CN117690300B - Method for optimizing vehicle to acquire traffic light color and countdown information - Google Patents
Method for optimizing vehicle to acquire traffic light color and countdown information Download PDFInfo
- Publication number
- CN117690300B CN117690300B CN202410156687.1A CN202410156687A CN117690300B CN 117690300 B CN117690300 B CN 117690300B CN 202410156687 A CN202410156687 A CN 202410156687A CN 117690300 B CN117690300 B CN 117690300B
- Authority
- CN
- China
- Prior art keywords
- vehicle
- traffic light
- timing
- red light
- time
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 25
- 238000004364 calculation method Methods 0.000 claims abstract description 27
- 206010021033 Hypomenorrhoea Diseases 0.000 claims abstract description 19
- 238000005259 measurement Methods 0.000 claims description 7
- 238000009960 carding Methods 0.000 claims description 4
- 238000004891 communication Methods 0.000 abstract description 4
- 230000008901 benefit Effects 0.000 description 3
- 238000010586 diagram Methods 0.000 description 3
- 238000004519 manufacturing process Methods 0.000 description 3
- 238000013461 design Methods 0.000 description 2
- 238000011161 development Methods 0.000 description 2
- 206010039203 Road traffic accident Diseases 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 239000003086 colorant Substances 0.000 description 1
- 238000007405 data analysis Methods 0.000 description 1
- 230000008451 emotion Effects 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0125—Traffic data processing
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0108—Measuring and analyzing of parameters relative to traffic conditions based on the source of data
- G08G1/0112—Measuring and analyzing of parameters relative to traffic conditions based on the source of data from the vehicle, e.g. floating car data [FCD]
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0137—Measuring and analyzing of parameters relative to traffic conditions for specific applications
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/09—Arrangements for giving variable traffic instructions
- G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Chemical & Material Sciences (AREA)
- Analytical Chemistry (AREA)
- Traffic Control Systems (AREA)
Abstract
The invention relates to a method for optimizing a vehicle to acquire traffic light color and countdown information, and acquiring vehicle self data; triggering a timing state according to the vehicle speed; triggering red light time calculation according to the position relation between the vehicle position and the intersection stop line when the vehicle stops; calculating a traffic light period according to the red light time; aiming at a common non-networked vehicle, the invention can acquire the traffic light color and countdown information of the road junction without establishing communication connection with a cloud big data platform; traffic light data estimation is carried out aiming at the cloud big data platform, a large amount of traffic data of different vehicles is not needed to be used as a calculation basis, and traffic light color and countdown information can be calculated based on one vehicle driving data; the traffic light color and countdown information of the lane level can be displayed.
Description
Technical Field
The invention belongs to the technical field of traffic light countdown, and particularly relates to a method for optimizing a vehicle to acquire traffic light color and countdown information.
Background
At present, when a vehicle runs to a traffic light intersection on a road, most of traffic lights at the intersection only display traffic light red, green and yellow light color information, and no countdown color step information of the traffic lights are displayed, so that the vehicle cannot control the speed of the vehicle to reasonably pass through the intersection, the tension emotion of the driver is increased, and the probability of running the red light and traffic accidents of the vehicle is increased. Meanwhile, for a common traditional vehicle, when the vehicle cannot realize the function of internet of vehicles and cannot acquire traffic light color and countdown information through advanced vehicle-mounted equipment such as a camera and a radar or a big data cloud platform, how to identify the current traffic light color and countdown information, and the improvement of the traffic efficiency and the safety of the vehicle at an intersection are a problem which needs to be solved at present.
At present, aiming at the series of problems, the prior art scheme mainly depends on two schemes, the first is based on a high-precision sensor such as a vehicle camera radar and the like, and the traffic light color of a traffic light intersection where a vehicle is positioned is identified, so that the change of the light color is identified. And secondly, counting all vehicles passing through the traffic light intersection based on the cloud big data platform, and estimating traffic light color and color step countdown information of the intersection according to the statistical information of all the vehicles.
