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 .
Status of Claims
This Office Action is in response to the application filed on 03/10/2026. Claims 1 - 20 are presently pending and are presented for examination.
Response to Arguments
3. With respect to the Applicant’s remarks, see pages 10 - 21, filed on 03/10/2026; Applicant’s “Amendment and Remarks” have been fully considered. Applicant’s remarks will be addressed in sequential order as they were presented.
4. With respect to the rejection under 35 U.S.C. 103, applicant’s “Amendment and Remarks” have been fully considered and are persuasive. The prior art of record does not appear to disclose the limitation “wherein the historical driving decision is a past instance of a driving decision implemented from a prior vehicle-to-everything (V2X) network communication;” as amended in claim 1. Therefore, this is now a 2nd non-final as mapped in the office action below.
The argument that claim 1 is not taught by Ariannezhad is not persuasive. As defined in the specification of the application that is currently being examined, the specification in paragraph [0037] defines an entity as being “Examples of the entity type may include, but are not limited to,…a transportation device (e.g., a bicycle and/or vehicle),…”. Entity is a term that is defined broadly in the specification. Ariannezhad may not explicitly state a vehicle as an entity but Ariannezhad still, according to the definition in the specification, identifies and communicates with vehicles (entities). In order for an incident risk prediction value to be generated, contextual data such as incidents, weather conditions, roadway geometry, are identified and inputted into a machine learning model [0013], [0022]. Therefore, Ariannezhad does identify contextual data and inputs and processes it into a machine learning model.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim(s) 1, 8, & 15 are rejected under 35 U.S.C. 103 as being unpatentable over US20210089938A1 (hereinafter, “Ariannezhad”), and further in view of US20190266516A1 (hereinafter, “Olabiyi”), and further in view of US20230303121A1 (hereinafter, “Kaur”), and further in view of US20220289240A1 (hereinafter, “Ucar”).
7. Regarding claims 1, 8, & 15, Ariannezhad teaches a computer-based method of connecting a vehicle to entities, the method comprising [0016]: Ariannezhad teaches Vehicle-to-Everything (V2x).
identifying one or more entity types that influenced a historical driving decision based on the historical data,… [0026], [0032] Third party services (112) may provide historical data regarding incidents, vehicle operator data, traffic data, etc. [0026]. These third-party services may be some sort of entity such other communication devices associated with other vehicles [0032]. The entity that is influencing a historical driving decision is the third-party services (112) which may be any communication device that can connect to these third-party services.
Ariannezhad does not explicitly teach …wherein the historical driving decision is a past instance of a driving decision implemented from a prior vehicle-to-everything (V2X) network communication;
However, Olabiyi teaches …wherein the historical driving decision is a past instance of a driving decision… [0047], [0050] Olabiyi teaches that a vehicle maintains historical driving information including prior driving actions, and vehicle states such as steering, braking, acceleration, turning, and trajectory information. These historical states are stored and subsequently used to predict or determine future vehicle operations. Since Olabiyi preserves prior driving actions in a database (250) for later decision making, a person of ordinary skill in the art would have understood these stored driving actions to represent historical driving decisions corresponding to previously executed vehicle maneuvers.
Ariannezhad does not explicitly teach …implemented from a prior vehicle-to-everything (V2X) network communication ([0056], [0059] – [0060] Fig. 1 – 2);
However, Kaur teaches vehicles receiving information through a V2X communications and determines or modifies its driving behavior based on that exchanged information. The disclosed V2X messages influence vehicle maneuvers such as yielding, passing, stopping, parking, or other driving actions, such that the resulting driving decision is implemented in response to information received over the V2X network. Therefore, Kaur teaches that a driving decision is generated and carried out based on a prior V2X communication, corresponding to the claimed requirement that the driving decision be implemented from a prior vehicle-to-everything (V2X) network communication.
