Traffic light intelligent regulation and control system and method based on traffic big data

Abstract

The invention relates to the technical field of traffic light regulation and control, in particular to a traffic light intelligent regulation and control system and method based on traffic big data, and the system comprises an information collection module, a video processing module, an image processing module, an analysis control module and a traffic light display module. The plurality of information acquisition modules are uniformly distributed between the two traffic light display modules, and the information acquisition modules are used for acquiring video information of vehicles on the road; the video processing module is used for receiving video information and converting the video information into picture information through a frame extraction function; the image processing module is used for extracting vehicle feature information in the picture information, wherein the vehicle feature information comprises the number of vehicles, the positions of the vehicles and the lighting conditions of the vehicles; the traffic light display module comprises a straight arrow, a left-turn arrow and a right-turn arrow; the analysis control module is used for analyzing the vehicle feature information. According to the invention, a large number of follow-up straight vehicles are prevented from continuously driving to a congested road section, and the congested condition can be relieved.

Description

Technical Field

[0001] The present invention relates to the technical field of traffic light control, and in particular to a traffic light intelligent control system and method based on traffic big data. Background Art

[0002] Traffic lights are an important part of the urban traffic system, and their control methods largely determine the smoothness and safety of traffic. However, the current traffic light control methods still have some shortcomings. For example, when traffic congestion occurs on non-elevated roads in cities due to traffic accidents such as rear-end collisions, the current traffic light display system cannot accurately determine whether a traffic accident has occurred, and provide the function of determining whether to change the driving direction for subsequent vehicles at the intersection. Subsequent vehicles may continue to pour into the congested section, resulting in a larger area of ​​congestion. Summary of the invention

[0003] In view of this, the purpose of the present invention is to propose a traffic light intelligent control system and method based on traffic big data, so as to solve the problem that the current traffic light display system cannot accurately judge whether a traffic accident has occurred and provide vehicles at subsequent intersections with a judgment on whether to change the direction of travel.

[0004] Based on the above purpose, the present invention provides a traffic light intelligent control system based on traffic big data, including: an information acquisition module, a video processing module, an image processing module, an analysis and control module and a traffic light display module, wherein:

[0005] The information collection module is provided in plurality, and the plurality of information collection modules are evenly distributed between the two traffic light display modules, and the information collection module is used to obtain video information of vehicles on the road;

[0006] The video processing module is used to receive the video information and convert the video information into picture information through a frame extraction function;

[0007] The image processing module is used to extract vehicle feature information from the image information, wherein the vehicle feature information includes the number of vehicles, the location of vehicles and the lighting conditions of vehicles;

[0008] The traffic light display module includes a straight arrow, a left turn arrow and a right turn arrow, and the colors of the arrows include red, green and yellow, and one arrow corresponds to one lane;

[0009] The analysis and control module is used to analyze vehicle characteristic information. When it is determined based on the vehicle characteristic information that there is a traffic jam and a traffic accident occurs, the analysis and control module receives the vehicle characteristic information of the left road and the right road of the previous intersection of the current road. When it is determined based on the vehicle characteristic information that there is no traffic jam, the analysis and control module controls the straight arrow of the previous intersection of the current road to execute a first adjustment scheme. The first adjustment scheme includes adjusting the straight arrow originally green at the previous intersection to a gradient green arrow. The gradient green arrow indicates that there is a traffic jam ahead after going straight, and the driver determines whether to go straight according to the needs. When it is determined based on the vehicle characteristic information that there are fewer vehicles on the left road than on the right road, when the left turn arrow of the current road is green, the straight arrow is adjusted to a left turn arrow and displayed green, indicating that the driver determines whether to turn left according to the needs. When it is determined based on the vehicle characteristic information that there are more vehicles on the left road than on the right road, when the right turn arrow of the current road is green, the straight arrow is adjusted to a right turn arrow and displayed green, indicating that the driver determines whether to turn right according to the needs.

[0010] When the analysis and control module determines that the road is clear based on the real-time vehicle characteristic information, the control state of the traffic light display module is restored to the initial state.

