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 .
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.
Status of Claims
The following is a non-final, first office action in response to the communication filed on 06/27/2025.
Claims 1-20 are currently pending.
Claims 1-20 have been examined.
Priority
Applicant' s claim for the benefit of prior-filed application under 35 U.S.C. 119(e) or under 35 U.S.C. 120, 121, or 365(c) is acknowledged.
Information Disclosure Statement
The Information Disclosure Statement received on 09/23/2026 has been reviewed and considered.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claims recite the judicial exception of a mental process. This judicial exception is not integrated into a practical application, nor do the claims include additional elements that are sufficient to amount to significantly more than the judicial exception.
Step 1: Yes, the claims are drawn to one or more statutory categories.
Step 1 of the Subject Matter Eligibility Test entails considering whether the claimed subject
matter falls within the four statutory categories of patentable subject matter identified by 35
U.S.C. 101: Process, machine, manufacture, or composition of matter.
Claims 1-9 are directed toward a method (i.e., process) with at least one step, claims 19-20 are directed toward ae electronic device (i.e., a machine), and claims 10-18 are directed toward a non-transitory computer readable storage medium (i.e., a manufacture).
Step 2A Prong 1: Yes, the claims recite an abstract idea.
If the claim recites a statutory category of invention, the claim requires further analysis
in Step 2A. Step 2A of the Subject Matter Eligibility Test is a two-prong inquiry. In Prong One,
examiners evaluate whether the claim recites a judicial exception.
Claim 1 recites abstract limitations, including those in bold below.
A time to collision prediction method for a vehicle, comprising:
obtaining first state information of an ego vehicle and second state information of a target object;
determining a collision risk and a first predicted time to collision between the ego vehicle and the target object based on the first state information and the second state information;
in response to that the collision risk indicates that a collision will occur between the ego vehicle and the target object, determining a collision state between the ego vehicle and the target object based on the first predicted time to collision; and
determining a target time to collision between the ego vehicle and the target object based on the collision state and the first predicted time to collision.
These limitations, as drafted, are simple processes that, under their broadest reasonable interpretation, cover performance in the mind. For example, the claim encompasses observing two vehicles at risk of colliding, obtaining basic kinematic information about the vehicle such as orientation and velocities, and performing basic computations in the mind to determine when and where a collision between the two vehicles would occur. The claim does not recite anything that precludes it from the mental process grouping.
Step 2A Prong 2: No, the claims do not recite additional elements that integrate the judicial exception into a practical application.
If the claim recites a judicial exception in step 2A Prong One, the claim requires further
analysis in step 2A Prong Two. In step 2A Prong Two, examiners evaluate whether the claim
recites additional elements that integrate the exception into a practical application of that
exception.
Claim 1 recites additional element limitations, including those underlined below.
A time to collision prediction method for a vehicle, comprising:
obtaining first state information of an ego vehicle and second state information of a target object;
determining a collision risk and a first predicted time to collision between the ego vehicle and the target object based on the first state information and the second state information;
in response to that the collision risk indicates that a collision will occur between the ego vehicle and the target object, determining a collision state between the ego vehicle and the target object based on the first predicted time to collision; and
determining a target time to collision between the ego vehicle and the target object based on the collision state and the first predicted time to collision.
The obtaining first state information of an ego vehicle and second state information of a target object is recited at a high level of generality and amounts to no more than insignificant pre-solution activity.
The additional elements fail to integrate the judicial exception into a practical application (see MPEP 2106.05(g)) because they merely amount to insignificant extra-solution activity.
Step 2B: No, the additional elements of these claims do not amount to significantly more than the judicial exception.
If the additional elements do not integrate the exception into a practical application in
step 2A Prong Two, then the claim is directed to the recited judicial exception, and requires
further analysis under Step 2B to determine whether they provide an inventive concept (i.e.,
whether the additional elements amount to significantly more than the exception itself).
As discussed above, the obtaining first state information of an ego vehicle and second state information of a target object amounts to no more than insignificant extra-solution activity and is recited at a high level of generality. The obtaining first state information of an ego vehicle and second state information of a target object as described in the claim is well-understood, routine, and conventional in the art.
Thus, even when viewed as an ordered combination, nothing in the claims add significantly more (i.e., an inventive concept) to the mental process.
The limitations of claims 2-9 merely serve to further clarify the mental process steps by adding detail to how the mental processes should be performed in ways that can still be done by performance of the mind. For the reasons described above with respect to claim 1, this judicial exception is not meaningfully integrated into a practical application or significantly more than the abstract idea.
The limitations of claim 10 is analogous to the limitations of claim 1 and thus the analysis of claim 1 is applied to claim 10. Claim 10 additionally recites a non-transitory computer readable storage medium, wherein the storage medium stores computer program instructions, when executed by a processor, cause the processor to implement the method that merely serves as a generic means to apply the otherwise judicial exception.
The additional limitations of claims 11-18 are analogous to the limitations of claims 2-9, respectively, and thus the analysis of claims 2-9 are applied to claims 11-18.
The limitations of claim 19 is analogous to the limitations of claim 1 and thus the analysis of claim 1 is applied to claim 19. Claim 19 additionally recites an electronic device, wherein the electronic device comprises: a memory, configured to store a computer program product, and a processor, configured to execute the computer program product stored in the memory, wherein when the computer program product is executed, the processor implements the method that merely serves as a generic means to apply the otherwise judicial exception.
The additional limitations of claims 20 are analogous to the limitations of claim 2, respectively, and thus the analysis of claims 2 is applied to claim 20.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1-5 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Zhao et al. (CN 114394091 A; hereinafter Zhao).