Ariannezhad, Olabiyi, and Kaur are analogous art because Ariannezhad teaches third party services that contain historical data regarding incidents, vehicle operator data, and traffic data, to influence a historical driving decision while Olabiyi teaches storing historical states in a database and using those historical states for future decision making with vehicle operations while Kaur teaches using V2X communication to generate decisions for vehicles.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having the teachings of Olabiyi and Kaur, to modify the teachings of the Ariannezhad to include the teachings of Olabiyi and Kaur to improve future decision-making through V2X communications.
8. Ariannezhad further teaches identifying a contextual situation of one or more roadways in a geographical area based on the real-time and the historical data [0017], [0022], [0032]; A contextual situation is when the roadway has some shape or form of hazard or restriction present that makes the vehicle have to be more aware of its surroundings due to external factors and circumstances such as road hazards, traffic, pedestrians, construction, etc. Those type of contextual situations can be identified when the roadway segments are identified [0017], [0022]. Both historical data and real-time data are identified. Real-time data (208) and the historical data involved scenarios and situations based on roadways ([0032] Fig. 1). Roadways are located in geographical areas.
deriving one or more required entities for the primary vehicle to implement a driving decision on at least one roadway of the one or more roadways during a specific time period based on the identified contextual situation and the one or more entity types that influenced the historical driving decision, wherein a machine learning model correlates the identified contextual situation to the one or more entity types [0013], [0032], [0036] – [0037]; Block 402 in Figure 4 is where entities are derived since the V2X technology has to identify which third-party services (112) are to be communicated with via any communication device that can connect to these third-party services (112) [0017], [0032]. These third-party services related to deriving entities by gathering information from the real-time vehicular incident risk prediction service (116). The real-time vehicular incident risk prediction service (116) will identify vehicles at risk using a trained machine learning model. This information will then be sent to the third-party services (112) which will then derive the entity [0017] – [0018]. Communication with third-party services (112) has to be established in order to receive data in regards to the roadway for the primary vehicle that has identified the incident risk on a roadway. When an incident risk is identified, this constitutes as a contextual situation, a real-time warning is sent (408) to a user (120) in order to help the vehicle generate a driving decision. Ariannezhad doesn’t explicitly recite a driving decision being made but it would have been obvious that when a warning is sent to the user, it is inevitable that a driving decision in regards to braking, acceleration, deacceleration, or avoiding will have to be made. Contextual situations such as weather conditions, roadway geometry, and the like can be inputted into the machine learning model to train the machine learning model to more accurately produce predictions the risk of vehicular incidents occurring [0013]. Predicting vehicular incidents requires a correlation between vehicles (one or more entities) and a contextual situation to reliably produce a prediction for a vehicular incident.
creating a tailored vehicle-to-everything (V2X) network for the primary vehicle by connecting the primary vehicle to the derived one or more required entities for the identified contextual situation; and ([0032] Fig. 1 & 4) At block 402, the vehicle will receive V2X data from various communication devices associated with other vehicles, which are considered the one or more required entities, traveling on the roadway segment that are connected to these third-party services (112) via through communication devices that are connected to these third-party services (112) as well as data in relation to the incident risk that was detected. The data from the 402 block being fed to the vehicle from these various communication devices such as other vehicles (entities) in connection with the third-party services (112) is a network of information being transmitted to the vehicle tailored specifically for that vehicle as depicted in Figure 1.
causing the primary vehicle to implement the driving decision [0021], [0036]. Ariannezhad doesn’t explicitly recite a driving decision being made but it would have been obvious that when a warning is sent to the user, it is inevitable that a driving decision in regards to braking, acceleration, deacceleration, or avoiding will be made.
9. Ariannezhad further teaches receiving real-time and historical data from one or more sources… [0026], [0032]; Both historical data and real-time data are identified and collected. Real-time data (208) and the historical data involved scenarios and situations based on roadways [Fig. 1].