[0011] Optionally, the analysis and control module determines that the left road is congested based on the vehicle characteristic information of the left road and the right road is not congested, and the analysis and control module controls the straight arrow of the previous intersection of the current road to execute a second adjustment scheme, and the second adjustment scheme includes adjusting the straight arrow at the previous intersection when it is originally green to a gradient green arrow, the gradient green arrow indicates that there is a traffic jam ahead, and the driver determines whether to go straight according to the needs, and when the right turn arrow is green, the straight arrow is adjusted to a right turn arrow showing green, indicating that the driver determines whether to turn right according to the needs;

[0012] The analysis and control module determines that there is no traffic jam on the left road based on the vehicle characteristic information of the left road and the right road. When there is traffic jam on the right road, the analysis and control module controls the straight arrow of the previous intersection of this road to execute the third adjustment plan. The third adjustment plan includes adjusting the original straight arrow of the previous intersection to a gradient green arrow when it is green. The gradient green arrow indicates a traffic jam ahead, and the driver determines whether to go straight according to needs. When the left turn arrow is green, the straight arrow is adjusted to a left turn arrow showing green, indicating that the driver determines whether to turn left according to needs.

[0013] Optionally, the analysis control module determines that the left road and the right road are not congested based on the vehicle feature information of the left road and the right road, and the number of through lanes is greater than or equal to 2;

[0014] When the number of through lanes is an even number, the analysis and control module controls the through arrow of the previous intersection of the road to execute the fourth adjustment scheme instead of the first adjustment scheme, the fourth adjustment scheme includes adjusting the straight arrow originally in the previous intersection to a gradient green arrow when it is green, the gradient green arrow indicates a traffic jam ahead, and the driver determines whether to go straight according to the needs, when the left turn arrow is green, half of the straight arrows near the left turn side are adjusted to the left turn arrows showing green, and the driver determines whether to turn left according to the needs, when the right turn arrow is green, half of the straight arrows near the right turn side are adjusted to the right turn arrows showing green, and the driver determines whether to turn right according to the needs, and when it is determined that the road is clear, it returns to the initial control state;

[0015] When the number of straight lanes is an odd number, the analysis and control module controls the straight arrow of the previous intersection of the road to execute the fifth adjustment scheme instead of the first adjustment scheme. The fifth adjustment scheme includes adjusting the straight arrow of the previous intersection from green to a gradient green arrow. The gradient green arrow indicates a traffic jam ahead. The driver determines whether to go straight according to the needs. When it is determined that there are fewer vehicles on the left road than on the right road, when the left turn arrow is green, the left turn arrow is close to the left turn side. The number of straight arrows is adjusted to a left turn arrow and displayed in green. n Indicates the number of straight lanes, indicating that the driver needs to determine whether to turn left. When the right turn arrow is green, close to the right turn side The straight arrow is adjusted to the right turn arrow in green, indicating that the driver can decide whether to turn right according to the needs. When it is judged that there are more vehicles on the left road than on the right road, when the left turn arrow is green, the driver should turn left. The number of straight arrows is adjusted to the left turn arrow showing green, indicating that the driver can decide whether to turn left according to the need. When the right turn arrow shows green, the right turn side is close to The straight arrow is adjusted to a right-turn arrow in green, indicating that the driver can decide whether to turn right as needed.

[0016] Optionally, when a traffic jam and a traffic accident are determined based on the vehicle characteristic information, the left-turn arrow on the left road of the previous intersection heading towards the traffic accident is adjusted from green to a gradient green arrow. The gradient green arrow indicates a traffic jam ahead after turning left, and the driver determines whether to turn left according to needs. When the straight arrow on the left lane displays green, the corresponding left-turn arrow of the left lane is adjusted to a straight arrow displays green, indicating that the driver determines whether to go straight as needed.

[0017] Optionally, when a traffic jam and a traffic accident are determined based on the vehicle characteristic information, the right-turn arrow on the right road at the previous intersection heading towards the traffic accident is adjusted from green to a gradient green arrow. The gradient green arrow indicates a traffic jam ahead after turning right, and the driver determines whether to turn right according to needs. When the straight arrow on the right lane displays green, the corresponding right-turn arrow of the right lane is adjusted to a straight arrow displays green, indicating that the driver determines whether to go straight as needed.

[0018] Optionally, the determining of traffic jam and traffic accident based on vehicle characteristic information includes, after determining that the number of vehicles exceeds a predetermined value, determining whether there are vehicles in a tilted, horizontal or reverse state, and if so, whether the hazard lights of vehicles in a tilted, horizontal or reverse state are turned on; if so, it is determined that a traffic accident has occurred.