Regarding claim 1, Zhao discloses the subject matter indicated in bold below:
A time to collision prediction method for a vehicle, comprising (see Zhao at least pg. 8, paragraph 7 “The invention . . . provides a speed control method of a traffic vehicle . . . which comprises the following steps: . . .”; pg. 8, paragraph 14 “. . . recording the time corresponding to the track point which is coincided for the first time as collision time ttc . . .”):
obtaining first state information of an ego vehicle and second state information of a target object (see Zhao at least pg. 8, paragraph 8 “firstly, acquiring the kinematic information of a self vehicle [(i.e., first state information)] and an adjacent traffic vehicle [(i.e., second state information)] . . .”);
determining a collision risk and a first predicted time to collision between the ego vehicle and the target object based on the first state information and the second state information (see Zhao at least pg. 9, paragraph 4 “Comparing, judging whether the corner of the rectangular frame of the vehicle interferes with the parallel traffic vehicle, if a certain corner meets the requirement [(i.e., determining collision risk)] . . .”; pg. 10, paragraph 3 “. . . the long collision time calculation and the collision situation determination in the fourth step include the following steps: . . .”; pg. 11, paragraph 1 “The collision situation and collision time are calculated as follows: . . .”; Equation for ttccase0 – time to collision (i.e., a first predicted time to collision between the ego vehicle and the target object) determined using first and second state information);
in response to that the collision risk indicates that a collision will occur between the ego vehicle and the target object, determining a collision state between the ego vehicle and the target object based on the first predicted time to collision (see Zhao at least pg. 20, paragraph 3 “if ttcx,1≥ttcy,1 . . . then[, ]The collision condition I represents that the head of the vehicle and the tail corner of the parallel traffic vehicle have side-to-side collision;”; pg. 20, paragraph 4 “if ttcx,2≥ttcy,2&ttcx,1＜ttcy,1[ ]If the collision situation is a collision situation II, the collision situation is represented as that the corner of the head of the vehicle collides with the side edge of the traffic vehicle on the parallel road at the corner opposite to the side edge;”; pg. 20, paragraph 5 “if ttcx,3≥ttcy,3&ttcx,2＜ttcy,2[ ]If the collision situation is a collision situation III, the collision situation is shown, and the corner of the head of the parallel traffic vehicle and the side edge of the vehicle generate corner-to-side collision;”; pg. 20, paragraph 6 “if ttcx,4≥ttcy,4&ttcx,3＜ttcy,3[ ]If the collision situation is IV, the side-to-side collision between the head of the merging traffic vehicle and the corner of the tail of the vehicle is shown;”); and
determining a target time to collision between the ego vehicle and the target object based on the collision state and the first predicted time to collision (see Zhao at least pg. 19, paragraph 1 “. . . calculating the longitudinal collision time ttcx[ ]And time to side impact ttcy [(i.e., target time to collision, which is also the ego vehicle time to collision ttc, is based on the collision states- longitudinally and latitudinally)] . . .”).
Regarding claim 2, Zhao discloses the subject matter of claim 1 as recited in the claim and applied above. Additionally, Zhao discloses the subject matter indicated in bold below:
. . . wherein the determining a collision risk between the ego vehicle and the target object based on the first state information and the second state information comprises (see Zhao at least pg. 9, paragraph 4 “Comparing, judging whether the corner of the rectangular frame of the vehicle interferes with the parallel traffic vehicle, if a certain corner meets the requirement [(i.e., determining collision risk)] . . .”):
determining a first predicted trajectory within a preset time period for the ego vehicle based on the first state information (see Zhao at least pg. 2, paragraph 6 “predicting a discrete track of the vehicle [(i.e., ego vehicle)] in the future delta T time [(i.e., present time period)] . . . the track sequence comprises longitudinal position, transverse position, speed and orientation angle information of the vehicle relative to the current time [(i.e., first state information)] within future delta T time;”);
determining a second predicted trajectory within the preset time period for the target object based on the second state information (see Zhao at least pg. 15, paragraph 5 “predicting a merging discrete track of the merging traffic vehicle [(i.e., target object)] in the future delta T time [(i.e., present time period)]: . . . including the position, speed and orientation angle information of the merging traffic vehicle [(i.e., second state information)] in future delta T time, and converting the merging discrete track sequence into a current-time own vehicle coordinate system;”);
determining at least one second predicted time to collision between the ego vehicle and the target object based on the first predicted trajectory and the second predicted trajectory (see Zhao at least pg. 19, paragraph 1 “. . . calculating the longitudinal collision time ttcx[ ]And time to side impact ttcy [(i.e., multiple times to collision predicted)] . . .”; Equation for ttcx/y,1-4 – each time to collision determined using first and second predicted trajectories); and
determining the collision risk between the ego vehicle and the target object based on the at least one second predicted time to collision (see Zhao at least pg. 9, paragraph 4 “Comparing, judging whether the corner of the rectangular frame of the vehicle interferes with the parallel traffic vehicle, if a certain corner meets the requirement [(i.e., determining collision risk)] . . .”; Expressions for |xcorner| and |ycorner|- x and y for each corner is considered in determining collision risk).
