CN115665936A - Tunnel illumination energy-saving control strategy generation method, system, terminal and medium - Google Patents
Tunnel illumination energy-saving control strategy generation method, system, terminal and medium Download PDFInfo
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Abstract
The invention discloses a tunnel lighting energy-saving control strategy generation method, a system, a terminal and a medium, which relate to the technical field of tunnel lighting and have the technical scheme key points that: acquiring traffic flow information of an upstream side of a target tunnel, and performing simulation analysis according to the traffic flow information to obtain vehicle distribution density information of the target tunnel in a target period; constructing a correlation function between the vehicle light starting rate and the tunnel light intensity; based on the association function and the constraint condition of the tunnel illumination regulation and control frequency, establishing a strategy optimization model by taking the minimum sum of the tunnel illumination output power and the vehicle light power as a target; and inputting the vehicle distribution density information into a strategy optimization model to generate a tunnel illumination control strategy. The invention considers the influence of the tunnel light intensity on the starting of the vehicle light, not only reduces the tunnel light regulation frequency, but also reduces the total energy consumption during the tunnel operation, and realizes the low-carbon emission operation.
Description
Technical Field
The present invention relates to the field of tunnel lighting technologies, and in particular, to a method, a system, a terminal, and a medium for generating an energy-saving control strategy for tunnel lighting.
Background
The traditional tunnel lighting control mainly controls the lighting quantity and the light intensity of the tunnel lighting at different time periods, so that the aim of saving energy is fulfilled. Along with the frequent occurrence of tunnel traffic accidents, in order to improve the road surface condition in the tunnel and the visual enjoyment in the tunnel and reduce the fatigue of a driver, a method for intelligently controlling tunnel illumination based on the environmental change inside and outside the tunnel and the vehicle speed information is disclosed in the prior art.
However, because the environmental change influence factors are more and the vehicle speed information fluctuation is larger due to the influence of the road height and the peak, and the driving speeds of different vehicles are also different greatly, when the tunnel illumination is intelligently controlled based on the environmental change inside and outside the tunnel and the vehicle speed information, the tunnel illumination regulation and control frequency is too high, the service life of the tunnel illumination is seriously influenced, and the interference to the normal driving driver in the tunnel is also generated. In addition, the tunnel lighting control method increases energy consumption of tunnel lighting in the implementation process, and particularly, lamps may be turned on when a vehicle passes through a tunnel, which causes excessive energy consumption and excessive carbon emission during tunnel operation.
Therefore, how to research and design a tunnel lighting energy-saving control strategy generation method, system, terminal and medium capable of overcoming the above defects is a problem which is urgently needed to be solved at present.
Disclosure of Invention
In order to solve the defects in the prior art, the invention aims to provide a tunnel lighting energy-saving control strategy generation method, a tunnel lighting energy-saving control strategy generation system, a tunnel lighting energy-saving control terminal and a tunnel lighting energy-saving control medium, wherein the influence of tunnel light intensity on vehicle light starting is considered, and a tunnel lighting control strategy is obtained by solving the minimum total power value after tunnel lighting and vehicle light starting at the same time as an optimization target under the condition of meeting the power value which is required for entering a tunnel and weakening visual discomfort caused by light intensity change, so that the tunnel lighting control strategy is reduced, the tunnel light regulation frequency is reduced, the total energy consumption during tunnel operation is reduced, and low-carbon emission operation is realized.
The technical purpose of the invention is realized by the following technical scheme:
in a first aspect, a method for generating a tunnel lighting energy-saving control strategy is provided, which includes the following steps:
acquiring traffic flow information of an upstream side of a target tunnel, and performing simulation analysis according to the traffic flow information to obtain vehicle distribution density information of the target tunnel in a target period;
constructing a correlation function between the vehicle light starting rate and the tunnel light intensity;
based on the association function and the constraint condition of the tunnel illumination regulation and control frequency, establishing a strategy optimization model by taking the minimum sum of the tunnel illumination output power and the vehicle light power as a target;
and inputting the vehicle distribution density information into a strategy optimization model to generate a tunnel lighting control strategy.
Further, the process of acquiring the traffic flow information specifically includes:
calculating to obtain the minimum tunnel driving time according to the ratio of the tunnel length to the tunnel speed limit information;
calculating to obtain an acquisition spacing distance according to the product of the minimum tunnel driving time and the road speed limit information at the upstream side of the target tunnel;
selecting a place which is not less than the collection interval distance from an uplink entrance of the target tunnel as a collection place from the uplink side of the target tunnel;
and collecting traffic flow information at a collection place by taking the minimum tunnel driving time as collection time.