[0019] Based on the same invention, the present invention also provides a control method of a traffic light intelligent control system based on traffic big data, including:

[0020] Obtain video information of vehicles on the road, and then transmit the video information to the video processing module, which converts the video information into image information through the frame extraction function;

[0021] Extract vehicle feature information from the image information to obtain the number of vehicles on the road, the position of the vehicle relative to the traffic markings, and the status of vehicle lights;

[0022] After judging that a traffic jam and a traffic accident have occurred based on the number of vehicles on the road, the position of the vehicles relative to the traffic markings, and the lighting of the vehicles, the vehicle characteristic information of the left and right roads of the previous intersection of the road is received;

[0023] When it is determined based on the vehicle characteristic information of the left road and the right road that there is no traffic jam, the analysis and control module controls the straight arrow of the previous intersection of the current road to execute the first adjustment scheme, wherein the first adjustment scheme includes adjusting the straight arrow originally green at the previous intersection to a gradient green arrow, when it is determined based on the vehicle characteristic information that there are fewer vehicles on the left road than on the right road, when the left turn arrow of the current road is displayed in green, the straight arrow is adjusted to a left turn arrow and displayed in green, and when it is determined based on the vehicle characteristic information that there are more vehicles on the left road than on the right road, when the right turn arrow of the current road is displayed in green, the straight arrow is adjusted to a right turn arrow and displayed in green;

[0024] After judging whether the road is clear based on real-time vehicle characteristic information, the control state of the traffic light display module is restored to the initial state.

[0025] The system obtains video information of vehicles on the road, and then transmits the video information to the video processing module. The video processing module converts the video information into image information through the frame extraction function; extracts vehicle feature information in the image information, obtains the number of vehicles on the road, the position of vehicles relative to traffic markings and the condition of vehicle lights; after judging that a traffic jam has occurred and a traffic accident has occurred based on the number of vehicles on the road, the position of vehicles relative to traffic markings and the condition of vehicle lights, receives the vehicle feature information of the left and right roads of the previous intersection of the road; when judging that there is no traffic jam based on the vehicle feature information of the left and right roads, the analysis control module controls the intersection of the road The straight arrow at the previous intersection executes the first adjustment plan, which includes adjusting the original green straight arrow at the previous intersection to a gradient green arrow; when it is judged based on vehicle characteristic information that there are fewer vehicles on the left road than on the right road, when the left turn arrow of this road displays green, the straight arrow is adjusted to a left turn arrow and displays green; when it is judged based on vehicle characteristic information that there are more vehicles on the left road than on the right road, when the right turn arrow of this road displays green, the straight arrow is adjusted to a right turn arrow and displays green; after judging based on real-time vehicle characteristic information that the road is clear, the control state of the initial traffic light display module is restored.

[0026] From the above, it can be seen that the present invention can remind the drivers behind that there is a traffic jam ahead through a gradual green arrow, and can detect whether the left road and the right road are congested. When there is no traffic jam, the straight arrow can be adjusted so that the originally straight-moving vehicles can be diverted to the left road and the right road, avoiding a large number of subsequent straight-moving vehicles from continuously driving towards the congested section, which can alleviate the congestion and improve the commuting efficiency of the diverted vehicles. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only for the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0028] Figure 1 It is a structural block diagram of the control system of an embodiment of the present invention;

[0029] Figure 2 Schematic diagram of the positional relationship among the main road, the left road and the right road according to an embodiment of the present invention. DETAILED DESCRIPTION

[0030] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with specific embodiments.

[0031] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the present invention should be understood by people with ordinary skills in the field to which the present invention belongs. The "first", "second" and similar words used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0032] like Figure 1-Figure 2 As shown, a traffic light intelligent control system and method based on traffic big data includes: an information acquisition module, a video processing module, an image processing module, an analysis and control module and a traffic light display module, wherein:

[0033] The information collection module is provided with a plurality of modules, and the plurality of modules are evenly distributed between the two traffic light display modules. The information collection module is used to obtain video information of vehicles on the road. The information collection module may include a camera, and the video information of vehicles on the road is obtained through the camera.

[0034] The video processing module is used to receive the video information and convert the video information into picture information through a frame extraction function;

[0035] The image processing module is used to extract vehicle feature information from the image information, wherein the vehicle feature information includes the number of vehicles, the location of vehicles and the lighting conditions of vehicles;

[0036] The traffic light display module includes a straight arrow, a left turn arrow and a right turn arrow, and the colors of the arrows include red, green and yellow, and one arrow corresponds to one lane;