Regarding claim 3, Zhao discloses the subject matter of claim 2 as recited in the claim and applied above. Additionally, Zhao discloses the subject matter indicated in bold below:
. . . wherein the determining the collision risk between the ego vehicle and the target object based on the at least one second predicted time to collision comprises (see Zhao at least pg. 9, paragraph 4 “Comparing, judging whether the corner of the rectangular frame of the vehicle interferes with the parallel traffic vehicle, if a certain corner meets the requirement [(i.e., determining collision risk)] . . .”; Expressions for |xcorner| and |ycorner|- x and y for each corner is considered in determining collision risk):
determining, based on the first state information, a corresponding collision avoidance state of the ego vehicle at the at least one second predicted time to collision, to obtain at least one first collision avoidance state (see Zhao at least pg. 2, paragraph 11 “. . . the self-adaptive cruise system of the automobile is communicated with the brake system and the driving system to generate proper brake pressure or engine output power, and the automobile is controlled to run to a following target of the self-adaptive cruise system at a desired acceleration to be switched to a parallel traffic vehicle or a longitudinal distance between the automobile and a front vehicle of a current lane is less than or equal to a following distance thvh。”; pg. 7, paragraph 12 “. . . if ttc is less than or equal to delta T or the judged collision situation is good, I or II, the expected braking deceleration of the self vehicle is as follows:”);
determining, based on the second state information, a corresponding collision avoidance state of the target object at the at least one second predicted time to collision, to obtain at least one second collision avoidance state (see Zhao at least pg. 3, paragraph 4“. . . assuming that the two keep constant speed straight running from the above [(i.e., collision avoidance state of target object assumed to be the same as the collision state of target object)] . . . ”; pg. 15, paragraph 5 “predicting a merging discrete track of the merging traffic vehicle [(i.e., target object)] in the future delta T time [(i.e., present time period)]: . . . including the position, speed and orientation angle information of the merging traffic vehicle [(i.e., second state information)] in future delta T time, and converting the merging discrete track sequence into a current-time own vehicle coordinate system;”); and
determining the collision risk between the ego vehicle and the target object based on the first collision avoidance state and the second collision avoidance state at the second predicted time to collision (see Zhao at least pg. 7, paragraph 6 “. . . according to the determined collision situation, calculating the corresponding collision time ttc, wherein the calculation formula is as follows:”; Equations for ttccase1-4 – In cases 1, 2, and 3, the judgment is that the remedial action taken to avoid the collision will successfully avoid collision (i.e., no collision risk), whereas in case 4, also called “crash situation iv,” the collision occurs (i.e., definite collision risk)).
Regarding claim 4, Zhao discloses the subject matter of claim 3 as recited in the claim and applied above. Additionally, Zhao discloses the subject matter indicated in bold below:
. . . wherein the determining the collision risk between the ego vehicle and the target object based on the first collision avoidance state and the second collision avoidance state at the second predicted time to collision comprises (see Zhao at least pg. 9, paragraph 4 “Comparing, judging whether the corner of the rectangular frame of the vehicle interferes with the parallel traffic vehicle, if a certain corner meets the requirement [(i.e., determining collision risk)] . . .”; Expressions for |xcorner| and |ycorner|- x and y for each corner is considered in determining collision risk):
determining a collision risk between the ego vehicle and the target object at the second predicted time to collision based on the first collision avoidance state and the second collision avoidance state at the second predicted time to collision (see Zhao at least pg. 7, paragraph 6 “. . . according to the determined collision situation, calculating the corresponding collision time ttc, wherein the calculation formula is as follows:”; Equations for ttccase1-4 – In cases 1, 2, and 3, the judgment is that the remedial action taken to avoid the collision will successfully avoid collision (i.e., no collision risk), whereas in case 4, also called “crash situation iv,” the collision occurs (i.e., definite collision risk));
in response to that there is no collision risk between the ego vehicle and the target object at each second predicted time to collision, determining that no collision will occur between the ego vehicle and the target object (see Zhao at least pg. 7, paragraph 6 “. . . according to the determined collision situation, calculating the corresponding collision time ttc, wherein the calculation formula is as follows:”; Equations for ttccase1-4 – In cases 1, 2, and 3, the judgment is that the remedial action taken to avoid the collision will successfully avoid collision (i.e., no collision risk), whereas in case 4, also called “crash situation iv,” the collision occurs (i.e., definite collision risk)); and
in response to that there is a collision risk between the ego vehicle and the target object at the at least one second predicted time to collision, determining that the collision will occur between the ego vehicle and the target object (see Zhao at least pg. 7, paragraph 6 “. . . according to the determined collision situation, calculating the corresponding collision time ttc, wherein the calculation formula is as follows:”; Equations for ttccase1-4 – In cases 1, 2, and 3, the judgment is that the remedial action taken to avoid the collision will successfully avoid collision (i.e., no collision risk), whereas in case 4, also called “crash situation iv,” the collision occurs (i.e., definite collision risk)).