The prior art scheme has the following disadvantages:
aiming at the fact that a common non-networked vehicle cannot acquire traffic light color and countdown information of a road junction through establishing communication connection with a cloud big data platform;
aiming at vehicles without sensing capability such as cameras, radars and the like, traffic light color and countdown information of a road junction cannot be obtained through a sensor of the vehicle;
traffic light data estimation is carried out on a cloud big data platform, a large amount of traffic data of different vehicles is needed to be used as a calculation basis, and traffic light color and countdown information cannot be calculated based on single vehicle driving data.
The existing scheme can not display traffic light color and countdown information of a lane level, and can not display traffic light color and countdown information corresponding to a lane where a vehicle is located aiming at an intersection with straight, left-turn and right-turn.
Disclosure of Invention
This section is intended to outline some aspects of embodiments of the invention and to briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section as well as in the description summary and in the title of the application, to avoid obscuring the purpose of this section, the description summary and the title of the invention, which should not be used to limit the scope of the invention.
In view of the following technical problems in the prior art: the problem that the existing common traditional vehicle cannot acquire traffic light color and countdown information when the vehicle cannot realize the function of the internet of vehicles.
In order to solve the technical problems, the invention provides the following technical scheme: a method for optimizing a vehicle to acquire traffic light color and countdown information,
acquiring vehicle self data;
triggering a timing state according to the vehicle speed;
triggering red light time calculation according to the position relation between the vehicle position and the intersection stop line when the vehicle stops;
and calculating the traffic light period according to the red light time.
As a preferable technical scheme of the method for optimizing the vehicle to acquire traffic light color and countdown information, the vehicle self data comprises vehicle position, vehicle speed and vehicle running course angle.
As a preferred technical scheme of a method for optimizing a vehicle to acquire traffic light color and countdown information, the triggering timing state according to the vehicle speed includes:
and comparing and judging whether the vehicle is at a traffic light intersection or not based on the vehicle data and the map data, and determining the lane to which the vehicle belongs.
As a preferred technical scheme of the method for optimizing the vehicle to obtain the traffic light color and the countdown information, the triggering the timing state according to the vehicle speed further comprises:
setting a first speed threshold;
if the vehicle speed is smaller than the first speed threshold and is reduced to zero, starting timing from when the vehicle speed is zero to when the vehicle speed is not zero, and counting timing information;
the timing information includes a timing start time point and a timing period.
As a preferable technical scheme of a method for optimizing a vehicle to acquire traffic light color and countdown information, the calculating of the red light time comprises;
comparing the stopping position of the vehicle with the map data to judge whether the vehicle is positioned at the stopping line;
if the vehicle is not at the stop line, storing the current position information, timing information and the distance from the stop line;
if the vehicle is at the stop line, storing the current position information and timing information of the vehicle, and calculating the red light duration of the corresponding lane of the road opening according to the stored time information.
As a preferred technical scheme for optimizing a method for acquiring traffic light color and countdown information of a vehicle, calculating the red light duration of a lane corresponding to a road opening according to stored time information comprises the following steps:
carding the timing period, and counting the occurrence times of the timing period in the data counting of multiple times;
setting a first time number threshold, namely firstly, enabling a timing period with the longest duration to be the duration of the red light, and marking the timing period as a first result red light duration X if the occurrence number of the timing period meets the first time number threshold;
if the number of times of the timing period does not meet the first time threshold, judging whether the timing period with shorter duration meets the first time threshold or not until a first result red light duration X is obtained.
As a preferred technical scheme for optimizing a method for acquiring traffic light color and countdown information of a vehicle, comparing a vehicle stop position with map data to determine whether the vehicle is located at a stop line comprises:
comparing whether the distance between the stopping position of the vehicle and the stopping line in the map data is smaller than a first distance threshold value;
if the distance is smaller than the first distance threshold value, judging that the distance is at the stop line;
if the distance is greater than the first distance threshold, the stop line is judged not to be located.
As a preferred technical scheme for optimizing a method for obtaining traffic light color and countdown information of a vehicle, calculating a traffic light period according to red light time comprises the following steps:
the total duration of the green light yellow light is preset to be Y, and the traffic light period is X+Y;
determining two red light starting time points according to a judging mode of the first result red light duration X to obtain a measurement duration M containing Z traffic light periods, wherein the measurement duration M comprises the following steps:
from the measured sets of M-column equations:
；
wherein the method comprises the steps of~/>And->As is known, find a common solution for (X, Z) in the system of equations and output as a result.
