阅读说明：本技术 一种基于车载智能摄像头和大数据平台的红绿灯预判方法和存储设备 (Traffic light pre-judging method based on vehicle-mounted intelligent camera and big data platform and storage device ) 是由 薛斯岐 傅振兴 凌政锋 余淑豪 周剑花 戴富庶 于 2021-05-20 设计创作，主要内容包括：本发明涉及汽车技术领域,特别涉及一种基于车载智能摄像头和大数据平台的红绿灯预判方法和存储设备。所述一种基于车载智能摄像头和大数据平台的红绿灯预判方法,包括步骤：判断是否符合预设条件,若符合预设条件,则通过摄像头获取交通灯状况相关数据,所述摄像头设置于车顶；根据所述交通灯状况相关数据对驾驶人员发出指示。因摄像头设置于车顶,具有较高的视野,可以实现交通灯遮挡或者驾驶员视野受限的情况下,通过摄像头获取交通灯状况相关数据,对所述交通灯状况相关数据进行分析即可得知前方交通情况,并对驾驶人员发出相关指示,帮助驾驶人员安全驾驶。(The invention relates to the technical field of automobiles, in particular to a traffic light prejudging method and storage equipment based on a vehicle-mounted intelligent camera and a big data platform. The traffic light prejudging method based on the vehicle-mounted intelligent camera and the big data platform comprises the following steps: judging whether a preset condition is met, if so, acquiring relevant data of the traffic light condition through a camera, wherein the camera is arranged on the roof of the vehicle; and sending an instruction to a driver according to the traffic light condition related data. Because the camera is arranged on the roof, the camera has a higher visual field, and can acquire traffic light condition related data through the camera under the condition that the traffic light is shielded or the visual field of a driver is limited, analyze the traffic light condition related data to know the front traffic condition and send related instructions to the driver to help the driver to drive safely.)

1. A traffic light prejudging method based on a vehicle-mounted intelligent camera and a big data platform is characterized by comprising the following steps:

judging whether a preset condition is met, if so, acquiring relevant data of the traffic light condition through a camera, wherein the camera is arranged on the roof of the vehicle;

and sending an instruction to a driver according to the traffic light condition related data.

2. The traffic light prejudging method based on the vehicle-mounted intelligent camera and the big data platform as claimed in claim 1, wherein the step of acquiring the traffic light condition related data through the camera includes the following steps:

requesting traffic light condition related data according to the vehicle-mounted navigation positioning information through a network;

or

And requesting the traffic light condition related data according to the vehicle-mounted navigation positioning information through the cloud platform.

3. The traffic light prejudging method based on the vehicle-mounted intelligent camera and the big data platform as claimed in claim 2, wherein the step of requesting the traffic light condition related data according to the vehicle-mounted navigation positioning information through the cloud platform specifically comprises the steps of:

judging whether corresponding traffic light condition related data is requested or not, if the corresponding traffic light condition related data is not returned, acquiring current traffic light related information through a camera, and uploading the traffic light related information to a cloud platform;

if the data related to the condition of the corresponding traffic light is not complete, the change or the reading of the traffic light is identified through the camera, if the change or the reading of the traffic light is failed, the line passing time of the vehicle before the stop line is captured to be used as the green light starting time for calibration, and then the timing time is estimated.

4. The traffic light prejudging method based on the vehicle-mounted intelligent camera and the big data platform according to any one of claims 1 to 3, wherein the step of sending an indication to a driver according to the traffic light condition related data specifically comprises the following steps:

and if the data related to the traffic light condition is complete, displaying the traffic light state and the countdown on a vehicle display.

5. The traffic light prejudging method based on the vehicle-mounted intelligent camera and the big data platform according to any one of claims 1 to 4,

the traffic light condition related data includes, but is not limited to: the time counting method comprises the following steps of (1) carrying out an array of traffic states, timing time, state change sequences of traffic lights and corresponding time corresponding to lanes at the current time;

the preset conditions include, but are not limited to: the camera recognizes that the distance between the traffic signal lamp and the vehicle-mounted navigation position information and the intersection with the traffic lamp meets a certain threshold value.

6. A storage device having a set of instructions stored therein, the set of instructions being operable to perform: judging whether a preset condition is met, if so, acquiring data related to the traffic light condition, wherein the storage device is arranged on the roof of the vehicle;

and sending an instruction to a driver according to the traffic light condition related data.