Regarding claim 5, Zhao discloses the subject matter of claim 1 as recited in the claim and applied above. Additionally, Zhao discloses the subject matter indicated in bold below:
. . . wherein the in response to that the collision risk indicates that a collision will occur between the ego vehicle and the target object, determining a collision state between the ego vehicle and the target object based on the first predicted time to collision comprises (see Zhao at least pg. 7, paragraph 2 “if ttcx,1≥ttcy,1 . . . then[, ]The collision condition I represents that the head of the vehicle and the tail corner of the parallel traffic vehicle have side-to-side collision;”; pg. 7, paragraph 3 “if ttcx,2≥ttcy,2&ttcx,1＜ttcy,1[ ]If the collision situation is a collision situation II, the collision situation is represented as that the corner of the head of the vehicle collides with the side edge of the traffic vehicle on the parallel road at the corner opposite to the side edge;”; pg. 7, paragraph 4 “if ttcx,3≥ttcy,3&ttcx,2＜ttcy,2[ ]If the collision situation is a collision situation III, the collision situation is shown, and the corner of the head of the parallel traffic vehicle and the side edge of the vehicle generate corner-to-side collision;”; pg. 7, paragraph 5 “if ttcx,4≥ttcy,4&ttcx,3＜ttcy,3[ ]If the collision situation is IV, the side-to-side collision between the head of the merging traffic vehicle and the corner of the tail of the vehicle is shown;”):
determining, based on the first state information, a first center coordinate, first size information, and a first orientation angle of the ego vehicle at the first predicted time to collision (see Zhao at least pg. 8, paragraph 8 “. . . acquiring the kinematic information of a self vehicle [(i.e., ego vehicle)] and an adjacent traffic vehicle [(i.e., target object)]: . . . the course angle [(i.e., orientation angle)] . . .”; pg. 15, paragraph 6 “. . . predicting a discrete track of the vehicle 1 [(i.e., ego vehicle)] in the future delta T time: the track point is the position of the geometric center of the vehicle at the corresponding moment . . .”; pg. 14, paragraph 7 “. . . the method fully considers the traffic vehicle lane merging intention and the future possible specific driving track of the self vehicle and the lane merging traffic vehicle, and greatly improves the prediction precision of the collision in a short time by detecting the coincidence of the rectangular frames and considering the actual size of the vehicle; furthermore, the long-time collision time calculation and the collision situation judgment are carried out by considering the actual size of the vehicle . . .”); and
determining, based on the second state information, a second center coordinate, second size information, and a second orientation angle of the target object at the first predicted time to collision (see Zhao at least pg. 8, paragraph 8 “. . . acquiring the kinematic information of a self vehicle [(i.e., ego vehicle)] and an adjacent traffic vehicle [(i.e., target object)]: . . . the course angle [(i.e., orientation angle)] . . .”; pg. 15, paragraph 5 “. . . predicting a merging discrete track of the merging traffic vehicle 2 [(i.e., target object)] in the future delta T time: the track point is the position of the geometric center of the vehicle at the corresponding moment . . .”; pg. 14, paragraph 7 “. . . the method fully considers the traffic vehicle lane merging intention and the future possible specific driving track of the self vehicle and the lane merging traffic vehicle, and greatly improves the prediction precision of the collision in a short time by detecting the coincidence of the rectangular frames and considering the actual size of the vehicle; furthermore, the long-time collision time calculation and the collision situation judgment are carried out by considering the actual size of the vehicle . . .”);
determining a first bounding box of the ego vehicle based on the first center coordinate, the first size information, and the first orientation angle, and determining a second bounding box of the target object based on the second center coordinate, the second size information, and the second orientation angle (see Zhao at least pg. 17, paragraph 1 “. . . respectively calculating coordinates (x ') of four corner points of the rectangular frame [(i.e., bounding box)] of the parallel traffic vehicle 2 relative to the track point of the vehicle 1 . . .”; pg. 17, paragraph 2 “. . . corner point coordinates (x ') of traffic vehicle 2 to be merged . . . [y'corner,fl,fr,rl,rr ]Length [lh] of rectangular frame of [vehicle] 1[ ]Width wh [(i.e., corner computations use size information)] . . .”; pg. 17, paragraph 7 “. . . extracting position, speed and heading angle information of the vehicle 1 and the parallel traffic vehicle 2 when the trajectory prediction last time . . .”; Equations for ttcx-y,1-4 – The equations use the relative angle (theta) and size information (l, w) in determining bounding box corner positions for computing the time to collision);
determining a positional relationship between the first bounding box and the second bounding box (see Zhao at least pg. 13, paragraph 1 “. . . in the above formula, xk、yk、vxk、vyk[ ]Respectively the longitudinal relative distance, the transverse relative distance, the longitudinal relative speed and the transverse relative speed of the merging traffic vehicle 2 and the self-vehicle 1 . . .”); and
determining the collision state between the ego vehicle and the target object based on the positional relationship, the first orientation angle, and the second orientation angle (see Zhao at least pg. 7, paragraph 2 “if ttcx,1≥ttcy,1 . . . then[, ]The collision condition I represents that the head of the vehicle and the tail corner of the parallel traffic vehicle have side-to-side collision;”; pg. 7, paragraph 3 “if ttcx,2≥ttcy,2&ttcx,1＜ttcy,1[ ]If the collision situation is a collision situation II, the collision situation is represented as that the corner of the head of the vehicle collides with the side edge of the traffic vehicle on the parallel road at the corner opposite to the side edge;”; pg. 7, paragraph 4 “if ttcx,3≥ttcy,3&ttcx,2＜ttcy,2[ ]If the collision situation is a collision situation III, the collision situation is shown, and the corner of the head of the parallel traffic vehicle and the side edge of the vehicle generate corner-to-side collision;”; pg. 7, paragraph 5 “if ttcx,4≥ttcy,4&ttcx,3＜ttcy,3[ ]If the collision situation is IV, the side-to-side collision between the head of the merging traffic vehicle and the corner of the tail of the vehicle is shown;”; Equations for ttcx-y,1-4 – The equations use the relative angle (theta) and positions in for computing the time to collision).
Claim Rejections - 35 USC § 103
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 6-9 are rejected under 35 U.S.C. 103 as being unpatentable over Zhao in view of Eggert et al. (Eggert, J., & Puphal, T. (2017, September). Continuous risk measures for ADAS and AD. In Future Active Safety Technology Symposium.; hereinafter Eggert).