Ariannezhad does not explicitly teach …and an opt-in from a primary vehicle and one or more secondary vehicles, wherein the primary vehicle is an autonomous vehicle;
However, Ucar teaches …and an opt-in from a primary vehicle and one or more secondary vehicles, wherein the primary vehicle is an autonomous vehicle [0077], [0083], [0212]; Ucar teaches an ego vehicle (primary vehicle) [0083] and surrounding connected vehicles (secondary vehicles) that exchange V2X messages to enable cooperative driving behavior and trajectory planning. However, Ucar does not explicitly disclose an opt-in mechanism whereby the primary and secondary vehicles selectively authorize participation in the data-sharing framework. Instead, participation is implied through V2X communication protocols and cooperative system engagement among connected vehicles [0077], [0212].
Ariannezhad and Ucar are analogous art because Ariannezhad teaches on having V2x capabilities which helps in receiving real-time data and historical data from one or multiple sources while Ucar teaches on having an autonomous ego vehicle use V2x with other vehicles which implicitly implies that opt-in’s are included due to how communication protocols in V2X communication work. One of ordinary skill in the art would have had the motivation to combine Ariannezhad with Ucar because both address improving vehicle decision-making through the use of V2X communications in connected and autonomous driving environments. It would have been obvious to integrate the multi-source real-time and historical data ingestion framework of Ariannezhad into the cooperative autonomous vehicle system of Ucar in order to enhance the ego vehicle’s decision-making using richer contextual information derived from both past and present V2X data. Such a combination would have predictably resulted in an autonomous vehicle system that receives real-time and historical data from multiple participating vehicles within a V2x network, where participation is governed by communication protocols that require vehicles to engage in data exchange.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having the teachings of Ucar to modify the teachings of Ariannezhad to include the teachings of Ucar to have more information that can be transmitted over in a scenario where the related vehicles can send over more useful information if opted-in.
Claim(s) 2 & 9 are rejected under 35 U.S.C. 103 as being unpatentable over US20210089938A1 (hereinafter, “Ariannezhad”), and further in view of US20190266516A1 (hereinafter, “Olabiyi”), and further in view of US20230303121A1 (hereinafter, “Kaur”), and further in view of US20220289240A1 (hereinafter, “Ucar”), and further in view of US20220039082A1 (hereinafter, “Belleschi”).
11. Regarding claims 2 & 9, the modified Ariannezhad reference does not explicitly teach the computer-based method of claim 1, further comprising: determining whether at least one required entity is duplicated; and in response to determining whether the at least one required entity is duplicated, deduplicating the at least one duplicated required entity by connecting the at least one duplicated required entity to only one vehicle.
However, Belleschi in the same field of endeavor, teaches the computer-based method of claim 1, further comprising: determining whether at least one required entity is duplicated; and in response to determining whether the at least one required entity is duplicated, deduplicating the at least one duplicated required entity by connecting the at least one duplicated required entity to only one vehicle [0057], [0089]. A user equipment (UE), a vehicle from a platoon, is connected to an evolved node B (eNB) which provides coverage for a specific geographic area. The eNB is a cellular network base station, the entity. The whole pool of UEs are then connected to the eNB. This means the whole platoon is connected the same eNB. The entity, eNB is duplicated in this instance since it is communicating with all of the vehicles in the platoon. The second option Belleschi teaches, has it to where only one vehicle in the platoon is in charge of sending a request [0089]. Therefore, all the vehicles that were connected to the eNB are now deduplicated and now the vehicle leader of the platoon is the only vehicle connected to the eNB.
One of ordinary skill in the art, before the effective filing date of the instant application with a reasonable expectation of success, would have been motivated to modify the disclosure of the modified Ariannezhad reference with the teachings of Belleschi, to prevent gathering extra information that is already received due to being connected to the same entity.
Claim(s) 3, 10, & 17 are rejected under 35 U.S.C. 103 as being unpatentable over US20210089938A1 (hereinafter, “Ariannezhad”), and further in view of US20190266516A1 (hereinafter, “Olabiyi”), and further in view of US20230303121A1 (hereinafter, “Kaur”), and further in view of US20220289240A1 (hereinafter, “Ucar”), and further in view of US20210185484A1 (hereinafter, “Zhou”), and further in view of US20220039082A1 (hereinafter, “Belleschi”).