7. The storage device of claim 6, wherein the set of instructions is further configured to perform: the step of acquiring the relevant data of the traffic light condition through the camera specifically comprises the following steps:

requesting traffic light condition related data according to the vehicle-mounted navigation positioning information through a network;

or

And requesting the traffic light condition related data according to the vehicle-mounted navigation positioning information through the cloud platform.

8. The storage device of claim 7, wherein the set of instructions is further configured to perform:

the method for requesting the traffic light condition related data through the cloud platform according to the vehicle navigation positioning information specifically comprises the following steps:

judging whether corresponding traffic light condition related data is requested or not, if the corresponding traffic light condition related data is not returned, acquiring current traffic light related information through a camera, and uploading the traffic light related information to a cloud platform;

if the data related to the condition of the corresponding traffic light is not complete, the change or the reading of the traffic light is identified through the camera, if the change or the reading of the traffic light is failed, the line passing time of the vehicle before the stop line is captured to be used as the green light starting time for calibration, and then the timing time is estimated.

9. A storage device according to any of claims 6 to 8, wherein said set of instructions is further adapted to perform:

the step of sending an instruction to a driver according to the traffic light condition related data specifically comprises the following steps:

and if the data related to the traffic light condition is complete, displaying the traffic light state and the countdown on a vehicle display.

10. A storage device according to claims 6 to 9, wherein said traffic light condition related data includes, but is not limited to: the time counting method comprises the following steps of (1) carrying out an array of traffic states, timing time, state change sequences of traffic lights and corresponding time corresponding to lanes at the current time;

the preset conditions include, but are not limited to: the camera recognizes that the distance between the traffic signal lamp and the vehicle-mounted navigation position information and the intersection with the traffic lamp meets a certain threshold value.

Technical Field

The invention relates to the technical field of automobiles, in particular to a traffic light prejudging method and storage equipment based on a vehicle-mounted intelligent camera and a big data platform.

Background

The traffic light recognition of the current automobile intelligent driving system mainly realizes the traffic light recognition of a crossroad through a front camera and reminds drivers.

The partial functions can remind a driver of the current traffic condition in a certain scene, but sometimes the current traffic light state cannot be known due to traffic congestion, the shielding of vehicles in front, such as large trucks, buses and the like, or other special conditions, and the red light running is mistaken.

Disclosure of Invention

Therefore, a traffic light prejudging method based on a vehicle-mounted intelligent camera and a big data platform is needed to be provided, so that the technical problems that the current traffic light state cannot be known and the red light is rushed by mistake due to traffic jam and shielding of vehicles in front are solved. The specific technical scheme is as follows:

a traffic light prejudging method based on a vehicle-mounted intelligent camera and a big data platform comprises the following steps:

judging whether a preset condition is met, if so, acquiring relevant data of the traffic light condition through a camera, wherein the camera is arranged on the roof of the vehicle;

and sending an instruction to a driver according to the traffic light condition related data.

Further, the step of acquiring the data related to the traffic light condition through the camera specifically comprises the following steps:

requesting traffic light condition related data according to the vehicle-mounted navigation positioning information through a network;

or

And requesting the traffic light condition related data according to the vehicle-mounted navigation positioning information through the cloud platform.

Further, the step of requesting the traffic light condition related data according to the vehicle navigation positioning information through the cloud platform specifically comprises the steps of:

judging whether corresponding traffic light condition related data is requested or not, if the corresponding traffic light condition related data is not returned, acquiring current traffic light related information through a camera, and uploading the traffic light related information to a cloud platform;

if the data related to the condition of the corresponding traffic light is not complete, the change or the reading of the traffic light is identified through the camera, if the change or the reading of the traffic light is failed, the line passing time of the vehicle before the stop line is captured to be used as the green light starting time for calibration, and then the timing time is estimated.

Further, the step of sending an instruction to a driver according to the data related to the traffic light condition specifically comprises the following steps:

and if the data related to the traffic light condition is complete, displaying the traffic light state and the countdown on a vehicle display.

Further, the traffic light condition related data includes, but is not limited to: the time counting method comprises the following steps of (1) carrying out an array of traffic states, timing time, state change sequences of traffic lights and corresponding time corresponding to lanes at the current time;

the preset conditions include, but are not limited to: the camera recognizes that the distance between the traffic signal lamp and the vehicle-mounted navigation position information and the intersection with the traffic lamp meets a certain threshold value.

In order to solve the technical problem, the storage device is further provided, and the specific technical scheme is as follows:

a storage device having stored therein a set of instructions for performing: judging whether a preset condition is met, if so, acquiring data related to the traffic light condition, wherein the storage device is arranged on the roof of the vehicle;

and sending an instruction to a driver according to the traffic light condition related data.