[0037] The analysis and control module is used to analyze vehicle characteristic information. When it is determined based on the vehicle characteristic information that there is a traffic jam and a traffic accident occurs, the analysis and control module receives the vehicle characteristic information of the left road and the right road of the previous intersection of the current road. When it is determined based on the vehicle characteristic information that there is no traffic jam, the analysis and control module controls the straight arrow of the previous intersection of the current road to execute a first adjustment scheme. The first adjustment scheme includes adjusting the straight arrow of the previous intersection to a gradient green arrow when it is originally green. The gradient green arrow is an LED light representing an arrow that lights up row by row in sequence. The gradient green arrow indicates that there is a traffic jam ahead after going straight. The driver determines whether to go straight as needed. When it is determined based on the vehicle characteristic information that there are fewer vehicles on the left road than on the right road, when the left turn arrow of the current road displays green, the straight arrow is adjusted to a left turn arrow and displays green, indicating that the driver determines whether to turn left as needed. When it is determined based on the vehicle characteristic information that there are more vehicles on the left road than on the right road, when the right turn arrow of the current road displays green, the straight arrow is adjusted to a right turn arrow and displays green, indicating that the driver determines whether to turn right as needed.

[0038] When the analysis and control module determines that the road is clear based on the real-time vehicle characteristic information, the control state of the traffic light display module is restored to the initial state.

[0039] When the system is working, the information acquisition module obtains the video information of the vehicles on the road in real time, and then transmits the video information to the video processing module. The video processing module converts the video information into picture information through the frame extraction function, and then transmits the picture information to the image processing module. The image processing module extracts the vehicle feature information in the picture information to obtain the number of vehicles on the road, the position of the vehicles relative to the traffic markings and the lighting of the vehicles. When the analysis and control module determines that there is a traffic jam and a traffic accident based on the number of vehicles on the road, the position of the vehicles relative to the traffic markings and the lighting of the vehicles, the analysis and control module receives the vehicle feature information of the left road and the right road of the previous intersection of the road. When it is determined that there is no traffic jam based on the vehicle feature information of the left road and the right road, it means that the subsequent straight-going vehicles on the road can be diverted to the left road and the right road to avoid more vehicles from pouring into the congested section. In order to realize this function, the analysis and control module controls the straight arrow of the previous intersection of the road to execute the first adjustment plan. The first adjustment plan includes the original straight arrow of the current intersection. When the straight arrow is green, it is adjusted to a gradient green arrow. The gradient green arrow indicates that there is a traffic jam ahead after going straight. The driver can determine whether to go straight according to the needs. For example, although there is a traffic jam ahead, the road ahead is the location of the destination, so the driver can choose to continue going straight. If the road ahead is a road that can be bypassed, the driver can choose not to go straight and wait for subsequent adjustment plans. When it is determined based on vehicle feature information that there are fewer vehicles on the left road than on the right road, when the left turn arrow of this road is green, the straight arrow is adjusted to a left turn arrow and displays green, indicating that the driver determines whether to turn left according to the needs. At this time, the vehicle that chooses not to go straight ahead can now turn left to avoid the congested section. If you do not turn left, you can wait until the gradient green arrow lights up again and then choose to continue going straight. When it is determined based on vehicle feature information that there are more vehicles on the left road than on the right road, when the right turn arrow of this road is green, the straight arrow is adjusted to a right turn arrow and displays green, indicating that the driver determines whether to turn right according to the needs. At this time, the vehicle that chooses not to go straight ahead can now avoid the congested section by turning right.

[0040] Since navigation is rarely used on urban roads, it is not easy to detect road congestion in a timely manner, which will cause subsequent vehicles to continue to drive towards congested sections, resulting in larger congestion and affecting commuting efficiency. As can be seen from the above, in order to solve this problem, the present invention can use a gradient green arrow to remind the driver behind that there is a traffic jam ahead, and at the same time can detect whether the left and right roads are congested. When there is no traffic jam, the straight arrow can be adjusted so that the originally straight-moving vehicles can be diverted to the left and right roads, avoiding a large number of subsequent straight-moving vehicles from continuing to drive towards congested sections, which can alleviate the congestion and improve the commuting efficiency of the diverted vehicles.

[0041] At the same time, compared with the existing variable lane system design, the present invention also has some additional beneficial effects. For example, the present invention does not need to design a variable lane sign, and the existing variable lane sign is usually designed on the side of the road at a certain distance from the traffic light, and the lane change is carried out at a fixed time, which requires the driver to observe in advance. When the vehicle passes the variable lane sign, it cannot change lanes again according to the situation. The lane changing method of the present invention can change lanes in real time according to the traffic jam situation. As long as there is no traffic light on the road section, the lane change can be carried out in real time according to the situation. The driver does not need to observe other signs additionally, and only needs to look at the traffic light.

