches that the V2X system can share a plethora of data associated with the segment of the route on which the vehicle is driving) “wherein the data associated with said another portion of the route include data associated with a trajectory of the motor vehicle moving along said another portion of the route;” ([0087] teaches the system determining acceleration and location information, i.e. trajectory information, of the other vehicle on the route) “wherein said trajectory data include data associated with an intersection between the first motor vehicle's trajectory and that of the motor vehicle moving along said another portion of the route;” ([0087] teaches the determination that a collision will occur between vehicles) and “the mandatory deceleration point is relocated so as to prevent the first motor vehicle and the motor vehicle moving along said another portion of the route from reaching said intersection at the same time, while also enabling the first motor vehicle to move along its trajectory without stopping” ([0087] teaches adjusting the ego vehicle speed profile in order to prevent a collision or “intersection” of the vehicles based on their trajectories. [0092] teaches the vehicle system adjusting its deceleration programming to allow the ego vehicle to proceed without stopping based on the location of other vehicles on a route. i.e. adjusting the deceleration point)
It would have been prima facie obvious to one of ordinary skill in the art, before the effective filing date, to incorporate the teachings of Cserna with Kibalama; and have a reasonable expectation of success. Both relate to the generation of vehicle routes and controls for the vehicle in response to regenerative braking controls and its environment. As Kibalama teaches in [0037]-[0038] the use of vehicle profiles allows for the data of the vehicle to be monitored for and adjusted. This in turn allows for a maximizing of efficiency of the vehicle’s propulsion and energy system, [0044]. This would improve upon systems that are looking to be the most efficient system possible and ensure the system/method is optimal. The reception of information from infrastructure allows for a more precise control. As [0087] teaches the tracing of another vehicle allows the system to prevent improper start-stop operations and prevent excess energy usage.
Claim 28 is substantially similar and would be rejected for the same reasoning.
Regarding claim 19 Cserna teaches the method of claim 13, characterized in that in case the data associated with the portion of the route to be passed by the first motor vehicle further include at least data associated with a motor vehicle on the portion of the route at the mandatory deceleration point or in its vicinity, ([0031] and [0036] teach taking other motor vehicles into account when monitoring the route to be passed) would correspond to the estimated track for the motor vehicle on the portion of the route at the mandatory deceleration point or in its vicinity, ([0048] teaches the system generating a new track based on detected vehicles in the vicinity of the ego vehicle. This track is adjusted based on the trajectory of the other vehicles being slower/stopped when compared to the ego vehicle. The new trajectory is similar to the existing vehicles, but is adjusted so that the ego vehicle moves at a speed slower than the existing vehicle)
Cserna does not teach a track for that motor vehicle is generated; and wherein the first motor vehicle is moving along the portion of the route at a lesser speed than the motor vehicle on the portion of the route at the mandatory deceleration point or in its vicinity
However, Kibalama teaches “a track for that motor vehicle is generated” ([0051]-[0052] teaches receiving data to generate an indication of another vehicle in the path and determining the trajectory of the another vehicle) and “wherein the first motor vehicle is moving along the portion of the route at a lesser speed than the motor vehicle on the portion of the route at the mandatory deceleration point or in its vicinity” ([0051] teaches the vehicle system adjusting the vehicle controls based on a lead vehicle being slower than the ego vehicle)
It would have been prima facie obvious to one of ordinary skill in the art, before the effective filing date, to incorporate the teachings of Cserna with Kibalama; and have a reasonable expectation of success. Both relate to the generation of vehicle routes and controls for the vehicle in response to regenerative braking controls and its environment. As Kibalama teaches in [0037]-[0038] the use of vehicle profiles allows for the data of the vehicle to be monitored for and adjusted. This in turn allows for a maximizing of efficiency of the vehicle’s propulsion and energy system, [0044]. This would improve upon systems that are looking to be the most efficient system possible and ensure the system/method is optimal. The reception of information from infrastructure allows for a more precise control. As [0087] teaches the tracing of another vehicle allows the system to prevent improper start-stop operations and prevent excess energy usage.