Regarding claim 6, Zhao discloses the subject matter of claim 1 as recited in the claim and applied above. Additionally, Zhao discloses the subject matter indicated in bold below:
. . . wherein the determining a target time to collision between the ego vehicle and the target object based on the collision state and the first predicted time to collision comprises (see Zhao at least pg. 19, paragraph 1 “. . . calculating the longitudinal collision time ttcx[ ]And time to side impact ttcy [(i.e., target time to collision, which is also the ego vehicle time to collision ttc, is based on the collision states- longitudinally and latitudinally)] . . .”):
obtaining at least one collision mode in the collision state, wherein the at least one collision mode corresponds to one collision corner point and one collision edge (see Zhao at least pg. 7, paragraph 2 “if ttcx,1≥ttcy,1 . . . then[, ]The collision condition I represents that the head of the vehicle and the tail corner of the parallel traffic vehicle have side-to-side collision;”; pg. 7, paragraph 3 “if ttcx,2≥ttcy,2&ttcx,1＜ttcy,1[ ]If the collision situation is a collision situation II, the collision situation is represented as that the corner of the head of the vehicle collides with the side edge of the traffic vehicle on the parallel road at the corner opposite to the side edge [(i.e., corner point and edge)];”; pg. 7, paragraph 4 “if ttcx,3≥ttcy,3&ttcx,2＜ttcy,2[ ]If the collision situation is a collision situation III, the collision situation is shown, and the corner of the head of the parallel traffic vehicle and the side edge of the vehicle generate corner-to-side collision [(i.e., corner point and edge)];”; pg. 7, paragraph 5 “if ttcx,4≥ttcy,4&ttcx,3＜ttcy,3[ ]If the collision situation is IV, the side-to-side collision between the head of the merging traffic vehicle and the corner of the tail of the vehicle is shown [(i.e., corner point and edge)];”);
determining a corresponding collision compensation time . . . for the collision mode based on the collision corner point and the collision edge corresponding to the collision mode, to obtain at least one collision compensation time (see Zhao at least pg. 7, paragraph 2 “if ttcx,1≥ttcy,1 . . . then[, ]The collision condition I represents that the head of the vehicle and the tail corner of the parallel traffic vehicle have side-to-side collision;”; pg. 7, paragraph 3 “if ttcx,2≥ttcy,2&ttcx,1＜ttcy,1[ ]If the collision situation is a collision situation II, the collision situation is represented as that the corner of the head of the vehicle collides with the side edge of the traffic vehicle on the parallel road at the corner opposite to the side edge [(i.e., corner point and edge)];”; pg. 7, paragraph 4 “if ttcx,3≥ttcy,3&ttcx,2＜ttcy,2[ ]If the collision situation is a collision situation III, the collision situation is shown, and the corner of the head of the parallel traffic vehicle and the side edge of the vehicle generate corner-to-side collision [(i.e., corner point and edge)];”; pg. 7, paragraph 5 “if ttcx,4≥ttcy,4&ttcx,3＜ttcy,3[ ]If the collision situation is IV, the side-to-side collision between the head of the merging traffic vehicle and the corner of the tail of the vehicle is shown [(i.e., corner point and edge)];”; pg. 7, paragraph 6 “. . . according to the determined collision situation, calculating the corresponding collision time ttc . . .”) . . .
determining the target time to collision based on . . . the first predicted time to collision (see Zhao at least pg. 19, paragraph 1 “. . . calculating the longitudinal collision time ttcx[ ]And time to side impact ttcy [(i.e., target time to collision, which is also the ego vehicle time to collision ttc, is based on the collision states- longitudinally and latitudinally)] . . .”).
Zhao also discloses assuming that the vehicles will continue along a straight path (see Zhao at least pg. 3, paragraph 4 “. . . assuming that the two keep constant speed straight running from the above [(i.e., collision avoidance state of target object assumed to be the same as the collision state of target object)] . . . ”)
While Zhao discloses determining a corresponding collision compensation time for the collision mode based on the collision corner point and the collision edge corresponding to the collision mode, to obtain at least one collision compensation time and determining the target time to collision based on the first predicted time to collision, it does not appear to explicitly disclose determining a corresponding collision point for the collision mode based on the collision corner point and the collision edge corresponding to the collision mode, to obtain at least one collision point nor determining the target time to collision based on the target compensation time.
