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 .
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.
Claim(s) 1-3, 5-12, 14-18 are rejected under 35 U.S.C. 103 as being unpatentable over Vandenberg (2018/0284770) in view of Rosales (2020/00184811).
Regarding applicant claim 1, Vandenberg teaches: A system for traffic management (see Vandenberg fig. 1 and [0037], [0051]-[0052] regarding a system for addressing traffic anomalies) comprising:
at least one sensor configured to detect information on road users in a segment of a road (see Vandenberg fig. 1 and [0051]-[0055] regarding the collection of data regarding the movement of vehicles in a geographic area); and
at least one processor (see Vandenberg fig. 1 and [0051] regarding operations computing system 104 comprising one or more computing devices 134) configured to:
receive the detected information from the at least one sensor (see Vandenberg [0051]-[0055]):
detect autonomous vehicles of the road users (see Vandenberg [0064] where computing device(s) 134 can select a plurality of autonomous vehicles to address a traffic anomaly, which requires the computing device(s) to detect and determine autonomous vehicles in the geographic area):
determine from the detected information at least one of location. speed and direction of each of said road users (see Vandenberg [0051]-[0055]); and
based on the detected autonomous vehicles and the at least one of location, speed and direction and on a set of traffic management rules, generate and selectively send a control signal comprising a driving instruction communicated to a communication device of each one or some of said autonomous vehicles, wherein the driving instruction is selected from the group of driving instructions consisting of: drive at a certain speed, stop, slow down, accelerate, turn, perform a collision prevention action, drive in a certain lane, change lanes, initiate a full emergency brake, steer by a certain angle, and steer by a certain direction (see Vandenberg [0056]-[0057] and [0059]-[0060] where computing device 134 generates a profile 138 that can help a vehicle operate in a manner that effectively addresses a traffic anomaly and where the profile can include vehicle actions such as managing vehicle speed (e.g. constant, accelerating, decelerating). See also [0064] where the computing device then selects one or more autonomous vehicles to address the traffic anomaly and [0068] where the profile is used by the autonomous vehicle to address the anomaly. As explained in [0019], traffic anomalies can include situations such as stop-and-go traffic snake, gridlock, phantom intersections. Therefore, it can be seen that the system in Vandenberg utilizes a set of traffic management rules. See also [0062]-[0063] regarding the detection of an existence of a traffic anomaly based on the traffic data, such as a vehicle being stuck at an intersection (which is based on the speed of a vehicle as determined using the sensors). Therefore, it can be seen that the profile, i.e. commands, that is communicated to the autonomous vehicles is based on the detection of the autonomous vehicles, the at least one of location, speed and direction of the vehicles and a set of traffic rules),
wherein and said at least one processor are located away from any of the detected autonomous vehicles (see fig. 1 showing computing device 134 being located away from the vehicles. See also [0051]).
Vandenberg teaches where the traffic data can be received from a traffic monitoring service, which is external to the vehicles, but does not specifically state that it receives data from a sensor that is located away from any vehicles.
Rosales teaches where traditional traffic monitoring services have included the use of video cameras installed on roads (see Rosales [0002]-[0003]), i.e. sensors located away from the vehicles. It would therefore have been obvious to one of ordinary skill in the art that the traffic data received from traffic monitoring service in Vandenberg could be collected using the traditional use of video cameras.
Regarding applicant claim 2, Vandenberg discloses wherein said at least one processor is configured to receive travel-related information from each of the autonomous vehicles ([0006] “autonomous vehicles include one or more processors).
Regarding applicant claim 3, Vandenberg discloses wherein the control signal comprises direct traffic management action ([0056]-[0057] and [0059]-[0060]; [0064])
Regarding applicant claim 5, Vandenberg discloses wherein said at least one sensor is selected from the group of sensors consisting of: electromagnetic sensors, image capturing sensors, light sensors, receivers configured to detect electromagnetic emissions, sensors configured to detect autonomous vehicles in the area of interest ([0021] “LIDAR, RADAR, cameras, ultrasonic sensors”).
Regarding applicant claim 6, Vandenberg discloses wherein the at least one processor is configured to predict possible collision between two or more of the road users, and wherein the control signal is a collision avoidance action signal to at least one of said two or more of the autonomous vehicles to avoid the possible collision ([0021]; [0069]).
Regarding applicant claim 7, Vandenberg discloses wherein the collision avoidance action is selected form the group of actions consisting of: altering a state of a traffic signal, sending a warning message, sending a control signal to automatically cause a change in at least one operational aspect of one of the two or more of the road users ([0021] “autonomous vehicle… can gather sensor data associated with one or more objects that are proximate to the autonomous vehicle”; [0022] “motion plan”).
Regarding applicant claim 8, Vandenberg discloses wherein the processor is configured to generate and selectively send a different control signal to different one or some of the autonomous vehicles ([0022] “perceive the surrounding environment of the autonomous vehicle and determine a motion plan for controlling the motion of the autonomous vehicle”).
Regarding applicant claim 9, Vandenberg discloses wherein the processor is configured, based on the determined at least one of location, speed and direction and on the set of traffic management rules, to generate and selectively send a control signal comprising a driving instruction communicated to the communication device of each of said one or some of the autonomous vehicles instructing that autonomous vehicle to drive at a certain speed, and to generate and selectively send another control signal comprising a driving instruction communicated to the communication device of another of said one or some autonomous vehicles instructing that other autonomous vehicle to change lane ([0022] “perceive the surrounding environment of the autonomous vehicle and determine a motion plan for controlling the motion of the autonomous vehicle”).