13. Regarding claims 3, 10, & 17, the modified Ariannezhad reference does not explicitly teach the computer-based method of claim 2, wherein the deduplicating further comprises: disconnecting the at least one duplicated required entity from each vehicle except for the primary vehicle, and wherein in response to determining the primary vehicle is unable to maintain the connection, reconnecting the at least one deduplicated required entity to exactly one secondary vehicle.
Zhou teaches the computer-based method of claim 2, wherein the deduplicating further comprises: disconnecting the at least one…and wherein in response to determining the primary vehicle is unable to maintain the connection, reconnecting…to exactly one secondary vehicle [0021], [0038]. When a primary vehicle is out of a region and the connection to that vehicle begins to weaken due to the connectivity range starting to exceed limits, the V2X-C node will be disconnected essentially from that primary vehicle and reconnected/allocated to another node which would be a secondary vehicle.
The modified Ariannezhad reference does not explicitly teach …duplicated required entity from each vehicle except for the primary vehicle,…the at least one deduplicated required entity…
However, Belleschi teaches …duplicated required entity from each vehicle except for the primary vehicle,…the at least one deduplicated required entity… [0057], [0089]. A user equipment (UE), a vehicle from a platoon, is connected to an evolved node B (eNB) which provides coverage for a specific geographic area. The eNB is a cellular network base station, the entity. The whole pool of UEs are then connected to the eNB. This means the whole platoon is connected the same eNB. The entity, eNB is duplicated in this instance since it is communicating with all of the vehicles in the platoon. The second option Belleschi teaches, has it to where only one vehicle in the platoon is in charge of sending a request [0089]. Therefore, all the vehicles that were connected to the eNB are now deduplicated and now the vehicle leader of the platoon is the only vehicle connected to the eNB.
Zhou and Belleschi are analogous art to Ariannezhad because Zhou teaches on disconnecting a vehicle from a node and reconnecting that node to a secondary vehicle while Belleschi teaches on having UEs (vehicles) connected to an eNB and deduplicating all the UEs from the eNB except for the vehicle leader.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having the teachings of Zhou and Belleschi to modify the teachings of the modified Ariannezhad reference to include the teachings of Zhou and Belleschi to further have a backup plan that can preserve that same information by handing it over to another vehicle.
Claim(s) 4, 11, & 18 are rejected under 35 U.S.C. 103 as being unpatentable over US20210089938A1 (hereinafter, “Ariannezhad”), and further in view of US20190266516A1 (hereinafter, “Olabiyi”), and further in view of US20230303121A1 (hereinafter, “Kaur”), and further in view of US20220289240A1 (hereinafter, “Ucar”), and further in view of US20210112388A1 (hereinafter, “Rosales”).
15. Regarding claims 4, 11, & 18, Ariannezhad teaches the computer-based method of claim 1, wherein connecting the primary vehicle to the one or more required entities for the identified contextual situation further comprises:
continuously monitoring for changes in the identified contextual situation… [0037]. Ariannezhad mentions that the indicia displayed may change as the vehicle travels along a roadway segment. The change in the display of the risk level is an indication that the incident risk that was detected is being monitored continuously. In order for a change in the risk level to occur, some sort of monitoring of the incident risk (contextual situation) has to occur to know what about the incident risk has changed. Also due to how the vehicle receives data from the V2X network that was created for the vehicle to receive information on the incident risk, the source that is transmitting said information on the incident risk has to be altered in order to transmit the updated information to the vehicle so that it can display the now altered risk level to the user.