Eggert teaches the subject matter underlined below:
. . . determining a corresponding collision compensation time and a corresponding collision point for the collision mode based on the future vehicle positions, to obtain at least one collision compensation time and at least one collision point (see Eggert at least Section 3.1, paragraph 1 “. . . both TP’s drive with constant longitudinal velocities v1,2. In this case, if they start driving at t with longitudinal positions l1,2, the time of collision/time of critical event will be at sE=TTC=−∆l/∆v, with ∆l :=l1−l2 and ∆v=v1−v2 [(i.e., time and point determined)].”; Figure 1- collision compensation time and points determined based on future vehicle positions (points along scene at times t, t+s1-3 for both vehicles); Equation 5- Euclidian distance (relative position between vehicles) considered for a given time t);
determining a target compensation time based on the at least one collision compensation time and the at least one collision point (see Eggert at least Section 3.1, paragraph 1 “. . . both TP’s drive with constant longitudinal velocities v1,2. In this case, if they start driving at t with longitudinal positions l1,2, the time of collision/time of critical event will be at sE=TTC=−∆l/∆v, with ∆l :=l1−l2 and ∆v=v1−v2 [(i.e., time and point determined, target compensation time same as collision time compensation time)].”; Figure 1- collision compensation time and points determined based on future vehicle positions (points along scene at times t, t+s1-3 for both vehicles); Equation 5- Euclidian distance (relative position between vehicles) considered for a given time t); and
determining the target time to collision based on the target compensation time and the first predicted time to collision (see Eggert at least Section 3.1, paragraph 1 “. . . both TP’s drive with constant longitudinal velocities v1,2. In this case, if they start driving at t with longitudinal positions l1,2, the time of collision/time of critical event will be at sE=TTC=−∆l/∆v, with ∆l :=l1−l2 and ∆v=v1−v2 [(i.e., time and point determined, target time to collision same as the target compensation time and the first predicted time to collision)].”; Figure 1- collision compensation time and points determined based on future vehicle positions (points along scene at times t, t+s1-3 for both vehicles); Equation 5- Euclidian distance (relative position between vehicles) considered for a given time t).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention with a reasonable expectation of success to have modified the determining a corresponding collision compensation time for the collision mode based on the collision corner point and the collision edge corresponding to the collision mode, to obtain at least one collision compensation time and determining the target time to collision based on the first predicted time to collision of Zhao with the determining a corresponding collision compensation time and a corresponding collision point for the collision mode based on the future vehicle positions, to obtain at least one collision compensation time and at least one collision point, determining a target compensation time based on the at least one collision compensation time and the at least one collision point, and determining the target time to collision based on the target compensation time and the first predicted time to collision as taught by Eggert to determine a corresponding collision point for the collision mode based on the collision corner point and the collision edge corresponding to the collision mode, to obtain at least one collision point and determine the target time to collision based on the target compensation time. Doing so would enable the collision prediction method to account for mathematical risk downstream, as recognized by Eggert (see Eggert at least “To quantify the risk of an accident between the ego-car and another car, the (time-varying!) spatial risk instantaneous collision event rate . . . is modelled . . .”; See section 3.3 in general- examiner notes that the section details the methodology for determining risk, which is dependent on both position and time; Equation 29- position used to determine spatial risk instantaneous collision event rate).
Regarding claim 7, Zhao and Eggert disclose the subject matter of claim 6 as recited in the claim and applied above.
While Zhao discloses determining a corresponding collision compensation time (see Zhao at least pg. 7, paragraph 6 “. . . according to the determined collision situation, calculating the corresponding collision time ttc . . .”), it does not appear to explicitly disclose determining a corresponding collision point for the collision mode based on the collision corner point and the collision edge corresponding to the collision mode, nor determining a target compensation time based on the at least one collision compensation time and the at least one collision point.
Eggert teaches the subject matter underlined below:
. . . wherein the determining a target compensation time based on the at least one collision compensation time and the at least one collision point comprises (see Eggert at least Section 3.1, paragraph 1 “. . . both TP’s drive with constant longitudinal velocities v1,2. In this case, if they start driving at t with longitudinal positions l1,2, the time of collision/time of critical event will be at sE=TTC=−∆l/∆v, with ∆l :=l1−l2 and ∆v=v1−v2 [(i.e., time and point determined, target compensation time same as collision time compensation time)].”; Figure 1- collision compensation time and points determined based on future vehicle positions (points along scene at times t, t+s1-3 for both vehicles); Equation 5- Euclidian distance (relative position between vehicles) considered for a given time t):
performing validity verification on the at least one collision point to obtain at least one valid collision point (see Eggert at least Section 3.3, paragraph 17 “The risk measure automatically approaches 0 if there are no critical events present, since then the over all escape probability approaches 1 and for an imminent critical event, the escape probability reaches 0 as there is no time left for any type of escape events in terms of avoidance behavior or similar.”; Equations 39 and 40- validation of the collision via computed risk); and
determining the target compensation time based on collision compensation time of the at least one valid collision point (see Eggert at least Section 3.1, paragraph 1 “. . . both TP’s drive with constant longitudinal velocities v1,2. In this case, if they start driving at t with longitudinal positions l1,2, the time of collision/time of critical event will be at sE=TTC=−∆l/∆v, with ∆l :=l1−l2 and ∆v=v1−v2 [(i.e., target time to collision same as the target compensation time)].”; Section 3.3, paragraph 17 “The risk measure automatically approaches 0 if there are no critical events present, since then the over all escape probability approaches 1 [(i.e., there is only a collision if there is risk of one)] and for an imminent critical event, the escape probability reaches 0 as there is no time left for any type of escape events in terms of avoidance behavior or similar.”; Figure 1- collision compensation time and points determined based on future vehicle positions (points along scene at times t, t+s1-3 for both vehicles); Equation 5- Euclidian distance (relative position between vehicles) considered for a given time t).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention with a reasonable expectation of success to have modified the determining a corresponding collision compensation time of Zhao with the determining a target compensation time based on the at least one collision compensation time and the at least one collision point comprising performing validity verification on the at least one collision point to obtain at least one valid collision point and determining the target compensation time based on collision compensation time of the at least one valid collision point as taught by Eggert to determine a target compensation time based on the at least one collision compensation time and the at least one collision point by performing validity verification on the at least one collision point to obtain at least one valid collision point and determining the target compensation time based on collision compensation time of the at least one valid collision point. The examiner supplies the same rationale for the combination of these references as supplied above with regard to claim 6.
Regarding claim 8, Zhao discloses the subject matter of claim 2 as recited in the claim and applied above.
While Zhao discloses determining a first predicted trajectory within a preset time period for the ego vehicle based on the first state information (see Zhao at least pg. 2, paragraph 6 “predicting a discrete track of the vehicle [(i.e., ego vehicle)] in the future delta T time [(i.e., present time period)] . . . the track sequence comprises longitudinal position, transverse position, speed and orientation angle information of the vehicle relative to the current time [(i.e., first state information)] within future delta T time;”), it does not appear to explicitly disclose dividing the preset time period into a preset quantity of sub-time periods, iteratively determining a corresponding trajectory segment for the sub-time periods based on the first state information, and determining the first predicted trajectory based on the corresponding trajectory segment of each sub-time period.