Further, the set of instructions is further for performing: the step of acquiring the relevant data of the traffic light condition through the camera specifically comprises the following steps:

requesting traffic light condition related data according to the vehicle-mounted navigation positioning information through a network;

or

And requesting the traffic light condition related data according to the vehicle-mounted navigation positioning information through the cloud platform.

Further, the set of instructions is further for performing:

the method for requesting the traffic light condition related data through the cloud platform according to the vehicle navigation positioning information specifically comprises the following steps:

judging whether corresponding traffic light condition related data is requested or not, if the corresponding traffic light condition related data is not returned, acquiring current traffic light related information through a camera, and uploading the traffic light related information to a cloud platform;

if the data related to the condition of the corresponding traffic light is not complete, the change or the reading of the traffic light is identified through the camera, if the change or the reading of the traffic light is failed, the line passing time of the vehicle before the stop line is captured to be used as the green light starting time for calibration, and then the timing time is estimated.

Further, the set of instructions is further for performing:

the step of sending an instruction to a driver according to the traffic light condition related data specifically comprises the following steps:

and if the data related to the traffic light condition is complete, displaying the traffic light state and the countdown on a vehicle display.

Further, the traffic light condition related data includes, but is not limited to: the time counting method comprises the following steps of (1) carrying out an array of traffic states, timing time, state change sequences of traffic lights and corresponding time corresponding to lanes at the current time;

the preset conditions include, but are not limited to: the camera recognizes that the distance between the traffic signal lamp and the vehicle-mounted navigation position information and the intersection with the traffic lamp meets a certain threshold value.

The invention has the beneficial effects that: judging whether a preset condition is met, if so, acquiring relevant data of the traffic light condition through a camera, wherein the camera is arranged on the roof of the vehicle; and sending an instruction to a driver according to the traffic light condition related data. Because the camera is arranged on the roof, the camera has a higher visual field, and can acquire traffic light condition related data through the camera under the condition that the traffic light is shielded or the visual field of a driver is limited, analyze the traffic light condition related data to know the front traffic condition and send related instructions to the driver to help the driver to drive safely. In addition, according to the technical scheme, only a software algorithm needs to be added on the basis of the original camera, the cost of single-vehicle hardware does not need to be increased, the scene of a visual field blind area of traffic lights on a cross road is effectively covered, the automobile intelligence is improved, and the driving risk under the similar scene is reduced.

Drawings

Fig. 1 is a flowchart of a traffic light pre-judging method based on a vehicle-mounted intelligent camera and a big data platform according to an embodiment;

fig. 2 is a schematic diagram of a traffic light pre-judging method based on a vehicle-mounted intelligent camera and a big data platform according to a specific embodiment;

fig. 3 is a schematic block diagram of a storage device according to an embodiment.

Description of reference numerals:

300. a storage device.

Detailed Description

To explain technical contents, structural features, and objects and effects of the technical solutions in detail, the following detailed description is given with reference to the accompanying drawings in conjunction with the embodiments.

Referring to fig. 1 to 2, in the present embodiment, a traffic light pre-judging method based on a vehicle-mounted intelligent camera and a big data platform may be applied to a storage device, where the storage device includes but is not limited to: personal computers, servers, general purpose computers, special purpose computers, network devices, embedded devices, programmable devices, intelligent mobile terminals, vehicle mounted intelligent devices, etc. In this embodiment, the storage device is exemplified by a smart camera, which is arranged on the roof of the vehicle for the purpose of obtaining a good field of view.

The core technical idea of the application is as follows: the vehicle-mounted intelligent camera on the roof is used for identifying the traffic signal lamps before passing through the intersection, and the data platform is used for acquiring the relevant data of the traffic light conditions and displaying the data on the vehicle.

The method comprises the following specific steps:

step S101: is a preset condition met?

If the preset condition is met, executing step S102: the method comprises the steps of obtaining relevant data of traffic light conditions through a camera, wherein the camera is arranged on the roof of the vehicle.

Step S103: and sending an instruction to a driver according to the traffic light condition related data.

As shown in fig. 2, in step S101, when the intelligent camera recognizes a traffic light and the vehicle-mounted navigation position information satisfies a certain threshold from the intersection with the traffic light. And if the condition is met, triggering the camera to acquire the data related to the traffic light condition.