The modified Ariannezhad reference does not explicitly teach …and altering the one or more required entities in the V2X network in accordance with the updated contextual situation
However, Rosales teaches …and altering the one or more required entities in the V2X network in accordance with the updated contextual situation [0017], [0029]. Broadest reasonable interpretation (BRI) of altering means changing in some form the required entities. The entities being the vehicles that are connected to the V2X network. Rosales teaches on assigning or relocating vehicles to detected gaps. These gaps are spaces on the roadway where no information is currently being taken. These gaps that are lacking information can be a safety hazard to vehicles so therefore these gaps can be considered a contextual situation due to the lack of information on the area. The gap could potentially contain a hazard of some sort. To prevent these gaps, vehicles are assigned routes or relocated to fill in these gaps. The relocation or reassigning is the altering of the one or more required entities in the V2X network.
Ariannezhad and Rosales are analogous art because Ariannezhad teaches on monitoring an incident risk and adjusting a risk level while Rosales teaches on relocating or reassigning vehicles to fill in gaps.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having the teachings of Rosales to modify the teachings of Ariannezhad as modified by Lektutai to include the teachings of Rosales to effectively relocate or reassign vehicles to fill in gaps that potentially may be hazardous to other vehicles and provide more safety.
Claim(s) 5, 12, & 19 are rejected under 35 U.S.C. 103 as being unpatentable over US20210089938A1 (hereinafter, “Ariannezhad”), and further in view of US20190266516A1 (hereinafter, “Olabiyi”), and further in view of US20230303121A1 (hereinafter, “Kaur”), and further in view of US20220289240A1 (hereinafter, “Ucar”), and further in view of US20200307578A1 (hereinafter, “Magolan”).
17. Regarding claims 5, 12, & 19, the modified Ariannexhad reference does not explicitly teach the computer-based method of claim 1, wherein causing the primary vehicle to implement the driving decision further comprises: controlling the primary vehicle to reduce a speed of the primary vehicle in response to detecting a problem condition.
However, Magolan in the same field of endeavor, teaches the computer-based method of claim 1, wherein causing the primary vehicle to implement the driving decision further comprises: controlling the primary vehicle to reduce a speed of the primary vehicle in response to detecting a problem condition ([0015] – [0016], [0018], Fig. 3 – 4). Magolan doesn’t explicitly recite that vehicle speed is reduced when a vehicle can’t connect to any sort of entity. Although, the specification discloses that the vehicle is configured to communicate with other vehicles within a threshold proximity [0049] and also to a wireless network [0015]. Magolan also teaches on having V2x capabilities [0049]. Magolan further discusses that the top speed of a vehicle may be limited due to ambient conditions such as traction, reduced visibility [0006], or being within a geofenced area [0018]. Given that this system relies on wireless communications to obtain condition data, a person of ordinary skill in the art would have recognize that losing such communications is itself a condition that reduces the vehicle’s ability to respond to hazards. It would have been a routine design decision to include some sort of module that detects whether communications were unavailable and the vehicle could not connect to any sort of entity, a problem condition, and to reduce the vehicle’s top speed when this situation occurs as a fallback safe mode. This modification aligns with the safety objective of the invention. Accordingly, incorporating the fallback safe mode of reducing the vehicle’s top speed upon connectivity loss would have been obvious from the disclosure.
One of ordinary skill in the art, before the effective filing date of the instant application with a reasonable expectation of success, would have been motivated to modify the disclosure of the modified Ariannezhad reference with the teachings of Magolan, to further add safety to the vehicle when no communication with any sort of entity can be established.
Claim(s) 6, 13, & 20 are rejected under 35 U.S.C. 103 as being unpatentable over US20210089938A1 (hereinafter, “Ariannezhad”), and further in view of US20190266516A1 (hereinafter, “Olabiyi”), and further in view of US20230303121A1 (hereinafter, “Kaur”), and further in view of US20220289240A1 (hereinafter, “Ucar”), and further in view of US20200307578A1 (hereinafter, “Magolan”), and further in view of US20210213869A1 (hereinafter, “Martin”).