Eggert teaches the subject matter underlined below:
. . . dividing the preset time period into a preset quantity of sub-time periods (see Eggert at least Section 3.2, paragraph 6 “. . . the probability that two TP’s will beat the same position within a future interval around [t+s] [(i.e., preset time interval s)]. . .”; Section 3.3, paragraph 2“For an exemplary vehicle, in a sufficiently small time interval of size ∆t [(i.e., divided into sub-time periods)] the so-called instantaneous event probability . . .”);
iteratively determining a corresponding trajectory segment for the sub-time periods based on the first state information (see Eggert at least Section 4.1, paragraph 2 “At every timestep t in the simulation, a constant velocity model is used for both TP’s to predict the distance dt:t+s for future times s [(i.e., repeated iteratively)].”; Figure 1- trajectory segments determined iteratively for different timesteps); and
determining the first predicted trajectory based on the corresponding trajectory segment of each sub-time period (see Eggert at least Section 4.1, paragraph 2 “At every timestep t in the simulation, a constant velocity model is used for both TP’s to predict the distance dt:t+s [(i.e., trajectory prediction)] for future times s.”; Figure 1- trajectory segments determined iteratively for different timesteps).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention with a reasonable expectation of success to have modified the determining a first predicted trajectory within a preset time period for the ego vehicle based on the first state information of Zhao with the dividing the preset time period into a preset quantity of sub-time periods, iteratively determining a corresponding trajectory segment for the sub-time periods based on the first state information, and determining the first predicted trajectory based on the corresponding trajectory segment of each sub-time period as taught by Eggert to divide the preset time period into a preset quantity of sub-time periods, iteratively determine a corresponding trajectory segment for the sub-time periods based on the first state information, and determine the first predicted trajectory based on the corresponding trajectory segment of each sub-time period. Doing so would provide a means for evaluating more complex kinematics than Zhao enables, since Zhao assumes straight-line movement between both vehicles over a time period. By evaluating sub-periods, Eggert takes similar discrete kinematic trajectory prediction and allows non-linear trajectories to be evaluated.
Regarding claim 9, Zhao and Eggert disclose the subject matter of claim 8 as recited in the claim and applied above.
While Zhao discloses determining at least one second predicted time to collision between the ego vehicle and the target object based on the first predicted trajectory and the second predicted trajectory (see Zhao at least pg. 19, paragraph 1 “. . . calculating the longitudinal collision time ttcx[ ]And time to side impact ttcy [(i.e., target time to collision, which is also the ego vehicle time to collision ttc, is based on the collision states- longitudinally and latitudinally)] . . .”), it does not appear to explicitly disclose determining the second predicted time to collision between the ego vehicle and the target object within each sub-time period in a chronological order, until it is determined that the collision risk between the ego vehicle and the target object at one determined second predicted time to collision indicates that a collision will occur.
Eggert teaches the subject matter underlined below:
. . . determining the second predicted time to collision between the ego vehicle and the target object within each sub-time period in a chronological order, until it is determined that the collision risk between the ego vehicle and the target object at one determined second predicted time to collision indicates that a collision will occur (see Eggert at least Section 4.1, paragraph 2 “At every timestep t in the simulation, a constant velocity model is used for both TP’s to predict the distance dt:t+s [(i.e., relative position)] for future times s . . . The sequence dt:t+s represents the input for all three risk measures [(i.e., risk used to determine collision)].”; Section 3.3, paragraph 17 “. . . for an imminent critical event, the escape probability reaches 0 as there is no time left for any type of escape events in terms of avoidance behavior or similar. Fig. 4 illustrates τ0-1 as trajectory alternatives changing zt:t+s, the positional uncertainty βcoll and the procedure of integrating the survival function S(t+s;t) over the predicted time s . . .”; Figure 1- trajectory segments determined iteratively for different timesteps; Figure 4- the collision risk is preformed iteratively over each time step until the risk is highest (τ0-1)).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention with a reasonable expectation of success to have modified the determining at least one second predicted time to collision between the ego vehicle and the target object based on the first predicted trajectory and the second predicted trajectory of Zhao with the determining the second predicted time to collision between the ego vehicle and the target object within each sub-time period in a chronological order, until it is determined that the collision risk between the ego vehicle and the target object at one determined second predicted time to collision indicates that a collision will occur as taught by Eggert to determine the second predicted time to collision between the ego vehicle and the target object within each sub-time period in a chronological order, until it is determined that the collision risk between the ego vehicle and the target object at one determined second predicted time to collision indicates that a collision will occur. The examiner supplies the same rationale for the combination of these references as supplied above with regard to claim 8.
Claims 10-14 and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Zhao in view of Jung (US 20230234576 A1; hereinafter Jung).
Regarding claim 10, the subject matter of claim 10 is analogous to the subject matter of claim 1 except that it additionally recites a non-transitory computer readable storage medium, wherein the storage medium stores computer program instructions, when executed by a processor, cause the processor to implement a time to collision prediction method for a vehicle, wherein the method comprises the method steps. As such, the analysis of claim 1 is applied to claim 10.
While Zhao discloses the method executed (see claim 1), it does not appear to explicitly disclose a non-transitory computer readable storage medium, wherein the storage medium stores computer program instructions, when executed by a processor, cause the processor to implement a time to collision prediction method for a vehicle, wherein the method comprises the method steps.