In the present embodiment, the traffic light condition related data includes, but is not limited to: the traffic state corresponding to each lane at the current time, the timing time, the sequence of the change of each state of the traffic light and the array of the corresponding time. The method specifically comprises the following steps:

and acquiring information (including lane related information (the length of a solid line of a lane in front of a crossroad stop line, lane indication and the like), state, left-right turning, straight running, time counting and other related information, such as the straight running time of the red light state: 60s counted time: 20s remained time: 40s) of the current traffic light, and displaying the state of the traffic light and countdown to remind a driver by the vehicle machine at the moment. Even if the traffic light in the place ahead can't be seen to navigating mate like this, also can know that present traffic light is in which of red, yellow and green, and then avoid violating traffic rules and drive, ensured the security of driving.

The "acquiring the data related to the traffic light condition by the camera" is specifically divided into two cases:

one is that the current traffic light is in an area which realizes the internet of things, and the related data of the traffic light condition is requested directly through the network according to the vehicle navigation positioning information. Namely: and if the current vehicle-mounted navigation information shows that the current area of the vehicle is on the xx road, requesting data related to the traffic light condition on the xx road through the network.

And if the traffic light temporal information (the Internet of things is not realized) cannot be acquired in the region, requesting the traffic light condition related data according to the vehicle-mounted navigation positioning information through the cloud platform. The vehicle-mounted intelligent camera can identify the state and the count of the traffic light, the timing system can be started at the moment, the state and the timing simulation calculation are started according to the data fed back by the platform, and the driver can be reminded on the vehicle machine no matter whether the front is sheltered or not. The system records the switching of the red, green and yellow states of the traffic light each time and the intermediate timing, then uploads the related traffic light information such as the position, the lane correlation, the timing, the state change sequence of the traffic light and the like to the cloud platform through the network, and the cloud platform checks and updates the traffic light data. The condition that the state change of the traffic lights cannot be identified in individual road sections (the traffic lights are low in position and cannot be identified due to strong light) can be calibrated by capturing the passing line of the vehicle in front of the stop line according to the camera as the starting time of the green light, and the timing time can be estimated by continuously capturing and calibrating data in the crowded road sections.

As shown in fig. 2, the following may be specifically mentioned:

and judging whether the corresponding traffic light condition related data is requested or not, if the corresponding traffic light condition related data is not returned, acquiring the current traffic light related information through a camera, and uploading the traffic light related information to the cloud platform. Thus, after a plurality of times of vehicle data addition and updating, a complete traffic light signal data set of the intersection can be formed.

If the data related to the condition of the corresponding traffic light is not complete, the change or the reading of the traffic light is identified through the camera, if the change or the reading of the traffic light is failed, the line passing time of the vehicle before the stop line is captured to be used as the green light starting time for calibration, and then the timing time is estimated.

Wherein if the data related to the corresponding traffic light condition is not complete, a special case is: the returned traffic light condition-related data only contains an array of sequences and corresponding times of changes in the various states of the traffic lights. The traffic light change or reading is identified through the camera, and if the traffic light is shielded or the identification fails, the line passing time of the vehicle before the stop line is captured to be used as the green light starting time for calibration, so that the timing time is estimated. Where a vehicle ahead take off may be considered a lane green light.

The data obtained subsequently can be uploaded to the cloud platform under the condition that the data are not complete or incomplete, so that the data are more and more perfect, and blind areas which are not covered by the Internet of things of traffic lights can be solved by utilizing big data in the long term.

And if the data related to the traffic light condition is complete, displaying the traffic light state and the countdown on the vehicle display.

Judging whether a preset condition is met, if so, acquiring relevant data of the traffic light condition through a camera, wherein the camera is arranged on the roof of the vehicle; and sending an instruction to a driver according to the traffic light condition related data. Because the camera is arranged on the roof, the camera has a higher visual field, and can acquire traffic light condition related data through the camera under the condition that the traffic light is shielded or the visual field of a driver is limited, analyze the traffic light condition related data to know the front traffic condition and send related instructions to the driver to help the driver to drive safely. In addition, according to the technical scheme, only a software algorithm needs to be added on the basis of the original camera, the cost of single-vehicle hardware does not need to be increased, the scene of a visual field blind area of traffic lights on a cross road is effectively covered, the automobile intelligence is improved, and the driving risk under the similar scene is reduced.