As a preferred technical scheme for optimizing a method for acquiring traffic light color and countdown information of a vehicle, if no common solution or multiple common solutions exist in an equation set, the calculation is participated in the calculation in the next timing period, and a first time threshold is adjusted, and the red light duration X of a second result is selected to participate in the calculation until the common solution is obtained;
the method comprises the following steps that as a preferable technical scheme of a method for optimizing a vehicle to acquire traffic light color and countdown information, a first speed threshold value is preset to be 5km/h, and a traffic light period phase is calculated according to red light time to calculate feedback adjustment;
the first distance threshold is preset to be 1m, and feedback adjustment is calculated according to red light time calculation traffic light period phase.
The invention has the beneficial effects that: aiming at a common non-networked vehicle, the traffic light color and countdown information of the road junction can be obtained without establishing communication connection with a cloud big data platform, and aiming at a vehicle without sensing capability such as a camera, a radar and the like, the traffic light color and countdown information of the road junction can be obtained without passing through a sensor of the vehicle; traffic light data estimation is carried out aiming at the cloud big data platform, a large amount of traffic data of different vehicles is not needed to be used as a calculation basis, and traffic light color and countdown information can be calculated based on one vehicle driving data; the traffic light color and the countdown information of the lane level can be displayed, and the traffic light color and the countdown information corresponding to the lane where the vehicle is located are respectively displayed aiming at the intersections with the straight line, the left turn and the right turn.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the description of the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art. Wherein:
FIG. 1 is a schematic diagram of an overall flow framework of the present invention;
FIG. 2 is a diagram of a time counting and frequency of occurrence corresponding to a line graph in an embodiment of the present invention;
fig. 3 is a schematic diagram of calculation of a measurement duration period in an embodiment of the present invention.
Detailed Description
In order that the above-recited objects, features and advantages of the present invention will become more readily apparent, a more particular description of the invention will be rendered by reference to specific embodiments thereof which are illustrated in the appended drawings.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, but the present invention may be practiced in other ways other than those described herein, and persons skilled in the art will readily appreciate that the present invention is not limited to the specific embodiments disclosed below.
Further, reference herein to "one embodiment" or "an embodiment" means that a particular feature, structure, or characteristic can be included in at least one implementation of the invention. The appearances of the phrase "in one embodiment" in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments.
Further, in describing the embodiments of the present invention in detail, the cross-sectional view of the device structure is not partially enlarged to a general scale for convenience of description, and the schematic is only an example, which should not limit the scope of protection of the present invention. In addition, the three-dimensional dimensions of length, width and depth should be included in actual fabrication.
Referring to fig. 1-3, the present embodiment provides a method for optimizing a vehicle to obtain traffic light color and countdown information, including,
acquiring vehicle self data;
triggering a timing state according to the vehicle speed;
triggering red light time calculation according to the position relation between the vehicle position and the intersection stop line when the vehicle stops;
and calculating the traffic light period according to the red light time.
For a vehicle normally running on a road, vehicle position information, vehicle speed information and vehicle running course angle information are acquired through a vehicle GPS, vehicle bus information and other vehicle-mounted terminals, meanwhile, the vehicle combines the vehicle position information, the vehicle speed information and the vehicle running course angle information with the vehicle end map data based on vehicle end map data stored by the vehicle, and whether the running direction in front of the vehicle is a traffic light intersection can be judged according to the vehicle navigation information.
It should be noted that, the offline map is pure map information that knows route information but cannot learn road conditions and whether traffic lights, light colors and time exist at intersections because the offline map is not networked.
Triggering the timing state based on the vehicle speed includes:
and comparing and judging whether the vehicle is at a traffic light intersection or not based on the vehicle data and the map data, and determining the lane to which the vehicle belongs.
Triggering the timing state based on the vehicle speed further includes:
setting a first speed threshold;
if the vehicle speed is smaller than the first speed threshold and is reduced to zero, starting timing from when the vehicle speed is zero to when the vehicle speed is not zero, and counting timing information;
the timing information includes a timing start time point and a timing period.