19. Regarding claims 6, 13, & 20, the modified Ariannezhad reference does not explicitly teach the computer-based method of claim 5, wherein the speed of the primary vehicle is reduced in response to determining the primary vehicle is unable to connect to at least one required entity.
However, Martin in the same field of endeavor, teaches the computer-based method of claim 5, wherein the speed of the primary vehicle is reduced in response to determining the primary vehicle is unable to connect to at least one required entity [0074]. Martin teaches a vehicle management system (200) that can perform certain safety checks and safety commands. A variety of safety parameters can be configured into this vehicle management system (200). A safety function of a vehicle being separated from another vehicle a certain distance can be implemented where if a vehicle (an entity) is a certain distance away from another vehicle, an operation of slowing down can be incorporated by the motion planning and control later (214). This may not be specifically a scenario where the vehicle is unable to connect to the entity, but it would’ve been obvious to implement a safety parameter where if the vehicle’s distance exceeds a certain specified distance and can no longer connect to the other entity to have the vehicle slow down as a safety precaution. This safety parameter is already incorporated, just not to the level where the separation between a vehicle and an entity are unable to connect to each other. This is even more obvious because of the fact that Martin can store a variety of safety parameters which the user may specify or implement.
One of ordinary skill in the art, before the effective filing date of the instant application with a reasonable expectation of success, would have been motivated to modify the disclosure of the modified Ariannezhad reference with the teachings of Martin, to further add safety to the vehicle when no communication with any sort of entity can be established.
Claim(s) 7 & 14 are rejected under 35 U.S.C. 103 as being unpatentable over US20210089938A1 (hereinafter, “Ariannezhad”), and further in view of US20190266516A1 (hereinafter, “Olabiyi”), and further in view of US20230303121A1 (hereinafter, “Kaur”), and further in view of US20220289240A1 (hereinafter, “Ucar”), and further in view of US20200307578A1 (hereinafter, “Magolan”), and further in view of US20170268896A1 (hereinafter, “Bai”).
21. Regarding claims 7 & 14, the modified Ariannezhad reference does not explicitly teach the computer-based method of claim 5, wherein the speed of the primary vehicle is reduced in response to determining the identified contextual situation is unable to be associated with the historical driving decision.
However, Magolan teaches the computer-based method of claim 5, wherein the speed of the primary vehicle is reduced… [0018] - [0019] Magolan mentions incorporating a speed limiter into the plurality of vehicles. Under certain conditions, this speed limiter may be used to reduce the vehicle top speed to a lower, limited speed.
The modified Ariannezhad reference does not explicitly teach …in response to determining the identified contextual situation is unable to be associated with the historical driving decision.
However, Bai teaches …in response to determining the identified contextual situation is unable to be associated with the historical driving decision [0088]. Bai teaches on a comparison calculator (420) that can match current event data such as a contextual situation to historical event data. If the comparison calculator doesn’t find a match of a new event data to a historical event data, then that new event data gets stored for future statistical analysis for future vehicles that may encounter that same new event data. Therefore, the new event data which constitutes as a contextual situation was unable to be associated with any historical data. This historical data may also include historical driving decisions [0005].
Magolan and Bai are analogous art to Ariannezhad because Magolan teaches on implementing a speed limiter into a vehicle that operates and reduces a vehicle’s speed under certain conditions while Bai teaches on being unable to associate a historical driving decision to new event data. Incorporating a speed limiter and limiting the speed of a vehicle under uncertain situational awareness such as being unable to associate a historical driving decision to new event data is a motivation to combine both these teachings together. Therefore, combining these references together to achieve speed reduction in response to an inability to associate the current situation with historical driving decision would’ve been obvious.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having the teachings of Magolan and Bai to modify the teachings of the modified Ariannezhad reference to include the teachings of Magolan and Bai to further add safety to the vehicle when no historical data related to a driving decision can be associated with a contextual situation.
Conclusion
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/DAVID MESQUITI OVALLE/Examiner, Art Unit 3669
/Erin M Piateski/Supervisory Patent Examiner, Art Unit 3669
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