[0042] In some embodiments, the analysis control module determines that the left road is congested based on the vehicle feature information of the left road and the right road, and when the right road is not congested, the analysis control module controls the straight arrow of the previous intersection of the current road to execute a second adjustment scheme, wherein the second adjustment scheme includes adjusting the straight arrow at the previous intersection to a gradient green arrow when the straight arrow is originally green, the gradient green arrow indicates a traffic jam ahead, and the driver determines whether to go straight according to the needs, and when the right turn arrow is green, the straight arrow is adjusted to a right turn arrow to be green, indicating that the driver determines whether to turn right according to the needs;

[0043] The analysis and control module determines that there is no traffic jam on the left road based on the vehicle characteristic information of the left road and the right road. When there is traffic jam on the right road, the analysis and control module controls the straight arrow of the previous intersection of this road to execute the third adjustment plan. The third adjustment plan includes adjusting the original straight arrow of the previous intersection to a gradient green arrow when it is green. The gradient green arrow indicates a traffic jam ahead, and the driver determines whether to go straight according to needs. When the left turn arrow is green, the straight arrow is adjusted to a left turn arrow showing green, indicating that the driver determines whether to turn left according to needs.

[0044] As can be seen from the above, when it is detected that one of the left road and the right road is congested, only the straight-moving vehicles on this road are diverted to the road without traffic jam between the left road and the right road.

[0045] In some embodiments, the analysis control module determines based on the vehicle characteristic information of the left road and the right road that the left road and the right road are not congested, and the number of through lanes is greater than or equal to 2;

[0046] When the number of through lanes is an even number, the analysis and control module controls the through arrow of the previous intersection of the road to execute the fourth adjustment scheme instead of the first adjustment scheme, the fourth adjustment scheme includes adjusting the straight arrow originally in the previous intersection to a gradient green arrow when it is green, the gradient green arrow indicates a traffic jam ahead, and the driver determines whether to go straight according to the needs, when the left turn arrow is green, half of the straight arrows near the left turn side are adjusted to the left turn arrows showing green, and the driver determines whether to turn left according to the needs, when the right turn arrow is green, half of the straight arrows near the right turn side are adjusted to the right turn arrows showing green, and the driver determines whether to turn right according to the needs, and when it is determined that the road is clear, it returns to the initial control state;

[0047] When the number of straight lanes is an odd number, the analysis and control module controls the straight arrow of the previous intersection of the road to execute the fifth adjustment scheme instead of the first adjustment scheme. The fifth adjustment scheme includes adjusting the straight arrow of the previous intersection from green to a gradient green arrow. The gradient green arrow indicates a traffic jam ahead. The driver determines whether to go straight according to the needs. When it is determined that there are fewer vehicles on the left road than on the right road, when the left turn arrow is green, the left turn arrow is close to the left turn side. The number of straight arrows is adjusted to a left turn arrow and displayed in green. n Indicates the number of straight lanes, indicating that the driver needs to determine whether to turn left. When the right turn arrow is green, close to the right turn side The straight arrow is adjusted to the right turn arrow in green, indicating that the driver can decide whether to turn right according to the needs. When it is judged that there are more vehicles on the left road than on the right road, when the left turn arrow is green, the driver should turn left. The number of straight arrows is adjusted to the left turn arrow showing green, indicating that the driver can decide whether to turn left according to the need. When the right turn arrow shows green, the right turn side is close to The straight arrow is adjusted to a right-turn arrow in green, indicating that the driver can decide whether to turn right as needed.

[0048] In this embodiment, when there are a large number of through lanes, if all vehicles on the through lanes are diverted to the left road or the right road, the traffic volume on the left road or the right road may suddenly increase, affecting commuting efficiency. To solve this problem, when the number of through lanes is greater than or equal to 2 and the number of through lanes is an even number, when the lane is congested but the left and right roads are not, the vehicles on the left half of the through lanes are diverted to the left road, and the vehicles on the right half of the through lanes are diverted to the right road;

[0049] When the number of through lanes is greater than or equal to 2, and the number of through lanes is an odd number, when there is a traffic jam in this lane, but there is no traffic jam on the left and right roads, and there are fewer vehicles on the left road than on the right road, the left lane will be The number of vehicles on the through lane is diverted to the left road, For example, if there are 3 straight lanes, the vehicles on the left 2 straight lanes will be diverted to the left road, and the vehicles on the right 1 straight lane will be diverted to the right road. When there is a traffic jam in this lane, but there are no traffic jams on the left and right roads, and there are more vehicles on the left road than on the right road, the right road will be diverted. The number of vehicles on the through lane is diverted to the right road, For example, if the number of straight lanes is 3, the vehicles on the two right straight lanes are diverted to the right road, and the vehicles on the one left straight lane are diverted to the left road.