Jung teaches the subject matter underlined below:
A non-transitory computer readable storage medium, wherein the storage medium stores computer program instructions, when executed by a processor, cause the processor to implement a time to collision prediction method for a vehicle, wherein the method comprises (see Jung at least [0020] “A system for evaluating a performance of an autonomous driving algorithm is provided, which may include a memory, and one or more processors connected to the memory and configured to execute one or more computer-readable programs included in the memory, in which the one or more programs may include instructions for . . .”): . . .
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention with a reasonable expectation of success to have modified the method of Zhao with the non-transitory computer readable storage medium, wherein the storage medium stores computer program instructions, when executed by a processor, cause the processor to implement a time to collision prediction method for a vehicle as taught by Jung to have a non-transitory computer readable storage medium, wherein the storage medium stores computer program instructions, when executed by a processor, cause the processor to implement a time to collision prediction method for a vehicle, wherein the method comprises the steps described above. Doing so would provide a means for executing the method steps described.
Regarding claim 11, Zhao and Jung disclose the subject matter of claim 10 as recited in the claim and applied above. The additional limitations of claim 11 are analogous to the additional limitations of claim 2. As such, the analysis of claim 2 above is applied to claim 11.
Regarding claim 12, Zhao and Jung disclose the subject matter of claim 11 as recited in the claim and applied above. The additional limitations of claim 12 are analogous to the additional limitations of claim 3. As such, the analysis of claim 3 above is applied to claim 12.
Regarding claim 13, Zhao and Jung disclose the subject matter of claim 12 as recited in the claim and applied above. The additional limitations of claim 13 are analogous to the additional limitations of claim 4. As such, the analysis of claim 4 above is applied to claim 13.
Regarding claim 14, Zhao and Jung disclose the subject matter of claim 10 as recited in the claim and applied above. The additional limitations of claim 14 are analogous to the additional limitations of claim 5. As such, the analysis of claim 5 above is applied to claim 14.
Regarding claim 19, the subject matter of claim 19 is analogous to the subject matter of claim 10 except that it additionally recites an electronic device, wherein the electronic device comprises: a memory, configured to store a computer program product. As such, the analysis of claim 1 is applied to claim 10.
While Zhao discloses the method executed (see claim 1), it does not appear to explicitly disclose an electronic device, wherein the electronic device comprises: a memory, configured to store a computer program product; and a processor, configured to execute the computer program product stored in the memory, wherein when the computer program product is executed, the processor implements a time to collision prediction method, wherein the method comprises the method steps.
Jung teaches the subject matter underlined below:
An electronic device, wherein the electronic device comprises:
A memory, configured to store a computer program product; and
a processor, configured to execute the computer program product stored in the memory, wherein when the computer program product is executed, the processor implements a time to collision prediction method, wherein the method comprises (see Jung at least [0020] “A system for evaluating a performance of an autonomous driving algorithm is provided, which may include a memory, and one or more processors connected to the memory and configured to execute one or more computer-readable programs included in the memory, in which the one or more programs may include instructions for . . .”; [0044] “In the present disclosure, a “system” may refer to at least one of a server device and a cloud device, but not limited thereto. For example, the system may include one or more server devices. In another example, the system may include one or more cloud devices. In still another example, the system may include both the server device and the cloud device operated in conjunction with each other.”): . . .
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention with a reasonable expectation of success to have modified the method of Zhao with the electronic device, wherein the electronic device comprises a memory, configured to store a computer program product, and a processor, configured to execute the computer program product stored in the memory, wherein when the computer program product is executed, the processor implements a time to collision prediction method, wherein the method comprises the steps described above. The examiner supplies the same rationale for the combination of these references as supplied above with regard to claim 10.
Regarding claim 20, Zhao and Jung disclose the subject matter of claim 19 as recited in the claim and applied above. The additional limitations of claim 20 are analogous to the additional limitations of claim 2. As such, the analysis of claim 2 above is applied to claim 20.
Claims 15-18 are rejected under 35 U.S.C. 103 as being unpatentable over Zhao in view of Jung and further in view of Eggert.
Regarding claim 15, Zhao and Jung disclose the subject matter of claim 10 as recited in the claim and applied above. The additional limitations of claim 15 are analogous to the additional limitations of claim 6. As such, the analysis of claim 6 above is applied to claim 15.
Regarding claim 16, Zhao, Jung, and Eggert disclose the subject matter of claim 15 as recited in the claim and applied above. The additional limitations of claim 16 are analogous to the additional limitations of claim 7. As such, the analysis of claim 7 above is applied to claim 16.
Regarding claim 17, Zhao and Jung disclose the subject matter of claim 11 as recited in the claim and applied above. The additional limitations of claim 17 are analogous to the additional limitations of claim 8. As such, the analysis of claim 8 above is applied to claim 17.
Regarding claim 18, Zhao, Jung, and Eggert disclose the subject matter of claim 17 as recited in the claim and applied above. The additional limitations of claim 18 are analogous to the additional limitations of claim 9. As such, the analysis of claim 9 above is applied to claim 18.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Nahata et al. (Nahata, R., Omeiza, D., Howard, R., & Kunze, L. (2021, September). Assessing and explaining collision risk in dynamic environments for autonomous driving safety. In 2021 IEEE international intelligent transportation systems conference (ITSC) (pp. 223-230). IEEE.) discloses a similar method for evaluating inter-vehicle collision risks.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to TABITHA KRESS whose telephone number is (703) 756-1763. The examiner can normally be reached MTWR 06:30-16:30 CST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Hitesh Patel can be reached at (571) 270-5442. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/TABITHA KRESS/Examiner, Art Unit 3667
/Hitesh Patel/Supervisory Patent Examiner, Art Unit 3667
10/1/26
