This invention relates generally to a method for controlling traffic using weather condition. More particularly, the present invention relates to a method for controlling traffic using weather condition and a system performing the method.
U.S. Pat. No. 10,490,066 to Green et al. discloses the use of sensor systems such as light detection and ranging (LiDAR) systems and color cameras such as red green blue (RGB) cameras to determine traffic data, such as the number of vehicles at a crossing, the number of vehicles turning, and the paths taken by the vehicles. US Patent Application Publication No. 2021/0334550 to Cho et al. discloses an artificial intelligent (AI) algorithm implemented by hardware circuit or software. The AI algorithms classify and label at least one vehicle in the image. US Patent Application Publication No. 2020/0293796 to Mohammadabadi et al. discloses machine learning algorithms being trained to compute information corresponding to an intersection such as intersection bounding boxes, coverage maps, attributes, and distances. US Patent Application Publication No. 2018/0096595 to et al. discloses detection of the presence of emergency vehicles based upon the captured audio data by performing a classification process.
Advantages of instant disclosure include adjustment of speed limit using weather condition; reduction of the number of right-angle collisions at an intersection; lower cost than those traffic controlling methods using in-ground inductive position sensors; and smoother traffic flows.
This invention discloses a method for controlling traffic at an intersection comprising three or more branches. The method comprising the steps of: capturing image data by a plurality of camera units positioned at the intersection; sending the image data to a control unit; determining from the image data a plurality of variables; and based on the plurality of variables, determining speed limits, and setting orders and durations of lights of a plurality of traffic lights positioned at the intersection.
In block 102, image data of each incoming direction (for example, each of incoming direction 272, incoming direction 274, and incoming direction 276 of
In examples of the present disclosure, license plate numbers of vehicles appeared in the videos or images may be removed by an AI algorithm. The videos or images may be used for traffic violation citations or as evidences for court proceedings. Block 102 may be followed by block 104.
In block 104, the captured image data of each incoming direction are sent to the control unit 206. Block 104 may be followed by block 106.
In block 106, the image data are processed by the control unit 206. Block 106 may be followed by block 108.
In block 108, switching-on timing, on-duration, switching-off timing, and off-duration of each light of a plurality of traffic lights 204 are predetermined. The switching-on timing, on-duration, switching-off timing, and off-duration of each light of the plurality of traffic lights 204 are then adjusted based at least on control signals sent from the control unit 206 to the plurality of traffic lights 204. For one example, each of the plurality of traffic lights comprises a red light, a yellow light, and a green light. For another example, each of the plurality of traffic lights 204 comprises a red light 242, a yellow light 244, a green light 246, and a left-turn light 248.
In examples of the present disclosure, traffic condition is sent to a cloud server 208 of
In block 402, image data of each incoming direction (for example, each of incoming direction 272, incoming direction 274, and incoming direction 276 of
In examples of the present disclosure, image data of each outgoing direction (for example, each of outgoing direction 282, outgoing direction 284, and outgoing direction 286 of
In block 404, the captured image data of each incoming direction are sent to the control unit 206. In examples of the present disclosure, the captured image data of each incoming direction and each outgoing direction are sent to the control unit 206. Block 404 may be followed by block 406.
In block 406, the image data are processed by the control unit 206. Artificial intelligent (AI) enhanced identification and classification are determined. Block 406 may be followed by block 408, block 412, or block 414.
In block 408, from the image data of each incoming direction, it is determined that an emergency vehicle 391 of
In block 410, the emergency vehicle 391 of
In block 412, from the image data of each incoming direction, a respective number of a plurality of vehicles 511 of
In examples of the present disclosure, a speed limit is determined using a weather condition. The determined speed limit is then displayed on a speed limit sign 591. In one example, the speed limit sign 591 comprises an electronic display 593. Though the electronic display 593 of
In one example, the weather condition is determined from the image data. In another example, the weather condition is from a weather station 592 (shown in dashed lines).
The respective speed of each of the plurality of vehicles 511 of
From the image data of each outgoing direction, a respective number of a plurality of outgoing vehicles 521 of
In block 414, from the image data of each incoming direction, it is determined that pedestrians 552 of
In examples of the present disclosure, the on-duration of green light will be extended by an additional time determined by an AI algorithm. This extension is applied when the AI algorithm, using captured images, detects the presence of an abnormally slow moving vehicle, e.g., having one or more flat tires, at the intersection. In examples of the present disclosure, the on-duration of a pedestrian crossing signal at a traffic light is extended by an additional time determined by an AI algorithm. This extension is applied when the AI algorithm, using captured images, detects the presence of a pedestrian at the intersection, using assistant equipment. The assistant equipment includes crutches and wheelchairs. In above examples, the traffic light condition remains unchanged until the slow moving object completes the crossing.
Block 414 may be followed by block 416.
In block 416, priority of pedestrians' and bicycles' passing the streets are determined by AI and machine learning (ML) algorithm. Based at least on the respective number of the plurality of pedestrians 552 and bicycles 554, determine a plurality of cycles of switching-on timing and on-duration of each light of a plurality of pedestrian traffic lights 562 positioned at the intersection 540. Block 416 may be followed by block 418.
In block 418, traffic light orders and durations are determined by AI and ML algorithms. Block 418 may be followed by block 402 so as to form a loop 420.
Those of ordinary skill in the art may recognize that modifications of the embodiments disclosed herein are possible. For example, a number of cameras positioned at an intersection may vary. Other modifications may occur to those of ordinary skill in this art, and all such modifications are deemed to fall within the purview of the present invention, as defined by the claims.
This patent application is a Continuation-in-part application of U.S. patent application Ser. No. 17/752,624. The Disclosure made in US Patent Application Publication No. 2023/0386329 to Qian, the Disclosure made in U.S. Pat. No. 10,490,066 to Green et al., the Disclosure made in US Patent Application Publication No. 2021/0334550 to Cho et al., the Disclosure made in US Patent Application Publication No. 2020/0293796 to Mohammadabadi et al., and the Disclosure made in US Patent Application Publication No. 2018/0096595 to Janzen et al. are hereby incorporated by reference.
Number | Date | Country | |
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Parent | 17752624 | May 2022 | US |
Child | 18942701 | US |