Claim 29 is substantially similar and would be rejected for the same reasoning.
Regarding claim 20 Cserna teaches the method of claim 13, characterized in that the data associated with the portion of the route to be passed by the first motor vehicle further include at least one of the following: estimation of a motor vehicle being present on another portion of the route, ([0031] and [0036] teach taking other motor vehicles into account when monitoring the route to be passed) estimation of a motor vehicle being present on the portion of the route at the mandatory deceleration point or in its vicinity, or a combination thereof; ([0031] and [0036] teach taking other motor vehicles into account when monitoring the route to be passed; a combination would be taught) wherein in case the data associated with the portion of the route to be passed by the first motor vehicle further include estimation of a motor vehicle being present on said another portion of the route, ([0031] and [0036] teach taking other motor vehicles into account when monitoring the route to be passed) ([0028] teaches the vehicle system determining a trajectory for a vehicle for an upcoming portion of the road. [0034] furthers this teaching with the use of a trajectory planning module) and
and wherein in case the data associated with the portion of the route to be passed by the first motor vehicle further include the estimation of a motor vehicle being present on the portion of the route at the mandatory deceleration point or in its vicinity, ([0031] and [0036] teach taking other motor vehicles into account when monitoring the route to be passed) ([0048] teaches the system generating a new track based on detected vehicles in the vicinity of the ego vehicle. This track is adjusted based on the trajectory of the other vehicles being slower/stopped when compared to the ego vehicle. The new trajectory is similar to the existing vehicles, but is adjusted so that the ego vehicle moves at a speed slower than the existing vehicle)
Cserna does not teach an estimated track for the motor vehicle that may be present on said another portion of the route is generated, wherein said estimated track contains at least data associated with said another portion of the route that motor vehicle may be moving along, wherein the data associated with said another portion of the route include data associated with an estimated trajectory of the motor vehicle, which may be moving along said another portion of the route; wherein in case the data associated with the trajectory of the first motor vehicle and the data associated with the estimated trajectory of the motor vehicle, which may be moving along said another portion of the route, include data associated with an intersection between the first motor vehicle's trajectory and the estimated trajectory of the motor vehicle, which may be moving along said another portion of the route, the mandatory deceleration point is relocated so as to prevent the first motor vehicle and the motor vehicle, which may be moving along said another portion of the route, from reaching said intersection at the same time, which may be located on said another portion of the route, while also enabling the first motor vehicle to move along its trajectory without stopping; an estimated track for that motor vehicle is generated; wherein the first motor vehicle is moving along the portion of the route at a lesser speed than the motor vehicle, which may be present on the portion of the route to be passed by the first motor vehicle, at the mandatory deceleration point or in its vicinity.
However, Kibalama teaches “an estimated track for the motor vehicle that may be present on said another portion of the route is generated, wherein said estimated track contains at least data associated with said another portion of the route that motor vehicle may be moving along, wherein the data associated with said another portion of the route include data associated with an estimated trajectory of the motor vehicle, which may be moving along said another portion of the route,” ([0051]-[0052] teaches receiving data to generate an indication of another vehicle in the path and determining the trajectory of the another vehicle. [0061] teaches that the V2X system can share a plethora of data associated with the segment of the route on which the vehicle is driving) “wherein in case the data associated with the trajectory of the first motor vehicle and the data associated with the estimated trajectory of the motor vehicle, which may be moving along said another portion of the route, include data associated with an intersection between the first motor vehicle's trajectory and the estimated trajectory of the motor vehicle, which may be moving along said another portion of the route,” ([0087] teaches the system determining acceleration and location information, i.e. trajectory information, of the other vehicle on the route. [0087] further teaches the determination that a collision will occur between vehicles) and “the mandatory deceleration point is relocated so as to prevent the first motor vehicle and the motor vehicle, which may be moving along said another portion of the route, from reaching said intersection at the same time, which may be located on said another portion of the route, while also enabling the first motor vehicle to move along its trajectory without stopping” ([0087] teaches