Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 08/04/2025 previously entered.
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
Claims 3, 8, 11, and 16 previously canceled.
Claims 1-2, 4-7, 9-10, and 12-15 are amended.
Claims 1-2, 4-7, 9-10, and 12-15 are pending.
Response to Arguments
Applicant's arguments filed 12/12/2025 have been fully considered but they are not persuasive.
Applicant’s arguments regarding “preset entry angle of the target”: Applicant argues (Remarks, pp. 7–8) that Danz only discloses detecting an entry angle of the subject vehicle (10) into the oncoming lane, not a preset entry angle of the target (vehicle 14). Applicant further argues that Musk fails to disclose setting a preset entry angle of the target and generating a warning when the target moves at that angle.
The Examiner respectfully disagrees. The rejection is based on a combination of references under § 103, not on any single reference in isolation. The claim requires the controller to “set a preset entry angle of the target within the detection range.” Under KSR Int’l Co. v. Teleflex Inc., 550 U.S. 398 (2007), the combination is evaluated as follows:
Danz teaches geometric trajectory analysis to determine whether a vehicle’s path intersects the oncoming lane ([0005]–[0010], [0027]). Suzuki teaches angle-based obstacle detection and approach filtering using distance and positional tracking (Col. 10, lines 19–30). Musk teaches computing direction vectors of neighboring target vehicles (Col. 18, lines 48–50) and generating warning signals based on potential collision events (Col. 7, lines 62–66).
A person of ordinary skill in the art (POSITA), working with these three references, would understand that if: (1) geometric trajectory intersection can be computed (Danz), (2) angle-based approach gating can be applied (Suzuki), and (3) target direction vectors are available (Musk), then applying angle-based gating to a target’s approach rather than the host vehicle’s trajectory is a predictable design variation—not a patentable distinction. The applicant’s argument hinges on whether the angle pertains to the host or the target, but this is a semantic distinction, not an architectural incompatibility. The underlying concept is angle-based collision risk assessment which is collectively taught by the references.
Applicant’s arguments regarding “lateral distance becomes zero”: Applicant argues (Remarks, pp. 7–8) that none of the references disclose determining whether a lateral distance between the vehicle and the obstacle becomes zero or does not become zero.
The Examiner respectfully disagrees. “Lateral distance becomes zero” is mathematically equivalent to determining that two objects’ paths intersect—i.e., that they achieve side-by-side alignment in the lateral dimension. Danz explicitly computes whether the vehicle’s parking trajectory will cross into the oncoming lane ([0005]–[0010]), which is functionally equivalent to determining when the lateral offset between the vehicle and the oncoming lane (where the obstacle travels) reaches zero. Musk teaches computing distance vectors that inherently include lateral distance components (Col. 18, lines 48–50). Detecting when lateral offset reduces to zero is inherent in computing object trajectory intersection as taught by the combination.
Although the exact phrase “lateral distance becomes zero” does not appear in the prior art, under § 103, there is no requirement that a reference use identical terminology. It is sufficient that the prior art collectively teaches the underlying concept.
Applicant’s arguments regarding “conditional branching structure (IF lateral distance = 0 / ≠ 0)”: Applicant argues that the references fail to teach the claimed conditional logic: (1) when lateral distance becomes zero → extend tracking point; (2) when lateral distance does not become zero → set preset entry angle → generate warning.
The Examiner respectfully disagrees. The references collectively teach: computing distance between objects (Musk), computing intersection/angle (Danz, Suzuki), generating warnings (Danz, Musk), and extrapolating tracking (Suzuki). Rearranging these individually taught capabilities into the claimed conditional structure constitutes a routine programming choice. See KSR, 550 U.S. at 421 (“[T]he combination of familiar elements according to known methods is likely to be obvious when it does no more than yield predictable results.”). Applicant has not demonstrated that the specific if/else sequencing produces any unexpected technical result that would not arise from the known combination of these techniques.
For the foregoing reasons, the Applicant’s arguments are not persuasive, and the rejection under 35 U.S.C. § 103 is maintained for claims 1–2, 4–7, 9–10, and 12–15 as unpatentable over Danz (US 2007/0063874 A1) in view of Suzuki (US 9,707,959 B2) and Musk (US 10,956,755 B2).