Regarding applicant claim 10, Vandenberg teaches: A method for traffic management (see Vandenberg fig. 1 and [0037], [0051]-[0052] regarding a system for addressing traffic anomalies) comprising:
at least one sensor configured to detect information on road users in a segment of a road (see Vandenberg fig. 1 and [0051]-[0055] regarding the collection of data regarding the movement of vehicles in a geographic area); and
at least one processor (see Vandenberg fig. 1 and [0051] regarding operations computing system 104 comprising one or more computing devices 134) configured to:
receive the detected information from the at least one sensor (see Vandenberg [0051]-[0055]):
detect autonomous vehicles of the road users (see Vandenberg [0064] where computing device(s) 134 can select a plurality of autonomous vehicles to address a traffic anomaly, which requires the computing device(s) to detect and determine autonomous vehicles in the geographic area):
determine from the detected information at least one of location. speed and direction of each of said road users (see Vandenberg [0051]-[0055]); and
based on the detected autonomous vehicles and the at least one of location, speed and direction and on a set of traffic management rules, generate and selectively send a control signal comprising a driving instruction communicated to a communication device of each one or some of said autonomous vehicles, wherein the driving instruction is selected from the group of driving instructions consisting of: drive at a certain speed, stop, slow down, accelerate, turn, perform a collision prevention action, drive in a certain lane, change lanes, initiate a full emergency brake, steer by a certain angle, and steer by a certain direction (see Vandenberg [0056]-[0057] and [0059]-[0060] where computing device 134 generates a profile 138 that can help a vehicle operate in a manner that effectively addresses a traffic anomaly and where the profile can include vehicle actions such as managing vehicle speed (e.g. constant, accelerating, decelerating). See also [0064] where the computing device then selects one or more autonomous vehicles to address the traffic anomaly and [0068] where the profile is used by the autonomous vehicle to address the anomaly. As explained in [0019], traffic anomalies can include situations such as stop-and-go traffic snake, gridlock, phantom intersections. Therefore, it can be seen that the system in Vandenberg utilizes a set of traffic management rules. See also [0062]-[0063] regarding the detection of an existence of a traffic anomaly based on the traffic data, such as a vehicle being stuck at an intersection (which is based on the speed of a vehicle as determined using the sensors). Therefore, it can be seen that the profile, i.e. commands, that is communicated to the autonomous vehicles is based on the detection of the autonomous vehicles, the at least one of location, speed and direction of the vehicles and a set of traffic rules),
wherein and said at least one processor are located away from any of the detected autonomous vehicles (see fig. 1 showing computing device 134 being located away from the vehicles. See also [0051]).
Vandenberg teaches where the traffic data can be received from a traffic monitoring service, which is external to the vehicles, but does not specifically state that it receives data from a sensor that is located away from any vehicles.
Rosales teaches where traditional traffic monitoring services have included the use of video cameras installed on roads (see Rosales [0002]-[0003]), i.e. sensors located away from the vehicles. It would therefore have been obvious to one of ordinary skill in the art that the traffic data received from traffic monitoring service in Vandenberg could be collected using the traditional use of video cameras.
Regarding applicant claim 11, Vandenberg discloses wherein said at least one processor is configured to receive travel-related information from each of the autonomous vehicles ([0006] “autonomous vehicles include one or more processors).
Regarding applicant claim 12, Vandenberg discloses wherein the control signal comprises direct traffic management action ([0056]-[0057] and [0059]-[0060]; [0064])
Regarding applicant claim 14, Vandenberg discloses wherein said at least one sensor is selected from the group of sensors consisting of: electromagnetic sensors, image capturing sensors, light sensors, receivers configured to detect electromagnetic emissions, sensors configured to detect autonomous vehicles in the area of interest ([0021] “LIDAR, RADAR, cameras, ultrasonic sensors”).
Regarding applicant claim 15, Vandenberg discloses wherein the at least one processor is configured to predict possible collision between two or more of the road users, and wherein the control signal is a collision avoidance action signal to at least one of said two or more of the autonomous vehicles to avoid the possible collision ([0021]; [0069]).
Regarding applicant claim 16, Vandenberg discloses wherein the collision avoidance action is selected form the group of actions consisting of: altering a state of a traffic signal, sending a warning message, sending a control signal to automatically cause a change in at least one operational aspect of one of the two or more of the road users ([0021] “autonomous vehicle… can gather sensor data associated with one or more objects that are proximate to the autonomous vehicle”; [0022] “motion plan”).
Regarding applicant claim 17, Vandenberg discloses wherein the processor is configured to generate and selectively send a different control signal to different one or some of the autonomous vehicles ([0022] “perceive the surrounding environment of the autonomous vehicle and determine a motion plan for controlling the motion of the autonomous vehicle”).
Regarding applicant claim 18, Vandenberg discloses wherein the processor is configured, based on the determined at least one of location, speed and direction and on the set of traffic management rules, to generate and selectively send a control signal comprising a driving instruction communicated to the communication device of each of said one or some of the autonomous vehicles instructing that autonomous vehicle to drive at a certain speed, and to generate and selectively send another control signal comprising a driving instruction communicated to the communication device of another of said one or some autonomous vehicles instructing that other autonomous vehicle to change lane ([0022] “perceive the surrounding environment of the autonomous vehicle and determine a motion plan for controlling the motion of the autonomous vehicle”).
Response to Arguments
Applicant’s arguments with respect to claim(s) 1-3, 5-12, 14-18 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Claim(s) 1-3, 5-12, 14-18 are rejected under 35 U.S.C. 103 as being unpatentable over VandenBerg (2018/0284770) in view of Rosales (2020/00184811).
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/W.L.L/ Examiner, Art Unit 3661
/PETER D NOLAN/Supervisory Patent Examiner, Art Unit 3661
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