When the vehicle judges that the traffic light intersection is in front of the vehicle based on the self data and the map data, the vehicle judges whether the speed information of the vehicle meets a preset first speed threshold value, the first speed threshold value can be that the vehicle speed is not more than 5km/h, the vehicle speed is reduced to 0km/h, and when the vehicle does not meet the first speed threshold value, the timing operation is not performed; when the vehicle meets the vehicle speed judging threshold value, starting timing, ending timing until the vehicle speed is not 0, and counting timing information.
Calculating the red light time comprises the following steps of;
comparing the stopping position of the vehicle with the map data to judge whether the vehicle is positioned at the stopping line;
if the vehicle is not at the stop line, storing the current position information, timing information and the distance from the stop line;
if the vehicle is at the stop line, storing the current position information and timing information of the vehicle, and calculating the red light duration of the corresponding lane of the road opening according to the stored time information.
When the vehicle starts timing, according to the vehicle position when the vehicle speed is reduced to 0, the vehicle position is matched with the vehicle end storage map data, the road junction lane where the vehicle is located is matched, the distance from the vehicle to the current lane stop line is judged when the vehicle stops, if the vehicle is not located at the stop line, the stored vehicle timing information is used for calculating the lamp color for auxiliary use, and when the vehicle is located at the stop line (such as a set threshold value of 1 meter), the vehicle position information and the countdown information are stored, and calculation is carried out according to the stored time information.
The calculating of the red light duration of the lane corresponding to the road opening according to the stored time information comprises the following steps:
carding the timing period, and counting the occurrence times of the timing period in the data counting of multiple times;
setting a first time number threshold, namely firstly, enabling a timing period with the longest duration to be the duration of the red light, and marking the timing period as a first result red light duration X if the occurrence number of the timing period meets the first time number threshold;
if the number of times of the timing period does not meet the first time threshold, judging whether the timing period with shorter duration meets the first time threshold or not until a first result red light duration X is obtained.
According to the data of the current intersection, the current lane and the stop line stored in the vehicle, the intersection and the lane are numbered, for example, the number is A-EW-Right1 (the east-west of the A road turns to the Right for 1 lane), calculation is carried out according to the timing information stored in the vehicle, firstly, carding statistics is carried out on the stored timing information, as shown in a table 1, the timing duration of each time is carded, statistics is carried out on the time duration of each time, for example, 4 times appear in 70 seconds, 2 times appear in 69 seconds, and so on, firstly, the time with the longest time duration of the time is taken as the countdown time of the A-EW-Right1 corresponding to the red light, for example, 70s is taken as the time of the countdown corresponding to the 70s, when the time of the time is met for the first time threshold, the first time threshold can be the time of the countdown of the red light, the time of the green light is greater than 1 time, and then the green light time of the step is corrected according to the calculation of the time duration of the yellow light, in particular, the first time threshold and the first time threshold are changed and recalculated.
Table 1 timing duration and appearance number correspondence table
| Time duration | 49s | 55s | 57s | 58s | 62s | 65s | 67s | 68s | 69s | 70s |
| Number of occurrences | 1 | 1 | 1 | 1 | 1 | 1 | 3 | 1 | 2 | 4 |
Comparing the vehicle stop position with the map data to determine whether the vehicle is located at the stop line includes:
comparing whether the distance between the stopping position of the vehicle and the stopping line in the map data is smaller than a first distance threshold value;
if the distance is smaller than the first distance threshold value, judging that the distance is at the stop line;
if the distance is greater than the first distance threshold, the stop line is judged not to be located.
Calculating the traffic light period according to the red light time comprises the following steps:
the total duration of the green light yellow light is preset to be Y, and the traffic light period is X+Y;
determining two red light starting time points according to a judging mode of the first result red light duration X to obtain a measurement duration M containing Z traffic light periods, wherein the measurement duration M comprises the following steps:
from the measured sets of M-column equations:
；
wherein the method comprises the steps of~/>And->As is known, find a common solution for (X, Z) in the system of equations and output as a result.