The following explanation is further provided for the traffic light principle of traffic flow estimation:

the intelligent camera is installed on the roof, has a higher visual field, and can predict the state of the traffic light according to the detection of different lanes. Firstly, obtaining lane information according to platform data and positioning information, positioning a lane where a vehicle is located and a distance from a stop line. The state of the traffic lights at the intersection changes, and the passing time in each direction has a fixed time difference. And (3) judging: (1) opposite lane: when the vehicle passing the stop line in front of the opposite lane line is captured, the green light starting time of the lane is recorded, and a traffic light timing system is triggered to record data. (2) Lane in the same direction: the camera can scan the vehicles in all lanes in the same direction, marks the vehicles in front of the stop lines of all the lanes (the scanning range is calibrated according to the distance of the stop lines and the width of the lanes) (if the vehicles in a part of the scanned lane area are shielded, the lane statistics is cancelled), records the green light starting time of each lane when the displacement distance of the marked vehicles exceeds a certain threshold value of the stop lines, and simultaneously triggers the traffic light timing system. (3) Traffic light timing system: when the state of the traffic light changes, the traffic flow of the passable lane can enter a flowing state, the camera monitors that the moving distance of the marking vehicle exceeds the stop line and reaches a certain threshold value, the traffic light timing system is triggered, the time of each lane is calculated according to the time of the lane and is compared with the time of each lane recorded by the current system, if the time error is low, the camera stops scanning, the current timing is adopted for calculation, the vehicle displays the result, if the error is large, the lane with the large error is removed, the average value is obtained, the data of each lane is updated, meanwhile, the timing is sent to the vehicle, the camera continues scanning, and the timing is continuously updated to reduce the error. This loop exit condition crosses the traffic light stop line & error is less than the threshold.

Further, at the intersection where the traffic lights are not networked and have no platform data, the vehicles can record the traffic lights and the relevant information data of the lanes, and time is counted, if the records are successfully recorded, the data can be uploaded to the cloud platform for data addition, and a complete traffic light signal data set of the intersection can be formed through multiple times of data updating of multiple vehicles.

Referring to fig. 2 to fig. 3, in the present embodiment, an embodiment of a memory device 300 is as follows:

in the present embodiment, the storage device 300 is exemplified by a smart camera, which is disposed on the roof of the vehicle and aims to obtain a good field of view. The specific implementation is as follows:

a storage device 300 having stored therein a set of instructions for performing: judging whether a preset condition is met, if so, acquiring data related to the traffic light condition, wherein the storage device 300 is arranged on the roof of the vehicle;

and sending an instruction to a driver according to the traffic light condition related data.

Wherein the preset conditions include, but are not limited to: the camera recognizes that the distance between the traffic signal lamp and the vehicle-mounted navigation position information and the intersection with the traffic lamp meets a certain threshold value.

In the present embodiment, the traffic light condition related data includes, but is not limited to: the traffic state corresponding to each lane at the current time, the timing time, the sequence of the change of each state of the traffic light and the array of the corresponding time. The method specifically comprises the following steps:

and acquiring information (including lane related information (the length of a solid line of a lane in front of a crossroad stop line, lane indication and the like), state, left-right turning, straight running, time counting and other related information, such as the straight running time of the red light state: 60s counted time: 20s remained time: 40s) of the current traffic light, and displaying the state of the traffic light and countdown to remind a driver by the vehicle machine at the moment.

Further, the set of instructions is further for performing: the method comprises the following steps of acquiring traffic light condition related data through a camera, and specifically comprises the following two conditions:

one is that the current traffic light is in an area which realizes the internet of things, and the related data of the traffic light condition is requested directly through the network according to the vehicle navigation positioning information. Namely: and if the current vehicle-mounted navigation information shows that the current area of the vehicle is on the xx road, requesting data related to the traffic light condition on the xx road through the network.

And if the traffic light temporal information (the Internet of things is not realized) cannot be acquired in the region, requesting the traffic light condition related data according to the vehicle-mounted navigation positioning information through the cloud platform. The vehicle-mounted intelligent camera can identify the state and the count of the traffic light, the timing system can be started at the moment, the state and the timing simulation calculation are started according to the data fed back by the platform, and the driver can be reminded on the vehicle machine no matter whether the front is sheltered or not. The system records the switching of the red, green and yellow states of the traffic light each time and the intermediate timing, then uploads the related traffic light information such as the position, the lane correlation, the timing, the state change sequence of the traffic light and the like to the cloud platform through the network, and the cloud platform checks and updates the traffic light data. The condition that the state change of the traffic lights cannot be identified in individual road sections (the traffic lights are low in position and cannot be identified due to strong light) can be calibrated by capturing the passing line of the vehicle in front of the stop line according to the camera as the starting time of the green light, and the timing time can be estimated by continuously capturing and calibrating data in the crowded road sections.