adjusting the ego vehicle speed profile in order to prevent a collision or “intersection” of the vehicles based on their trajectories. [0092] teaches the vehicle system adjusting its deceleration programming to allow the ego vehicle to proceed without stopping based on the location of other vehicles on a route. i.e. adjusting the deceleration point) “an estimated track for that motor vehicle is generated” ([0051]-[0052] teaches receiving data to generate an indication of another vehicle in the path and determining the trajectory of the another vehicle) and “wherein the first motor vehicle is moving along the portion of the route at a lesser speed than the motor vehicle, which may be present on the portion of the route to be passed by the first motor vehicle, at the mandatory deceleration point or in its vicinity.” ([0051] teaches the vehicle system adjusting the vehicle controls based on a lead vehicle being slower than the ego vehicle)
It would have been prima facie obvious to one of ordinary skill in the art, before the effective filing date, to incorporate the teachings of Cserna with Kibalama; and have a reasonable expectation of success. Both relate to the generation of vehicle routes and controls for the vehicle in response to regenerative braking controls and its environment. As Kibalama teaches in [0037]-[0038] the use of vehicle profiles allows for the data of the vehicle to be monitored for and adjusted. This in turn allows for a maximizing of efficiency of the vehicle’s propulsion and energy system, [0044]. This would improve upon systems that are looking to be the most efficient system possible and ensure the system/method is optimal. The reception of information from infrastructure allows for a more precise control. As [0087] teaches the tracing of another vehicle allows the system to prevent improper start-stop operations and prevent excess energy usage.
Claim 30 is substantially similar and would be rejected for the same reasoning.
Regarding claim 21 Cserna teaches the method of claim 13, characterized in that the possible deceleration point on the portion of the route is located in accordance with the data associated with the first motor vehicle. ([0036] teaches that the possible deceleration point is associated with vehicle data)
Claim 31 is substantially similar and would be rejected for the same reasoning.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Kang (US Pat 10,215,576) teaches a method for generating energy-optimized travel routes with a vehicle navigation system includes generating candidate travel routes between a route origin and one or more route destinations, and then dividing each candidate travel route into a plurality of route segments. The method includes estimating expected travel speeds along each segment using cloud information and calculating an expected energy efficiency over each of the candidate travel routes using one or more vehicle-specific energy efficiency models. The travel routes are displayed via the navigation system, including a trace of the energy-optimized travel routes and an expected or relative energy efficiency along the energy-optimized travel routes. A vehicle includes the navigation system and a powertrain. A powertrain controller may control vehicle speed over a selected route to maintain an optimally energy-efficient speed.
Gambera (US PG Pub 2016/0123755) teaches a fuel saving-aimed motor vehicle driver assistance system configured to receive and process motor vehicle-related data and motor vehicle position-related data to identify recurrent routes of a motor vehicle and to provide a motor vehicle driver, via an automotive human-machine interface, with motor vehicle driving assistance recommendations for fuel saving along the routes. The motor vehicle driver assistance system is configured to identify recurrent routes of the motor vehicle by determining a succession of geographic points, referred to as Waypoints, along a route of the motor vehicle, at which values of a series of physical quantities are determined and recorded, which define the attributes of the Waypoints. The Waypoint attributes are then updated when the vehicle travels through them. For each current motor vehicle position, a search is made for the Waypoint spatially closest to the current motor vehicle position and having certain characteristics, such that if such a Waypoint is not found, then a new Waypoint is defined, or else, if such a Waypoint is found, then variable Waypoint attributes are updated. The so-defined Waypoints are then concatenated so as to form an ordered list of Waypoints belonging to the same recurrent route. The characteristic points of the routes, such as bends, roundabouts and traffic lights, are identified and optimal speed profiles and primary controls for the motor vehicle at the characteristic points are computed. Based on the computed optimal speed profiles and primary controls and by means of the automotive human-machine interface, the motor vehicle driver is then provided with motor vehicle driving recommendations for fuel saving along the routes.
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 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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/N.S./Examiner, Art Unit 3665 /CHRISTIAN CHACE/Supervisory Patent Examiner, Art Unit 3665
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