Further, after the red light data (the first result red light duration X) of the current intersection, the current lane and the stop line are obtained, the green light and yellow light countdown information of the current intersection, the current lane and the stop line is calculated, and the calculation method is as follows:
firstly, based on the obtained red light data, finding out the time data corresponding to the countdown of the complete red light of the red light, if the first result red light duration X preliminarily obtained in the previous step is 70s, for example, obtaining the starting time of the vehicle corresponding to the 70s timing duration, for example, 10:00 seconds, obtaining the ending time of the vehicle corresponding to the 70s timing duration, for example, 10:01 minutes 10 seconds, simultaneously starting from 10:01 minutes 10 seconds, obtaining the starting time of the next 70s complete red light timing period, for example, 10:06 minutes 10 seconds, as a first group of calculation data, and likewise selecting a second group of data and a third group of data …
Assuming that the green light and yellow light time is y and the total duration is 300 seconds, the total time is subjected to x traffic light cycles, so that an equation of a first group of data is obtained, and similarly, for the data of a second group of total duration is 450 seconds, an equation of the second group of data is obtained, and the third group of data is analogized to obtain a common solution of a plurality of groups of data equations, and as an example in table 2, the common solution is y=80 seconds, and the green light and yellow light time is considered to be 80 seconds.
TABLE 2 multiunit data statistics and solution schematic form
If the equation set has no common solution or a plurality of common solutions, the next timing period participates in calculation and adjusts the first time threshold value, and the second result red light duration X is selected to participate in calculation until the common solution is obtained.
If the multiple groups of data are the common solution, the estimated traffic light duration in the second step is considered to have errors, the second duration in the traffic light duration in the second step is selected to be the duration of the red light, if 69s, calculation is carried out again to judge whether the common solution is obtained; and if only two groups of data have common solutions, the common solutions are considered to be green light and yellow light duration.
The first speed threshold value is preset to be 5km/h, and feedback adjustment is calculated according to the red light time calculation traffic light period phase;
the first distance threshold is preset to be 1m, and feedback adjustment is calculated according to the red light time calculation traffic light period stage.
The invention provides a method for optimizing traffic light color and countdown information acquired by a vehicle, which is characterized in that under the condition that a common vehicle is not based on sensing equipment such as a vehicle-mounted camera radar, road side sensing equipment and cloud control platform big data analysis, the vehicle calculates traffic light color and countdown information of an intersection based on the position, speed and vehicle-mounted map information of the vehicle, and calculates the green light color and the yellow light color and the countdown information of the intersection by giving the red light countdown information, and finally acquires the traffic light color steps and the countdown information of a vehicle driving road, thereby realizing the efficient passing of the vehicle at the traffic light intersection. Compared with the prior art, the method has the advantages that:
aiming at a common non-networked vehicle, the traffic light color and countdown information of the road junction can be obtained without establishing communication connection with a cloud big data platform;
aiming at vehicles without sensing capability such as cameras, radars and the like, traffic light color and countdown information of a road junction can be obtained without passing through a sensor;
traffic light data estimation is carried out aiming at the cloud big data platform, a large amount of traffic data of different vehicles is not needed to be used as a calculation basis, and traffic light color and countdown information can be calculated based on one vehicle driving data.
The traffic light color and the countdown information of the lane level can be displayed, and the traffic light color and the countdown information corresponding to the lane where the vehicle is located are respectively displayed aiming at the intersections with the straight line, the left turn and the right turn.
Further, according to the actual road condition experiment, in the normal working process of the testers, the measuring and calculating time passing through a certain intersection is within one week, and the time length reaching the same as the time length calculated by pinching after 12 times is approximately calculated.
It should be appreciated that in the development of any such actual implementation, as in any engineering or design project, numerous implementation-specific decisions may be made. Such a development effort might be complex and time consuming, but would nevertheless be a routine undertaking of design, fabrication, and manufacture for those of ordinary skill having the benefit of this disclosure.
It should be noted that the above embodiments are only for illustrating the technical solution of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that the technical solution of the present invention may be modified or substituted without departing from the spirit and scope of the technical solution of the present invention, which is intended to be covered in the scope of the claims of the present invention.