Further, the simulation analysis process of the vehicle distribution density information specifically includes:
determining the average speed of the vehicle according to the traffic flow information and the acquisition time, and taking the average speed of the vehicle as an estimated driving speed of the vehicle driving from the acquisition place to the upstream entrance of the target tunnel;
combining the estimated running speed, the standard braking acceleration and the tunnel speed limit information to carry out simulation analysis to obtain the time period of the vehicle running in the target tunnel;
and counting the number of the vehicles at the target tunnel at the same time node to obtain the distribution density information of the vehicles.
Further, the construction process of the association function specifically includes:
obtaining vehicle light starting data of a vehicle running under different tunnel light intensities;
and processing the vehicle light starting data by adopting a deep learning training model or a curve fitting method to obtain an association function representing the association relation between the vehicle light starting rate and the tunnel light intensity.
Further, the constraint conditions include:
the period of single tunnel illumination regulation is not less than the regulation interval time threshold;
and the difference of the tunnel illumination output power of adjacent tunnel illumination regulation is not greater than the regulation interval power threshold.
Further, the expression of the policy optimization model is specifically as follows:
wherein the content of the first and second substances,
representing the average power in a unit time after the vehicle light is started;
representing the regulation and control times of tunnel illumination in a target period;
is shown as
The tunnel illumination output power in the secondary regulation unit time;
is shown as
A period of secondary regulation;
is shown as
The termination time of the secondary regulation;
is shown as
The starting time of secondary regulation;
is represented by
The tunnel light intensity determined by the tunnel lighting output power in the secondary regulation unit time;
is represented by
The light starting rate of the vehicle is determined by the light intensity of the tunnel light in the secondary regulation;
representing the tunnel length;
to represent
The vehicle distribution density value at the moment;
represents a regulation interval time threshold;
representing a regulation interval power threshold;
is shown as
The tunnel illumination output power in the secondary regulation unit time;
the lower limit value of the tunnel lighting light regulation power is determined by the light intensity change conditions inside and outside the tunnel.
Further, the generation process of the tunnel lighting control strategy specifically includes:
solving the regulation and control periods in the target period and the total value of the tunnel illumination output power in each regulation and control period through a strategy optimization model;
and obtaining a tunnel illumination control strategy meeting the total value of tunnel illumination output power by regulating the quantity of tunnel illumination lights and/or regulating the actual working power of single tunnel illumination light.
In a second aspect, a tunnel lighting energy-saving control strategy generation system is provided, including:
the data acquisition module is used for acquiring traffic flow information of the upstream side of the target tunnel and obtaining vehicle distribution density information of the target tunnel in a target period according to traffic flow information simulation analysis;
the function construction module is used for constructing a correlation function between the vehicle light starting rate and the tunnel light intensity;
the model building module is used for building a strategy optimization model by taking the minimum sum of the tunnel illumination output power and the vehicle light power as a target based on the association function and the constraint condition of the tunnel illumination regulation and control frequency;
and the strategy optimization module is used for inputting the vehicle distribution density information into the strategy optimization model to generate and obtain the tunnel lighting control strategy.
In a third aspect, a computer terminal is provided, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and when the processor executes the program, the processor implements the method for generating the energy-saving control strategy for tunnel lighting according to any one of the first aspect.
In a fourth aspect, a computer-readable medium is provided, on which a computer program is stored, the computer program being executed by a processor to implement a tunnel lighting energy-saving control strategy generation method according to any one of the first aspect.
Compared with the prior art, the invention has the following beneficial effects:
1. the tunnel lighting energy-saving control strategy generation method considers the influence of tunnel light intensity on vehicle light starting, and solves the optimization target of minimum total power value after the tunnel lighting and the vehicle light are simultaneously started to obtain the tunnel lighting control strategy under the condition of meeting the power value which is used for weakening visual discomfort caused by light intensity change when the vehicle light enters a tunnel, so that the tunnel lighting control strategy is obtained, the tunnel light regulation and control frequency is reduced, the total energy consumption during tunnel operation is reduced, and low-carbon emission operation is realized;
2. according to the method, the collection place is selected at the upstream side of the target tunnel to collect the traffic flow information, and the vehicle distribution density information of the target tunnel in the target period is obtained through simulation analysis according to the traffic flow information, so that the condition that the accuracy of tunnel illumination regulation and control is reduced due to delay in real-time data processing is reduced, and the reliability of tunnel illumination control is higher;
3. the invention can realize the regulation and control of the tunnel illumination output power by regulating and controlling the quantity of the tunnel illumination lights, and can also realize the regulation and control of the tunnel illumination output power by regulating and controlling the actual working power of the single tunnel illumination light, and the regulation and control flexibility is stronger.
Drawings
The accompanying drawings, which are included to provide a further understanding of the embodiments of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the principles of the invention. In the drawings:
FIG. 1 is a flow chart in an embodiment of the invention;
fig. 2 is a block diagram of a system in an embodiment of the invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail below with reference to examples and the accompanying drawings, and the exemplary embodiments and descriptions thereof are only used for explaining the present invention and are not used as limiting the present invention.
Example 1: a method for generating a tunnel lighting energy-saving control strategy, as shown in fig. 1, includes the following steps:
step S1: acquiring traffic flow information of an upstream side of a target tunnel, and performing simulation analysis according to the traffic flow information to obtain vehicle distribution density information of the target tunnel in a target period;
step S2: constructing a correlation function between the vehicle light starting rate and the tunnel light intensity;
and step S3: based on the association function and the constraint condition of the tunnel illumination regulation and control frequency, establishing a strategy optimization model by taking the minimum sum of the tunnel illumination output power and the vehicle light power as a target;
and step S4: and inputting the vehicle distribution density information into a strategy optimization model to generate a tunnel illumination control strategy.
The process of acquiring the traffic flow information specifically comprises the following steps: calculating to obtain the minimum tunnel driving time according to the ratio of the tunnel length to the tunnel speed limit information; calculating to obtain an acquisition spacing distance according to the product of the minimum tunnel driving time and the road speed limit information at the upstream side of the target tunnel; selecting a place which is not less than the collection interval distance from an uplink entrance of the target tunnel as a collection place from the uplink side of the target tunnel; and collecting traffic flow information at a collection place by taking the minimum tunnel driving time as collection time.
In addition, the traffic flow information can also be obtained by analyzing the positioning information uploaded by the vehicle-mounted terminal, and the acquisition mode of the traffic flow information is not limited at the position.
The simulation analysis process of the vehicle distribution density information specifically comprises the following steps: determining the average speed of the vehicle according to the traffic flow information and the acquisition time, and taking the average speed of the vehicle as an estimated driving speed of the vehicle driving from the acquisition place to the upstream entrance of the target tunnel; combining the estimated running speed, the standard braking acceleration and the tunnel speed limit information to carry out simulation analysis to obtain the time period of the vehicle running in the target tunnel; the number of vehicles in the target tunnel at the same time node is counted to obtain vehicle distribution density information, so that the situation that the accuracy of tunnel illumination regulation and control is reduced due to delay in real-time data processing can be reduced, and the reliability of tunnel illumination control is higher. In addition, the vehicle distribution density information can also be obtained after identifying the video images collected in the tunnel in real time, and is not limited herein.
The construction process of the association function specifically comprises the following steps: obtaining vehicle light starting data of a vehicle running under different tunnel light intensities; and processing the vehicle light starting data by adopting a deep learning training model or a curve fitting method to obtain an association function representing the association relation between the vehicle light starting rate and the tunnel light intensity.
The constraint conditions include, but are not limited to, that the period of single tunnel illumination regulation is not less than the regulation interval time threshold, the difference between the tunnel illumination output powers of adjacent tunnel illumination regulation is not greater than the regulation interval power threshold, and the total power value after the tunnel illumination and the vehicle light are simultaneously activated is not less than the lower limit value of the tunnel illumination light regulation power determined by the light intensity change conditions inside and outside the tunnel.
The expression of the strategy optimization model is specifically as follows:
wherein the content of the first and second substances,
representing the average power in a unit time after the vehicle light is started;
representing the regulation and control times of tunnel illumination in a target period;
is shown as
The tunnel illumination output power in the secondary regulation unit time;
is shown as
A secondary regulation period;
is shown as
The termination time of the secondary regulation;
is shown as
The starting time of secondary regulation;
is represented by
The tunnel light intensity determined by the tunnel lighting output power in the secondary regulation unit time;
is represented by
The light starting rate of the vehicle is determined by the light intensity of the tunnel light in the secondary regulation;
representing the tunnel length;
represent
The vehicle distribution density value at the moment;
represents a regulation interval time threshold;
representing a regulation interval power threshold;
is shown as
The tunnel illumination output power in the secondary regulation unit time;
the lower limit value of the tunnel lighting light regulation power is determined by the light intensity change conditions inside and outside the tunnel.
The generation process of the tunnel lighting control strategy specifically comprises the following steps: solving the regulation and control periods in the target period and the total value of the tunnel illumination output power in each regulation and control period through a strategy optimization model; and obtaining a tunnel illumination control strategy meeting the total value of tunnel illumination output power by regulating the quantity of tunnel illumination lights and/or regulating the actual working power of single tunnel illumination light.
Example 2: a system for generating an energy-saving control strategy for tunnel lighting in embodiment 1 is used to implement the method for generating an energy-saving control strategy for tunnel lighting, and as shown in fig. 2, includes a data acquisition module, a function construction module, a model construction module, and a strategy optimization module.
The data acquisition module is used for acquiring traffic flow information of the upstream side of the target tunnel and obtaining vehicle distribution density information of the target tunnel in a target period according to traffic flow information simulation analysis; the function construction module is used for constructing a correlation function between the vehicle light starting rate and the tunnel light intensity; the model building module is used for building a strategy optimization model by taking the minimum sum of the tunnel illumination output power and the vehicle light power as a target based on the association function and the constraint condition of the tunnel illumination regulation and control frequency; and the strategy optimization module is used for inputting the vehicle distribution density information into the strategy optimization model to generate and obtain the tunnel illumination control strategy.
The working principle is as follows: the method considers the influence of the tunnel light intensity on the starting of the vehicle light, solves the optimization target with the minimum total power value after the tunnel lighting and the vehicle light are simultaneously started to obtain the tunnel lighting control strategy under the condition of meeting the power value which is used for weakening visual discomfort caused by light intensity change when the vehicle light enters the tunnel, reduces the tunnel light regulation and control frequency, reduces the total energy consumption during the tunnel operation, and realizes the low-carbon emission operation.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and so forth) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above embodiments are provided to further explain the objects, technical solutions and advantages of the present invention in detail, it should be understood that the above embodiments are merely exemplary embodiments of the present invention and are not intended to limit the scope of the present invention, and any modifications, equivalents, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (10)
1. A tunnel lighting energy-saving control strategy generation method is characterized by comprising the following steps:
acquiring traffic flow information of an upstream side of a target tunnel, and performing simulation analysis according to the traffic flow information to obtain vehicle distribution density information of the target tunnel in a target period;
constructing a correlation function between the vehicle light starting rate and the tunnel light intensity;
based on the association function and the constraint condition of the tunnel illumination regulation and control frequency, establishing a strategy optimization model by taking the minimum sum of the tunnel illumination output power and the vehicle light power as a target;
and inputting the vehicle distribution density information into a strategy optimization model to generate a tunnel illumination control strategy.
2. The method for generating the tunnel lighting energy-saving control strategy according to claim 1, wherein the obtaining process of the traffic flow information specifically comprises:
calculating to obtain the minimum tunnel driving time according to the ratio of the tunnel length to the tunnel speed limit information;
calculating to obtain an acquisition spacing distance according to the product of the minimum tunnel driving time and the road speed limit information at the upstream side of the target tunnel;
selecting a place which is not less than the collection interval distance from an uplink entrance of the target tunnel as a collection place from the uplink side of the target tunnel;
and collecting traffic flow information at a collection place by taking the minimum tunnel driving time as collection time.
3. The method for generating the tunnel lighting energy-saving control strategy according to claim 1, wherein the simulation analysis process of the vehicle distribution density information specifically comprises:
determining the average speed of the vehicle according to the traffic flow information and the acquisition time, and taking the average speed of the vehicle as an estimated driving speed of the vehicle driving from the acquisition place to the upstream entrance of the target tunnel;
combining the estimated running speed, the standard braking acceleration and the tunnel speed limit information to carry out simulation analysis to obtain the time period of the vehicle running in the target tunnel;
and counting the number of the vehicles at the target tunnel at the same time node to obtain the distribution density information of the vehicles.
4. The method according to claim 1, wherein the association function is constructed by:
obtaining vehicle light starting data of a vehicle running under different tunnel light intensities;
and processing the vehicle light starting data by adopting a deep learning training model or a curve fitting method to obtain an association function representing the association relation between the vehicle light starting rate and the tunnel light intensity.
5. The method as claimed in claim 1, wherein the constraint condition includes:
the period of single tunnel illumination regulation is not less than the regulation interval time threshold;
and the difference of the tunnel illumination output power of adjacent tunnel illumination regulation is not greater than the regulation interval power threshold.
6. The method as claimed in claim 1, wherein the expression of the policy optimization model is specifically:
wherein the content of the first and second substances,
representing the average power in a unit time after the vehicle light is started;
representing the regulation and control times of tunnel illumination in a target period;
is shown as
The tunnel illumination output power in the secondary regulation unit time;
is shown as
A secondary regulation period;
is shown as
The termination time of the secondary regulation;
is shown as
The starting time of secondary regulation;
is represented by
The tunnel light intensity determined by the tunnel lighting output power in the secondary regulation unit time;
is represented by
The light starting rate of the vehicle is determined by the light intensity of the tunnel light in the secondary regulation;
represents the tunnel length;
to represent
The vehicle distribution density value at the moment;
represents a regulation interval time threshold;
representing a regulation interval power threshold;
is shown as
The tunnel illumination output power in the secondary regulation unit time;
the lower limit value of the tunnel lighting light regulation power is determined by the light intensity change conditions inside and outside the tunnel.
7. The method according to claim 1, wherein the tunnel lighting energy-saving control strategy is generated by:
solving the regulation and control periods in the target period and the total value of the tunnel illumination output power in each regulation and control period through a strategy optimization model;
and obtaining a tunnel illumination control strategy meeting the total value of tunnel illumination output power by regulating the quantity of tunnel illumination lights and/or regulating the actual working power of single tunnel illumination light.
8. A tunnel lighting energy-saving control strategy generation system is characterized by comprising:
the data acquisition module is used for acquiring traffic flow information of the upstream side of the target tunnel and obtaining vehicle distribution density information of the target tunnel in a target period according to traffic flow information simulation analysis;
the function construction module is used for constructing a correlation function between the vehicle light starting rate and the tunnel light intensity;
the model building module is used for building a strategy optimization model by taking the minimum sum of the tunnel illumination output power and the vehicle light power as a target based on the association function and the constraint condition of the tunnel illumination regulation and control frequency;
and the strategy optimization module is used for inputting the vehicle distribution density information into the strategy optimization model to generate and obtain the tunnel illumination control strategy.
9. A computer terminal comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements a tunnel lighting energy saving control strategy generation method according to any one of claims 1 to 7 when executing the program.
10. A computer-readable medium, on which a computer program is stored, wherein the computer program is executed by a processor to implement a tunnel lighting energy-saving control strategy generation method according to any one of claims 1 to 7.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116347714A (en) * | 2023-05-23 | 2023-06-27 | 厦门普为光电科技有限公司 | Tunnel illumination control system with illumination automatic adjustment function |
| CN116761309A (en) * | 2023-06-14 | 2023-09-15 | 贵州中南交通科技有限公司 | Tunnel energy-saving intelligent management system and method |
| CN117056866A (en) * | 2023-10-12 | 2023-11-14 | 贵州新思维科技有限责任公司 | Tunnel intelligent dimming method and system with multi-source characteristic data fusion |
Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6161065A (en) * | 1997-04-08 | 2000-12-12 | Nissan Motor Co., Ltd. | Control system for vehicular illumination |
| DE102006001261A1 (en) * | 2005-01-14 | 2006-07-20 | Denso Corp., Kariya | Tunnel detection device and light control device for a vehicle |
| US20130169155A1 (en) * | 2010-09-17 | 2013-07-04 | Kazuhiko Nakashima | Headlamp device and luminance control method therefor |
| CN105188198A (en) * | 2015-08-21 | 2015-12-23 | Tcl集团股份有限公司 | Tunnel driving lamp control method and system, and mobile terminal |