[0050] From the above, it can be seen that when there are a large number of straight lanes, the number of straight lanes can be distributed differently, so that part of the traffic is diverted to the left road and part of the traffic is diverted to the right road. This can reduce the impact on the left road or the right road after the diversion and ensure commuting efficiency.

[0051] In some embodiments, when a traffic jam and a traffic accident are determined based on vehicle characteristic information, the left-turn arrow on the left road of the previous intersection heading towards the traffic accident is adjusted from green to a gradient green arrow. The gradient green arrow indicates a traffic jam ahead after turning left, and the driver determines whether to turn left according to needs. When the straight arrow on the left lane is green, the corresponding left-turn arrow of the left lane is adjusted to a straight arrow showing green, indicating that the driver determines whether to go straight according to needs.

[0052] Cars turning left on the left road will also drive into the congested section of this road. In order to further divert vehicles, the left-turn arrow on the left road of the previous intersection heading towards a traffic accident will be adjusted from green to a gradient green arrow. The gradient green arrow indicates a traffic jam ahead after turning left, which can serve as a reminder to the driver. When the straight-ahead arrow on the left lane is green, the corresponding left-turn arrow on the left lane is adjusted to a straight-ahead arrow showing green, indicating that you can go straight and achieve diversion. This can further reduce the occurrence of large-scale congestion.

[0053] In some embodiments, when a traffic jam and a traffic accident are determined based on vehicle characteristic information, the right-turn arrow on the right road of the previous intersection heading towards the traffic accident is adjusted from green to a gradient green arrow. The gradient green arrow indicates a traffic jam ahead after turning right, and the driver determines whether to turn right according to needs. When the straight arrow on the right lane displays green, the right-turn arrow corresponding to the right lane is adjusted to a straight arrow displayed green, indicating that the driver determines whether to go straight according to needs.

[0054] Cars turning right on the right road will also drive into the congested section of this road. In order to further divert vehicles, the right-turn arrow on the right road of the previous intersection heading towards the traffic accident will be adjusted from green to a gradient green arrow. The gradient green arrow indicates a traffic jam ahead after turning right, which can serve as a prompt to the driver. When the straight-ahead arrow on the right lane is green, the corresponding right-turn arrow on the right lane is adjusted to a straight-ahead arrow showing green, indicating that you can go straight and achieve diversion. This can further reduce the occurrence of large-scale congestion.

[0055] In some embodiments, the determination of traffic jam and traffic accident based on vehicle characteristic information includes, after determining that the number of vehicles in the image information exceeds a predetermined value, determining whether there are any vehicles in a tilted, horizontal or reverse state, and if so, determining whether the vehicles in the tilted, horizontal or reverse state have their hazard lights turned on, and if so, determining that a traffic accident has occurred. After a traffic accident occurs, traffic usually cannot be quickly restored to normal within a short period of time, and a subsequent adjustment plan is initiated at this time.

[0056] In order to further implement the present invention, the present invention also provides a control method of a traffic light intelligent control system based on traffic big data, comprising:

[0057] Obtain video information of vehicles on the road, and then transmit the video information to the video processing module, which converts the video information into image information through the frame extraction function;

[0058] Extract vehicle feature information from the image information to obtain the number of vehicles on the road, the position of the vehicle relative to the traffic markings, and the status of vehicle lights;

[0059] After judging that a traffic jam and a traffic accident have occurred based on the number of vehicles on the road, the position of the vehicles relative to the traffic markings, and the lighting of the vehicles, the vehicle characteristic information of the left and right roads of the previous intersection of the road is received;

[0060] When it is determined based on the vehicle characteristic information of the left road and the right road that there is no traffic jam, the analysis and control module controls the straight arrow of the previous intersection of the current road to execute the first adjustment scheme, wherein the first adjustment scheme includes adjusting the straight arrow originally green at the previous intersection to a gradient green arrow, when it is determined based on the vehicle characteristic information that there are fewer vehicles on the left road than on the right road, when the left turn arrow of the current road is displayed in green, the straight arrow is adjusted to a left turn arrow and displayed in green, and when it is determined based on the vehicle characteristic information that there are more vehicles on the left road than on the right road, when the right turn arrow of the current road is displayed in green, the straight arrow is adjusted to a right turn arrow and displayed in green;

[0061] After judging whether the road is clear based on real-time vehicle characteristic information, the control state of the traffic light display module is restored to the initial state.

[0062] This method can use a gradient green arrow to remind the driver behind that there is a traffic jam ahead, and can also detect whether the left and right roads are congested. When there is no traffic jam, the straight arrow can be adjusted so that the vehicles that were originally going straight can be diverted to the left and right roads, avoiding a large number of subsequent straight vehicles from continuing to drive towards the congested section, which can alleviate the congestion and improve the commuting efficiency of the diverted vehicles to avoid traffic jams.

[0063] It should be understood by those skilled in the art that the discussion of any of the above embodiments is merely illustrative and is not intended to imply that the scope of the present invention (including the claims) is limited to these examples. Under the concept of the present invention, the technical features in the above embodiments or different embodiments may be combined, the steps may be implemented in any order, and there are many other variations of the above aspects of the present invention, which are not provided in detail for the sake of simplicity.

[0064] The present invention is intended to cover all such substitutions, modifications and variations that fall within the broad scope of the appended claims. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A traffic light intelligent control system based on traffic big data, characterized in that: include: Information collection module, video processing module, image processing module, analysis and control module and traffic light display module, wherein: The information collection module is provided in plurality, and the plurality of information collection modules are evenly distributed between the two traffic light display modules, and the information collection module is used to obtain video information of vehicles on the road; The video processing module is used to receive the video information and convert the video information into picture information through a frame extraction function; The image processing module is used to extract vehicle feature information from the image information, wherein the vehicle feature information includes the number of vehicles, the location of vehicles and the lighting conditions of vehicles; The traffic light display module includes a straight arrow, a left turn arrow and a right turn arrow, and the colors of the arrows include red, green and yellow, and one arrow corresponds to one lane; The analysis and control module is used to analyze vehicle characteristic information. When it is determined based on the vehicle characteristic information that there is a traffic jam and a traffic accident occurs, the analysis and control module receives the vehicle characteristic information of the left road and the right road of the previous intersection of the current road. When it is determined based on the vehicle characteristic information that there is no traffic jam, the analysis and control module controls the straight arrow of the previous intersection of the current road to execute a first adjustment scheme. The first adjustment scheme includes adjusting the straight arrow originally green at the previous intersection to a gradient green arrow. The gradient green arrow indicates that there is a traffic jam ahead after going straight, and the driver determines whether to go straight according to the needs. When it is determined based on the vehicle characteristic information that there are fewer vehicles on the left road than on the right road, when the left turn arrow of the current road is green, the straight arrow is adjusted to a left turn arrow and displayed green, indicating that the driver determines whether to turn left according to the needs. When it is determined based on the vehicle characteristic information that there are more vehicles on the left road than on the right road, when the right turn arrow of the current road is green, the straight arrow is adjusted to a right turn arrow and displayed green, indicating that the driver determines whether to turn right according to the needs. When the analysis and control module determines that the road is clear based on the real-time vehicle characteristic information, the control state of the traffic light display module is restored to the initial state.

2. According to claim 1, a traffic light intelligent control system based on traffic big data is characterized in that: The analysis control module determines that the left road is congested based on the vehicle feature information of the left road and the right road, and when the right road is not congested, the analysis control module controls the straight arrow of the previous intersection of the current road to execute the second adjustment scheme, the second adjustment scheme includes adjusting the straight arrow of the previous intersection to a gradient green arrow when it is originally green, the gradient green arrow indicates that there is a traffic jam ahead, and the driver determines whether to go straight according to the needs, and when the right turn arrow is green, the straight arrow is adjusted to the right turn arrow to be green, indicating that the driver determines whether to turn right according to the needs; The analysis and control module determines that there is no traffic jam on the left road based on the vehicle characteristic information of the left road and the right road. When there is traffic jam on the right road, the analysis and control module controls the straight arrow of the previous intersection of this road to execute the third adjustment plan. The third adjustment plan includes adjusting the original straight arrow of the previous intersection to a gradient green arrow when it is green. The gradient green arrow indicates a traffic jam ahead, and the driver determines whether to go straight according to needs. When the left turn arrow is green, the straight arrow is adjusted to a left turn arrow showing green, indicating that the driver determines whether to turn left according to needs.

3. The intelligent traffic light control system based on traffic big data according to claim 1 is characterized in that: The analysis control module determines based on the vehicle characteristic information of the left road and the right road that the left road and the right road are not congested, and the number of through lanes is greater than or equal to 2; When the number of through lanes is an even number, the analysis and control module controls the through arrow of the previous intersection of the road to execute the fourth adjustment scheme instead of the first adjustment scheme, the fourth adjustment scheme includes adjusting the straight arrow originally in the previous intersection to a gradient green arrow when it is green, the gradient green arrow indicates a traffic jam ahead, and the driver determines whether to go straight according to the needs, when the left turn arrow is green, half of the straight arrows near the left turn side are adjusted to the left turn arrows showing green, and the driver determines whether to turn left according to the needs, when the right turn arrow is green, half of the straight arrows near the right turn side are adjusted to the right turn arrows showing green, and the driver determines whether to turn right according to the needs, and when it is determined that the road is clear, it returns to the initial control state; When the number of straight lanes is an odd number, the analysis and control module controls the straight arrow of the previous intersection of the road to execute the fifth adjustment scheme instead of the first adjustment scheme. The fifth adjustment scheme includes adjusting the straight arrow of the previous intersection from green to a gradient green arrow. The gradient green arrow indicates a traffic jam ahead. The driver determines whether to go straight according to the needs. When it is determined that there are fewer vehicles on the left road than on the right road, when the left turn arrow is green, the left turn arrow is close to the left turn side. The number of straight arrows is adjusted to a left turn arrow and displayed in green. n Indicates the number of straight lanes, indicating that the driver needs to determine whether to turn left. When the right turn arrow is green, close to the right turn side The straight arrow is adjusted to the right turn arrow in green, indicating that the driver can decide whether to turn right according to the needs. When it is judged that there are more vehicles on the left road than on the right road, when the left turn arrow is green, the driver should turn left. The number of straight arrows is adjusted to the left turn arrow showing green, indicating that the driver can decide whether to turn left according to the need. When the right turn arrow shows green, the right turn side is close to The straight arrow is adjusted to a right-turn arrow in green, indicating that the driver can decide whether to turn right as needed.

4. The intelligent traffic light control system based on traffic big data according to claim 1 is characterized in that: When a traffic jam and a traffic accident are determined based on the vehicle characteristic information, the left-turn arrow on the left road of the previous intersection heading towards the traffic accident is adjusted from green to a gradient green arrow. The gradient green arrow indicates a traffic jam ahead after turning left, and the driver determines whether to turn left as needed. When the straight arrow on the left lane is green, the left-turn arrow corresponding to the left lane is adjusted to a straight arrow showing green, indicating that the driver determines whether to go straight as needed.

5. The intelligent traffic light control system based on traffic big data according to claim 1 is characterized in that: When a traffic jam and a traffic accident are determined based on the vehicle characteristic information, the right-turn arrow on the right road of the previous intersection heading towards the traffic accident is adjusted from green to a gradient green arrow. The gradient green arrow indicates a traffic jam ahead after turning right, and the driver determines whether to turn right as needed. When the straight arrow on the right lane is green, the right-turn arrow corresponding to the right lane is adjusted to a straight arrow showing green, indicating that the driver determines whether to go straight as needed.

6. The intelligent traffic light control system based on traffic big data according to claim 1 is characterized in that: The method of judging traffic jam and traffic accident based on vehicle characteristic information includes, after judging that the number of vehicles exceeds a predetermined value, judging whether there are vehicles in a tilted, horizontal or reverse state, and judging whether the hazard lights of vehicles in a tilted, horizontal or reverse state are turned on; if the hazard lights are turned on, it is judged that a traffic accident has occurred.

7. A control method for a traffic light intelligent control system based on traffic big data according to claim 1, characterized in that: include: Obtain video information of vehicles on the road, and then transmit the video information to the video processing module, which converts the video information into image information through the frame extraction function; Extract vehicle feature information from the image information to obtain the number of vehicles on the road, the position of the vehicle relative to the traffic markings, and the status of vehicle lights; After judging that a traffic jam and a traffic accident have occurred based on the number of vehicles on the road, the position of the vehicles relative to the traffic markings, and the lighting of the vehicles, the vehicle characteristic information of the left and right roads of the previous intersection of the road is received; When it is determined based on the vehicle characteristic information of the left road and the right road that there is no traffic jam, the analysis and control module controls the straight arrow of the previous intersection of the current road to execute a first adjustment scheme, wherein the first adjustment scheme includes adjusting the straight arrow originally green at the previous intersection to a gradient green arrow, when it is determined based on the vehicle characteristic information that there are fewer vehicles on the left road than on the right road, when the left turn arrow of the current road is displayed green, the straight arrow is adjusted to a left turn arrow and displayed green, and when it is determined based on the vehicle characteristic information that there are more vehicles on the left road than on the right road, when the right turn arrow of the current road is displayed green, the straight arrow is adjusted to a right turn arrow and displayed green; After judging whether the road is clear based on real-time vehicle characteristic information, the control state of the traffic light display module is restored to the initial state.

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