As shown in fig. 2, the following may be specifically mentioned:

and judging whether the corresponding traffic light condition related data is requested or not, if the corresponding traffic light condition related data is not returned, acquiring the current traffic light related information through a camera, and uploading the traffic light related information to the cloud platform. Thus, after a plurality of times of vehicle data addition and updating, a complete traffic light signal data set of the intersection can be formed.

If the data related to the condition of the corresponding traffic light is not complete, the change or the reading of the traffic light is identified through the camera, if the change or the reading of the traffic light is failed, the line passing time of the vehicle before the stop line is captured to be used as the green light starting time for calibration, and then the timing time is estimated.

Wherein if the data related to the corresponding traffic light condition is not complete, a special case is: the returned traffic light condition-related data only contains an array of sequences and corresponding times of changes in the various states of the traffic lights. The traffic light change or reading is identified through the camera, and if the traffic light is shielded or the identification fails, the line passing time of the vehicle before the stop line is captured to be used as the green light starting time for calibration, so that the timing time is estimated. Where a vehicle ahead take off may be considered a lane green light.

And if the data related to the traffic light condition is complete, displaying the traffic light state and the countdown on the vehicle display.

Judging whether a preset condition is met, if so, acquiring relevant data of the traffic light condition through a camera, wherein the camera is arranged on the roof of the vehicle; and sending an instruction to a driver according to the traffic light condition related data. Because the camera is arranged on the roof, the camera has a higher visual field, and can acquire traffic light condition related data through the camera under the condition that the traffic light is shielded or the visual field of a driver is limited, analyze the traffic light condition related data to know the front traffic condition and send related instructions to the driver to help the driver to drive safely. In addition, according to the technical scheme, only a software algorithm needs to be added on the basis of the original camera, the cost of single-vehicle hardware does not need to be increased, the scene of a visual field blind area of traffic lights on a cross road is effectively covered, the automobile intelligence is improved, and the driving risk under the similar scene is reduced.

The following explanation is further provided for the traffic light principle of traffic flow estimation:

the intelligent camera is installed on the roof, has a higher visual field, and can predict the state of the traffic light according to the detection of different lanes. Firstly, obtaining lane information according to platform data and positioning information, positioning a lane where a vehicle is located and a distance from a stop line. The state of the traffic lights at the intersection changes, and the passing time in each direction has a fixed time difference. And (3) judging: (1) opposite lane: when the vehicle passing the stop line in front of the opposite lane line is captured, the green light starting time of the lane is recorded, and a traffic light timing system is triggered to record data. (2) Lane in the same direction: the camera can scan the vehicles in all lanes in the same direction, marks the vehicles in front of the stop lines of all the lanes (the scanning range is calibrated according to the distance of the stop lines and the width of the lanes) (if the vehicles in a part of the scanned lane area are shielded, the lane statistics is cancelled), records the green light starting time of each lane when the displacement distance of the marked vehicles exceeds a certain threshold value of the stop lines, and simultaneously triggers the traffic light timing system. (3) Traffic light timing system: when the state of the traffic light changes, the traffic flow of the passable lane can enter a flowing state, the camera monitors that the moving distance of the marking vehicle exceeds the stop line and reaches a certain threshold value, the traffic light timing system is triggered, the time of each lane is calculated according to the time of the lane and is compared with the time of each lane recorded by the current system, if the time error is low, the camera stops scanning, the current timing is adopted for calculation, the vehicle displays the result, if the error is large, the lane with the large error is removed, the average value is obtained, the data of each lane is updated, meanwhile, the timing is sent to the vehicle, the camera continues scanning, and the timing is continuously updated to reduce the error. This loop exit condition crosses the traffic light stop line & error is less than the threshold.

Further, the set of instructions is further for performing: at the intersection without the networking of the traffic lights and the platform data, the vehicles can record the traffic lights and the relevant information data of the lanes, the time is counted, if the records are successfully recorded, the data can be uploaded to the cloud platform for data addition, and a complete traffic light signal data set of the intersection can be formed through multiple times of data updating of multiple vehicles.

It should be noted that, although the above embodiments have been described herein, the invention is not limited thereto. Therefore, based on the innovative concepts of the present invention, the technical solutions of the present invention can be directly or indirectly applied to other related technical fields by making changes and modifications to the embodiments described herein, or by using equivalent structures or equivalent processes performed in the content of the present specification and the attached drawings, which are included in the scope of the present invention.