| CN110572912A (en) * | 2019-08-09 | 2019-12-13 | 厦门理工学院 | Light control method for tunnel driving light |
| CN110774975A (en) * | 2019-11-13 | 2020-02-11 | 上海智驾汽车科技有限公司 | Intelligent light control method and device based on image recognition |
| CN211139159U (en) * | 2019-08-09 | 2020-07-31 | 厦门理工学院 | Vehicle-mounted light control device and system |
| CN111885792A (en) * | 2020-08-10 | 2020-11-03 | 招商局重庆交通科研设计院有限公司 | Method for optimizing lighting design speed of highway tunnel in alpine region |
| CN112165747A (en) * | 2020-09-27 | 2021-01-01 | 西安工业大学 | Intelligent LED illumination regulation and control device for entrance section of expressway tunnel |
| CN113525223A (en) * | 2021-07-28 | 2021-10-22 | 中国第一汽车股份有限公司 | Vehicle lamp control method and device, computer equipment and storage medium |
| CN113630939A (en) * | 2021-07-30 | 2021-11-09 | 中汽创智科技有限公司 | Tunnel driving system, method and device, electronic equipment and storage medium |
| CN113747637A (en) * | 2021-08-03 | 2021-12-03 | 安徽长龙电气集团有限公司 | Night illumination optimization method for long tunnel entrance section of expressway |
| CN113923833A (en) * | 2021-10-20 | 2022-01-11 | 重庆交通大学 | Low traffic volume tunnel intelligence energy-saving control system based on deceleration strip |
| CN115529696A (en) * | 2022-10-11 | 2022-12-27 | 西南交通大学 | Tunnel illumination intensity control system based on vehicle positioning |
-
2022
- 2022-12-28 CN CN202211687635.4A patent/CN115665936B/en active Active
Patent Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6161065A (en) * | 1997-04-08 | 2000-12-12 | Nissan Motor Co., Ltd. | Control system for vehicular illumination |
| DE102006001261A1 (en) * | 2005-01-14 | 2006-07-20 | Denso Corp., Kariya | Tunnel detection device and light control device for a vehicle |
| US20130169155A1 (en) * | 2010-09-17 | 2013-07-04 | Kazuhiko Nakashima | Headlamp device and luminance control method therefor |
| CN105188198A (en) * | 2015-08-21 | 2015-12-23 | Tcl集团股份有限公司 | Tunnel driving lamp control method and system, and mobile terminal |
| CN211139159U (en) * | 2019-08-09 | 2020-07-31 | 厦门理工学院 | Vehicle-mounted light control device and system |
| CN110572912A (en) * | 2019-08-09 | 2019-12-13 | 厦门理工学院 | Light control method for tunnel driving light |
| CN110774975A (en) * | 2019-11-13 | 2020-02-11 | 上海智驾汽车科技有限公司 | Intelligent light control method and device based on image recognition |
| CN111885792A (en) * | 2020-08-10 | 2020-11-03 | 招商局重庆交通科研设计院有限公司 | Method for optimizing lighting design speed of highway tunnel in alpine region |
| CN112165747A (en) * | 2020-09-27 | 2021-01-01 | 西安工业大学 | Intelligent LED illumination regulation and control device for entrance section of expressway tunnel |
| CN113525223A (en) * | 2021-07-28 | 2021-10-22 | 中国第一汽车股份有限公司 | Vehicle lamp control method and device, computer equipment and storage medium |
| CN113630939A (en) * | 2021-07-30 | 2021-11-09 | 中汽创智科技有限公司 | Tunnel driving system, method and device, electronic equipment and storage medium |
| CN113747637A (en) * | 2021-08-03 | 2021-12-03 | 安徽长龙电气集团有限公司 | Night illumination optimization method for long tunnel entrance section of expressway |
| CN113923833A (en) * | 2021-10-20 | 2022-01-11 | 重庆交通大学 | Low traffic volume tunnel intelligence energy-saving control system based on deceleration strip |
| CN115529696A (en) * | 2022-10-11 | 2022-12-27 | 西南交通大学 | Tunnel illumination intensity control system based on vehicle positioning |
Non-Patent Citations (2)
| Title |
|---|
| WENHAO ZONG: "Vehicle model based visual-tag monocular ORB-SLAM" * |
| 黄鹤: "低流量高速公路隧道照明节能系统设计方法" * |
Cited By (6)
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| CN116347714B (en) * | 2023-05-23 | 2023-08-11 | 厦门普为光电科技有限公司 | Tunnel illumination control system with illumination automatic adjustment function |
| CN116761309A (en) * | 2023-06-14 | 2023-09-15 | 贵州中南交通科技有限公司 | Tunnel energy-saving intelligent management system and method |
| CN116761309B (en) * | 2023-06-14 | 2024-02-02 | 贵州中南交通科技有限公司 | Tunnel energy-saving intelligent management system and method |
| CN117056866A (en) * | 2023-10-12 | 2023-11-14 | 贵州新思维科技有限责任公司 | Tunnel intelligent dimming method and system with multi-source characteristic data fusion |
| CN117056866B (en) * | 2023-10-12 | 2024-01-30 | 贵州新思维科技有限责任公司 | Tunnel intelligent dimming method and system with multi-source characteristic data fusion |
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