Claims (3)
1. A method for optimizing a vehicle to acquire traffic light color and countdown information is characterized by comprising the following steps: comprising the steps of (a) a step of,
acquiring vehicle self data;
triggering a timing state according to the vehicle speed;
triggering red light time calculation according to the position relation between the vehicle position and the intersection stop line when the vehicle stops;
calculating a traffic light period according to the red light time;
the vehicle self data comprises a vehicle position, a vehicle speed and a vehicle running course angle;
the triggering of the timing state according to the vehicle speed includes:
the vehicle compares and judges whether the front of the vehicle is a traffic light intersection or not based on the data of the vehicle and map data, and determines a lane to which the vehicle belongs;
the triggering the timing state according to the vehicle speed further includes:
setting a first speed threshold;
if the vehicle speed is smaller than the first speed threshold and is reduced to zero, starting timing from when the vehicle speed is zero to when the vehicle speed is not zero, and counting timing information;
the timing information comprises a timing starting time point and a timing period;
calculating the red light time comprises the following steps of;
comparing the stopping position of the vehicle with the map data to judge whether the vehicle is positioned at the stopping line;
if the vehicle is not at the stop line, storing the current position information, timing information and the distance from the stop line;
if the vehicle is at the stop line, storing the current position information and timing information of the vehicle, and calculating the red light duration of the lane corresponding to the road opening according to the stored time information;
the calculating of the red light duration of the lane corresponding to the road opening according to the stored time information comprises the following steps:
carding the timing period, and counting the occurrence times of the timing period in the data counting of multiple times;
setting a first time number threshold, namely firstly, enabling a timing period with the longest duration to be the duration of the red light, and marking the timing period as a first result red light duration X if the occurrence number of the timing period meets the first time number threshold;
if the number of times of the timing period does not meet the first time threshold, judging whether the timing period with shorter duration meets the first time threshold or not until a first result red light duration X is obtained;
comparing the vehicle stop position with the map data to determine whether the vehicle is located at the stop line includes:
comparing whether the distance between the stopping position of the vehicle and the stopping line in the map data is smaller than a first distance threshold value;
if the distance is smaller than the first distance threshold value, judging that the distance is at the stop line;
if the distance is greater than the first distance threshold, judging that the distance is not at the stop line;
calculating the traffic light period according to the red light time comprises the following steps:
the total duration of the green light yellow light is preset to be Y, and the traffic light period is X+Y;
determining two red light starting time points according to a judging mode of the first result red light duration X to obtain a measurement duration M containing Z traffic light periods, wherein the measurement duration M comprises the following steps:
（X+Y）Z=M；
from the measured sets of M-column equations:
；
wherein the method comprises the steps of~/>And->As is known, find a common solution for (X, Z) in the system of equations and output as a result.
2. The method for optimizing the acquisition of traffic light color and countdown information by a vehicle of claim 1, wherein: if the equation set has no common solution or a plurality of common solutions, the next timing period participates in calculation and adjusts the first time threshold value, and the second result red light duration X is selected to participate in calculation until the common solution is obtained.
3. The method for optimizing the acquisition of traffic light color and countdown information by a vehicle of claim 2, wherein:
the first speed threshold value is preset to be 5km/h, and feedback adjustment is calculated according to the red light time calculation traffic light period phase;
the first distance threshold is preset to be 1m, and feedback adjustment is calculated according to red light time calculation traffic light period phase.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202410156687.1A CN117690300B (en) | 2024-02-04 | 2024-02-04 | Method for optimizing vehicle to acquire traffic light color and countdown information |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202410156687.1A CN117690300B (en) | 2024-02-04 | 2024-02-04 | Method for optimizing vehicle to acquire traffic light color and countdown information |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN117690300A CN117690300A (en) | 2024-03-12 |