The following claims 1 and 9 drafted by the examiner and considered to distinguish patentably over the art of record in this application, are presented to applicant for consideration:
Support for claim 1 suggested amendment is found in paragraphs [0046], [0048-0050], and [0025]:
1. (Currently amended) A system for detecting an obstacle, comprising: a detection sensor configured to;
detect a movement direction or a movement speed of a target within a detection range of a vehicle; and
form a tracking point for the detected target to track a movement of the target, wherein the tracking point corresponds to a first point in a movement direction of the target; and
a controller configured to:
when a lateral distance between the vehicle and the obstacle becomes zero, extend and track the tracking point to an outside of the detection range by a preset length based on the movement direction or the movement speed of the target being tracked;
wherein the controller is configured to extend the tracking point when the first point deviates from the detection range while a rear portion of the target remains within the detection range;
when the lateral distance between the vehicle and the obstacle does not become zero, set a preset entry angle of the target within the detection range; and
when the detection sensor detects the movement of the target at the preset entry angle, generate a warning signal.
Support for claim 9 suggested amendment is found in paragraphs [0046], [0048-0050], and [0025]:
9. (Currently amended) A method for detecting an obstacle, comprising:
detecting a movement direction or movement speed of a target within a detection range provided in a vehicle;
tracking a movement of the target by forming a tracking point for the target;
wherein the tracking point corresponds to a first point in a movement direction of the target;
when a lateral distance between the vehicle and the obstacle becomes zero, extending and tracking the tracking point to an outside of the detection range by a preset length based on the movement direction or the movement speed of the target being tracked by a detection sensor,
wherein the tracking point is extended when the first point deviates from the detection range while a rear portion of the target remains within the detection range; and
when the lateral distance between the vehicle and the obstacle does not become zero, setting a preset entry angle of the target within the detection range; and when the movement of the target at the preset entry angle is detected in the tracking of the movement of the target, generating the warning signal.
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 1-2, 4-7, 9-10, and 12-15 are rejected under 35 U.S.C. 103 as being unpatentable over Danz et al. (US 2007/0063874 A1) in view of Suzuki et al. (US 9,707,959 B2) and further in view of Musk et al. (US 10,956,755 B2).
Regarding Claims 1 and 9, Danz et al. (‘874) in view of Suzuki et al. (‘959) and Musk et al. (‘755) teaches:
Danz et al. (‘784) teaches: A system for detecting an obstacle, comprising: a detection sensor configured to:
detect a movement direction or a movement speed of a target within a detection range of a vehicle; ([0019], [0027]: “The means for determining the position of the oncoming lane in relation to the vehicle preferably has at least one ultrasonic sensor“; [0027]: “Ultrasonic sensors 24 have a sample area 26… Parked vehicles 12 as well as vehicles 14 in oncoming lane 16 are recorded within this sample area 26“).
Danz et al. (‘874) does not explicitly teach, but Suzuki et al. (‘959) teaches form a tracking point for the detected target to track a movement of the target (Col. 10, lines 27-30: “tracing the position of the stationary object or non-stationary object in the captured image with a known region tracking process, without repeatedly specifying the stationary object or non-stationary object“).
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to combine the obstacle detection system of Danz et al. (‘874) with the tracking point formation and tracking capabilities of Suzuki et al. (‘959). One would have been motivated to make this combination because both references address the common problem of vehicle obstacle detection and collision avoidance. Danz teaches ultrasonic obstacle detection during parking operations ([0027]) while Suzuki teaches enhanced object tracking using image processing (Col. 10, lines 27-30). The field of automotive safety systems commonly combines different sensor modalities to improve detection accuracy and reliability. A person of ordinary skill would have had a reasonable expectation of success in combining these teachings because both systems operate in the same automotive safety domain, both detect and track moving objects, and sensor fusion combining ultrasonic and visual detection was known in the art. The combination would simply enhance Danz’s ultrasonic detection with Suzuki’s proven tracking capabilities.
a controller configured to:
Danz et al. (‘784) teaches: when a lateral distance between the vehicle and the obstacle becomes zero, extend and track the tracking point to an outside of the detection range by a preset length based on the movement direction or the movement speed of the target being tracked; ([0020-0021]: “the dangerousness of the situation may be classified by a semi-autonomous parking system and, in the presence of a dangerous situation, automatic and timely braking may be triggered to avoid a collision“ – a zero distance is the same as measuring to a collision point and triggering the brakes to ‘avoid a collision’ which is inherently a zero distance).
Danz et al. (‘874) does not explicitly teach, but Suzuki et al. (‘959) teaches extending tracking beyond detection range (Col. 10, lines 27-30: “tracing the position of the stationary object or non-stationary object in the captured image with a known region tracking process, without repeatedly specifying the stationary object or non-stationary object“).
It would have been obvious to a person of ordinary skill in the art to enhance Danz’s collision detection system with Suzuki’s extended tracking capabilities. The motivation arises from the inherent limitations of sensor ranges – Danz’s ultrasonic sensors have limited detection ranges, and maintaining awareness of previously detected obstacles that move beyond sensor range would be a natural improvement. Suzuki specifically addresses this problem by continuing to track objects “without repeatedly specifying” them, indicating tracking continuation beyond initial detection. One of ordinary skill would expect success because Suzuki demonstrates working extended tracking technology (Col. 10, lines 27-30), and the fundamental challenge of maintaining object awareness beyond sensor range is the same whether using ultrasonic (Danz) or visual (Suzuki) detection. The predictive tracking algorithms from Suzuki could be readily applied to objects initially detected by Danz’s system.
when the lateral distance between the vehicle and the obstacle does not become zero, set a preset entry angle of the target within the detection range; and when the detection sensor detects the movement of the target at the preset entry angle, generate a warning signal.
Danz et al. (‘874) and Suzuki et al. (‘959) do not explicitly teach, but Musk et al. (‘755) teaches preset entry angle of the target (Col. 17, Fig. 5, Col. 18, lines 41-45: “In the example of FIG. 5, the bounding boxes are shown as rectangles around neighboring vehicles 511, 521, and 561. In various embodiments, a distance and direction from autonomous vehicle 501 can be determined“; Col. 18, lines 48-51: “distance vectors 513, 523, and 563 are used to annotate distance and direction of neighboring vehicles 511, 521, and 561“; and alerting, Col. 7, lines 62-66: “In some embodiments, vehicle control module 111 is used to control notification systems including warning systems to inform the driver and/or passengers of driving events such as a potential collision or the approach of an intended destination.”).
It would have been obvious to a person of ordinary skill in the art to combine the collision detection system of Danz et al. (‘874) and tracking capabilities of Suzuki et al. (‘959) with the directional analysis capabilities of Musk et al. (‘755). The motivation comes from the need for more precise collision risk assessment – while Danz detects obstacles and calculates collision trajectories, and Suzuki provides tracking, neither provides the detailed angular analysis of target approach directions that Musk teaches. Musk’s system determines “distance and direction” of neighboring vehicles (Fig. 5), providing exactly the angular information needed to enhance collision prediction accuracy. All three references operate in the automotive safety domain and address complementary aspects of obstacle detection and collision avoidance. A person of ordinary skill would have had reasonable expectation of success because: Musk demonstrates working directional analysis using “distance vectors 513, 523, and 563” to determine vehicle positions and angles; automotive safety systems routinely combine multiple sensor inputs; the angular data from Musk would enhance rather than conflict with the collision detection from Danz and tracking from Suzuki; and all three systems use compatible coordinate systems and vehicle-relative positioning that could be integrated using known techniques in automotive sensor fusion.
Regarding Claims 2 and 10, Danz et al. (‘874) in view of Suzuki et al. (‘959) and Musk et al. (‘755) teaches the system of claim 1.
Danz et al. (‘784) teaches: wherein the controller is further configured to generate the warning signal by predicting a collision point or calculating a collision time between the vehicle and the obstacle based on the movement direction and the movement speed of the target being tracked ([0010]: “In the event of the vehicle’s protrusion into the oncoming lane, a signal, which is processed by suitable means, preferably means for alerting the driver of the motor vehicle, or means for braking the vehicle is provided“; [0012]: “the means is a device for alerting the driver of the vehicle, the means for alerting the driver of the vehicle being in particular an acoustic, a visual, and/or a haptic means“).
Regarding Claims 4 and 12, Danz et al. (‘874) in view of Suzuki et al. (‘959) and Musk et al. (‘755) teaches the system of claim 2.
Danz et al. (‘874) does not explicitly teach, but Suzuki et al. (‘959) teaches wherein, when the tracking point deviates from the detection range after the warning signal is generated, the controller is further configured to extend and track the tracking point to maintain the warning signal up to a length of the extended tracking point (Col. 10, lines 27-30: “tracing the position of the stationary object or non-stationary object in the captured image with a known region tracking process, without repeatedly specifying the stationary object or non-stationary object“).
It would have been obvious to modify Danz’s warning system to include Suzuki’s extended tracking capabilities for maintaining warning signals. The motivation arises because Danz’s system generates warnings for collision risks ([0010]), but would naturally lose tracking when objects move beyond ultrasonic sensor range. Suzuki solves this exact problem by continuing to track objects “without repeatedly specifying” them, maintaining awareness beyond initial detection range. One of ordinary skill would expect success because Suzuki demonstrates functional extended tracking (Col. 10, lines 27-30), and maintaining warning signals during extended tracking is a logical application of Suzuki’s proven tracking technology to Danz’s established warning system.
Regarding Claims 5 and 13, Danz et al. (‘874) in view of Suzuki et al. (‘959) and Musk et al. (‘755) teaches the system of claim 4.
Danz et al. (‘784) teaches: wherein, when an angle of the movement direction of the target is gradually increased and an expected collision point is farther from the vehicle, the controller is further configured to terminate the warning signal at a preset first position shorter than the length of the extended tracking point ([0020-0021]: “the dangerousness of the situation may be classified by a semi-autonomous parking system and, in the presence of a dangerous situation, automatic and timely braking may be triggered to avoid a collision“).
The motivation to terminate warnings when collision risk decreases would be obvious because Danz teaches that “the dangerousness of the situation may be classified” ([0020-0021]), inherently suggesting that warnings should correspond to actual danger levels. When targets move away (farther collision point), continuing unnecessary warnings would be counterproductive. Success would be expected because Danz already demonstrates danger classification capabilities, and terminating warnings for reduced threats is a straightforward application of this existing functionality.
Regarding Claims 6 and 14, Danz et al. (‘874) in view of Suzuki et al. (‘959) and Musk et al. (‘755) teaches the system of claim 4.
Danz et al. (‘784) teaches: wherein, when an angle of the movement direction of the target is gradually increased and an expected collision point is closer to the vehicle, the controller is further configured to terminate the warning signal at a preset second position shorter than the length of the extended tracking point ([0020-0021]: “the dangerousness of the situation may be classified…in the presence of a dangerous situation, automatic and timely braking may be triggered“).
Similar to claim 5, the motivation comes from Danz’s teaching that dangerous situations trigger automatic responses ([0020-0021]). When collision points become closer, the system would logically adjust warning termination points accordingly. Success would be expected based on Danz’s demonstrated ability to classify danger levels and trigger appropriate responses.
Regarding Claims 7 and 15, Danz et al. (‘874) in view of Suzuki et al. (‘959) and Musk et al. (‘755) teaches the system of claim 2.
Danz et al. (‘784) teaches: wherein, when the speed of the target decreases and the target is stopped, the calculated predicted collision time is increased and the controller is further configured to terminate the warning signal ([0020-0021]: “the dangerousness of the situation may be classified by a semi-autonomous parking system“).
The motivation is obvious because stopped targets pose no collision risk, and continuing warnings would be counterproductive. Danz’s danger classification system ([0020-0021]) inherently suggests warnings should reflect actual risk levels. Success would be expected because detecting stopped objects and terminating unnecessary warnings is a straightforward application of Danz’s existing danger assessment capabilities.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to REMASH R GUYAH whose telephone number is (571)270-0115. The examiner can normally be reached M-F 7:30-4:30.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Vladimir Magloire can be reached at (571) 270-5144. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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REMASH R GUYAH
Examiner
Art Unit 3648C
/REMASH R GUYAH/Examiner, Art Unit 3648
/RESHA DESAI/Supervisory Patent Examiner, Art Unit 3648
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