| CN117690300B true CN117690300B (en) | 2024-04-12 |
Family
ID=90130523
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202410156687.1A Active CN117690300B (en) | 2024-02-04 | 2024-02-04 | Method for optimizing vehicle to acquire traffic light color and countdown information |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117690300B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115631637B (en) * | 2022-10-26 | 2024-10-22 | 东风汽车集团股份有限公司 | Intelligent green wave speed judging method and system |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105761516A (en) * | 2016-05-16 | 2016-07-13 | 北京数行健科技有限公司 | Method for estimating intersection signal light timing based on vehicle tracks |
| CN113808404A (en) * | 2021-09-30 | 2021-12-17 | 重庆长安汽车股份有限公司 | Fixed-time-length traffic signal lamp time length prediction method |
| CN114023085A (en) * | 2021-11-04 | 2022-02-08 | 中山大学 | Intersection signal timing parameter inference method based on bayonet detection data |
| CN115601983A (en) * | 2022-10-14 | 2023-01-13 | 北京百度网讯科技有限公司（Cn） | Method, device, equipment and storage medium for determining cycle duration of traffic signal lamp |
| CN117351760A (en) * | 2023-10-23 | 2024-01-05 | 东软集团股份有限公司 | Method and device for determining change rule of traffic signal lamp and related products |
-
2024
- 2024-02-04 CN CN202410156687.1A patent/CN117690300B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105761516A (en) * | 2016-05-16 | 2016-07-13 | 北京数行健科技有限公司 | Method for estimating intersection signal light timing based on vehicle tracks |
| CN113808404A (en) * | 2021-09-30 | 2021-12-17 | 重庆长安汽车股份有限公司 | Fixed-time-length traffic signal lamp time length prediction method |
| CN114023085A (en) * | 2021-11-04 | 2022-02-08 | 中山大学 | Intersection signal timing parameter inference method based on bayonet detection data |
| CN115601983A (en) * | 2022-10-14 | 2023-01-13 | 北京百度网讯科技有限公司（Cn） | Method, device, equipment and storage medium for determining cycle duration of traffic signal lamp |
| CN117351760A (en) * | 2023-10-23 | 2024-01-05 | 东软集团股份有限公司 | Method and device for determining change rule of traffic signal lamp and related products |
Also Published As
| Publication number | Publication date |
|---|---|
| CN117690300A (en) | 2024-03-12 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN102737504B (en) | Method for estimating bus arrival time in real time based on drive characteristics | |
| US20230325550A1 (en) | Method, device, equipment for determining test evaluation information and computer storage medium | |
| CN117690300B (en) | Method for optimizing vehicle to acquire traffic light color and countdown information | |
| CN105799512B (en) | Overspeed of vehicle based reminding method and system | |
| WO2016066018A1 (en) | Safe visual recognition-based method for standard measurement/calculation of daytime tunnel entrance section illumination, and system thereof | |
| US20230050063A1 (en) | Method and Apparatus for Detecting Complexity of Traveling Scenario of Vehicle | |
| EP3358545A1 (en) | Travel control method and travel control device | |
| US20110106419A1 (en) | Methods for reducing the consumption and cost of fuel | |
| CN105118316A (en) | Curved road safe speed calculating method and caution system based on vehicle infrastructure cooperation | |
| US10755564B2 (en) | System to optimize SCATS adaptive signal system using trajectory data | |
| CN107578620B (en) | Method, system and device for calculating road traffic capacity based on lane level system | |
| CN110444015B (en) | Intelligent network-connected automobile speed decision method based on no-signal intersection partition | |
| CN112810614B (en) | Method and device for predicting average energy consumption of electric automobile | |
| CN103810854B (en) | A kind of based on the artificial intelligent transportation parameter detection method demarcated | |
| CN115331401A (en) | Intelligent analysis early warning system for running safety of vehicles in long-distance tunnel on highway | |
| CN114648231A (en) | Quality evaluation method for road-side data of vehicle-road cooperation | |
| CN111508225A (en) | Information processing method, traffic control method, information processing device, traffic control equipment and storage medium | |
| Hoque et al. | Modification of Webster’s delay formula under non-lane based heterogeneous road traffic condition | |
| CN114898565B (en) | Self-adaptive control method of buried traffic signal lamp | |
| CN111915880A (en) | Method for estimating effective traffic capacity of accident point of highway abnormal event | |
| CN115880919A (en) | Intelligent traffic light command system and method | |
| WO2005030544A2 (en) | Device and method for determining a vehicle motion quantity | |
| CN115985111A (en) | Method for measuring and calculating number of vehicles queued in whole road section based on single data of vehicle passing through bayonet | |
| CN111815944B (en) | Data validity detection method and device, electronic equipment and computer storage medium | |
| CN114596710A (en) | Method, device, equipment and medium for calculating time length of traffic light |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |