CN216110866U - Tunnel vehicle accident detection and early warning device based on RSSI - Google Patents
Tunnel vehicle accident detection and early warning device based on RSSI Download PDFInfo
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- CN216110866U CN216110866U CN202120982224.2U CN202120982224U CN216110866U CN 216110866 U CN216110866 U CN 216110866U CN 202120982224 U CN202120982224 U CN 202120982224U CN 216110866 U CN216110866 U CN 216110866U
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Abstract
The utility model discloses a tunnel vehicle accident detection and early warning device based on RSSI (received signal strength indicator). The device comprises a WiFi detection module, a remote computing center and an accident early warning module; the WiFi detection module comprises a vehicle-mounted unit installed in a target vehicle and a WiFi detector installed in a tunnel, and is used for receiving information sent by the vehicle-mounted unit in the target vehicle and transmitting the information to the remote computing center; the remote computing center detects and processes the accident according to the received information and sends the processing result to the accident early warning module; and the accident early warning module carries out accident early warning according to the processing result. The utility model realizes the signal transmission based on the wireless communication technology DSRC, eliminates the phenomenon of same frequency interference and can ensure the communication effect of vehicles in a high-speed semi-closed environment; meanwhile, the vehicle positioning algorithm based on the RSSI value is adopted, and the vehicle positioning method has the advantages of low cost, convenience and quickness in installation, easiness in maintenance and realization of real-time high-precision positioning and detection.
Description
Technical Field
The utility model relates to the field of traffic safety, in particular to a tunnel vehicle accident detection and early warning device based on RSSI (received signal strength indicator).
Background
The tunnel is an engineering building buried in the ground and is a special road form for people to pass by using underground space. Due to the closed characteristic, the light condition in the tunnel is poor, the sight of a driver is affected, accidents such as rear-end collision, scratch and the like are easily caused in the tunnel, and then a series of road congestion is caused. Meanwhile, signals in the tunnel are weak, and it is difficult to find a reporting department mechanism in time and effectively transmit the reported department mechanism to a subsequent vehicle when a traffic accident occurs, so that the subsequent vehicle is easy to continuously drive in, and a secondary accident is caused. For the reasons, it is very important and necessary to develop a tunnel vehicle accident detection and early warning device with low cost, convenient installation, easy maintenance and high precision.
For the detection of the vehicle accident in the tunnel, the traffic flow parameters such as the average driving speed and the moving direction of the vehicle are mainly obtained by means of GPS positioning detection, video detection, detection based on the traffic flow parameters and the like at present, and the vehicle accident in the tunnel is judged on the basis of the traffic flow parameters. In the literature, "a traffic accident detection method based on video", a video detector-based accident detection method is adopted by a worship, and the motion state of the vehicle at the next moment is predicted by analyzing a background picture to judge whether the vehicle has an accident; in the literature, "simulation research for automatic detection of tunnel traffic accident", a method based on a traffic flow parameter theory is adopted to detect accidents, and traffic flow parameters such as vehicle density and flow rate can be changed when an accident occurs, so that the accident can be judged. Due to the sealing property inside the tunnel, the conventional GPS navigation positioning is difficult to realize high-precision real-time positioning in the tunnel, and the accident rescue in the tunnel is difficult, so that more serious secondary accidents are easily caused if the accident rescue is not timely processed. The GPS positioning can not be used in the tunnel due to weak signals, the accuracy of the cellular network positioning is not high, the position estimation is very rough, and the method is only suitable for O-D measurement. The precision of video detection is influenced by insufficient illumination in the tunnel and optical noise, and the detection precision in the tunnel is difficult to ensure; the detection method based on the traffic flow parameters is not high in detection efficiency, and often causes certain traffic jam when an accident is detected.
With the development of wireless sensing technology, the target positioning method based on wireless communication signals is receiving more and more attention from engineers and researchers. In the literature, "indoor WiFi positioning algorithm based on RSSI" Zhuzhengwei adopts WiFi detection technology to carry out indoor positioning research, and research shows that higher positioning accuracy can be achieved; huang Zilin in Multi-Stage geometric Positioning Using Filtered WiFi Scanner Data in an umbrella Road Environment performs Positioning research on outdoor pedestrians based on a WiFi detection technology, and obtains high Positioning precision. The research of the WiFi detection positioning technology based on the RSSI has obtained great achievements at present, not only can realize the real-time high-precision positioning of the vehicle, but also has the advantages of low cost, strong applicability in the tunnel and no influence of light line parts, so that the high precision can be achieved in the accident detection in the tunnel.
SUMMERY OF THE UTILITY MODEL
Aiming at the defects in the prior art, the utility model provides a tunnel vehicle accident detection and early warning device based on RSSI. The device acquires RSSI value, MAC address and timestamp information through WiFi wireless sensing technology, analyzes the acquired RSSI value through a signal attenuation model, extracts the distance between a target vehicle and a detector, and then converts the acquired distance into Euler distance through a position distance algorithm, thereby realizing accurate positioning of the vehicle, detecting tunnel accidents in real time, timely reminding rear vehicle front accidents and effectively avoiding secondary accidents. The algorithm for solving the target position by using the signal attenuation model is a relatively mature algorithm in the industry, and is currently used in an indoor positioning method based on RSSI (patent publication No. CN104619016A), an intelligent swimming bracelet based on RSSI wireless positioning technology (patent publication No. CN104433009A) and the like. The accident detection module judges the time-varying condition of vehicle positioning, and if the detected vehicle speed is far lower than the normal running speed or the longitudinal distance between two vehicles on the same lane is smaller than the length of a normal car, the traffic accident in the detection area is judged. The algorithm used by the accident detection module is also an algorithm mature in the industry, and is currently used in a control system and a method for preventing secondary accidents of automobiles in an expressway tunnel (patent publication No. CN107881951A), a tunnel driving safety early warning system and a tunnel driving safety early warning method based on vehicle driving state detection (patent publication No. CN108399794A) and the like. Further, when a traffic accident exists in the tunnel, the early warning module in the device can display accident information on a traffic information board, so that subsequent vehicles can conveniently know the current situation, and the travel is adjusted in time. The method has the advantages of high positioning precision, individual identification function, low equipment cost, simple and convenient installation, no need of damaging the road surface and easy maintenance in the later period.
The purpose of the utility model is realized by at least one of the following technical solutions.
A tunnel vehicle accident detection and early warning device based on RSSI comprises a WiFi detection module, a remote computing center and an accident early warning module;
the WiFi detection module comprises a vehicle-mounted unit installed in a target vehicle and a WiFi detector installed in a tunnel, and is used for receiving information sent by the vehicle-mounted unit in the target vehicle and transmitting the information to the remote computing center; the remote computing center detects and processes the accident according to the received information and sends the processing result to the accident early warning module; and the accident early warning module carries out accident early warning according to the processing result.
Further, the vehicle-mounted unit comprises a storage module, a DSRC communication module and a power supply module, and the WiFi detector comprises a WiFi probe network card and a router;
the WiFi probe network card collects detection request frame signal information sent by the DSRC communication module through the DSRC wireless communication technology, receives signal information of a target vehicle, comprises a mac address of the vehicle-mounted unit, RSSI signal strength and a corresponding timestamp, and sends the signal information to the remote computing center through the local area network.
Furthermore, the power supply module is powered by a solar panel and a lithium battery.
Furthermore, the WiFi probe network card and the router adopt a DS-007 detector, and the functions of the WiFi probe network card and the router are integrated;
the WiFi probe network card is used for detecting external WiFi signals and intensity and supporting Ethernet ports, WiFi and external USB flash disks to transmit data; the router has the function of connecting WiFi internet and supports the function of starting hot spots.
Further, the WiFi detectors are installed on the two sides of the tunnel, the height of the WiFi detectors is 1-1.5 meters, and the maximum detection distance of each WiFi detector is 200-300 meters in radius.
Further, the remote computing center comprises a vehicle positioning unit, an accident detection unit and a data storage unit;
the vehicle positioning unit positions the target vehicle in real time according to the received signal information of the target vehicle; the accident detection unit judges whether an accident occurs according to the real-time positioning data of the target vehicle, and sends a judgment result to the accident early warning module through the Ethernet after the accident occurs; the data storage unit stores the position results, the calculation results and the judgment results of the vehicle positioning unit and the accident detection unit.
Further, in the vehicle positioning unit, a signal attenuation model is adopted to calculate the Euclidean distance of the RSSI signal intensity, and the distance between the target vehicle and the WiFi detector is determined; and (3) positioning the specific position of the target vehicle based on a classical trilateration model, and analyzing the speed, the relative speed and the relative position of all vehicles.
Further, in the accident detection module, the time-varying situation of vehicle positioning is judged according to the specific position of the target vehicle, the speed, the relative speed and the relative position of all vehicles are analyzed, and if the fact that the speed of the target vehicle is far lower than the normal running speed or the longitudinal distance between two vehicles on the same lane is smaller than the length of a normal car is detected, it is judged that a traffic accident exists in a detection area;
furthermore, the accident early warning module comprises a traffic information board, the traffic information board is connected with an accident detection unit of the remote computing center through the Ethernet, and accident early warning information is displayed according to the received judgment result, wherein the accident early warning information comprises visibility of a front tunnel entrance, traffic flow in the tunnel, weather and time and date auxiliary information.
Furthermore, the accident early warning module transmits the accident early warning information displayed on the traffic information board back to the traffic control command center for recording, so that the control of personnel in the control command center is facilitated.
The utility model has the beneficial effects that:
(1) the device has the advantages of low cost, convenient installation, easy maintenance and realization of real-time high-precision positioning and detection based on the RSSI vehicle positioning scheme;
(2) under the scene that the driving sight line in the tunnel is influenced, the WiFi detection module of the device realizes the functions of real-time high-precision positioning of vehicles in the tunnel, accident detection and early warning by arranging a plurality of WiFi detectors, ensures the safety of tunnel passing and improves the tunnel passing efficiency;
(3) the WiFi detection module of the device realizes the collection of vehicle information by utilizing the connection between a plurality of WiFi detectors and the vehicle-mounted unit, and can ensure the communication effect of the device under the semi-closed condition in the tunnel.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and those skilled in the art can also obtain other drawings according to the drawings without inventive labor.
Fig. 1 is a block diagram of a tunnel vehicle accident detection and early warning device based on RSSI according to the present invention;
fig. 2 is a flowchart of a scheme of the RSSI-based tunnel vehicle accident detection and early warning apparatus according to the present invention.
Fig. 3 is a schematic diagram of an application of the RSSI-based tunnel vehicle accident detection and early warning apparatus according to the present invention.
Detailed Description
The following description of specific embodiments of representative embodiments of the utility model will be made with reference to the accompanying drawings, which are provided for illustration of the representative embodiments of the utility model. It is to be understood that the described representative embodiments are for purposes of illustration and explanation only and are not to be construed as limiting the utility model.
The key point of the present invention is to provide a technical solution for the structural part, and the following embodiments, if they relate to software or a control part, can be implemented by those skilled in the art by referring to the prior art.
Example (b):
an RSSI-based tunnel vehicle accident detection and early warning device is shown in figure 1 and comprises a WiFi detection module 101, a remote computing center 102 and an accident early warning module 103;
the WiFi detection module 101 comprises an on-board unit (OBU)201 installed in a target vehicle and a WiFi detector 202 installed in a tunnel, and receives information sent by the on-board unit 201 in the target vehicle and transmits the information to the remote computing center 102; the remote computing center 102 detects and processes the accident according to the received information, and sends the processing result to the accident early warning module 103; and the accident early warning module 103 carries out accident early warning according to the processing result.
The vehicle-mounted unit 201 comprises a storage module 302, a DSRC communication module 301 and a power supply module 303, and the WiFi detector 202 comprises a WiFi probe network card 304 and a router 305;
the WiFi probe network card 304 collects the probe request frame signal information sent by the DSRC communication module 301 through the DSRC wireless communication technology, receives the signal information of the target vehicle, including the mac address, RSSI signal strength and corresponding timestamp of the on-board unit 201, and sends to the remote computing center 102 through the local area network.
In this embodiment, the power supply module 303 is powered by a solar panel and a lithium battery.
In this embodiment, the WiFi probe network card 304 and the router 305 adopt a DS-007 detector (manufactured by china chengdu DataSky company), and integrate the functions of the WiFi probe network card 304 and the router 305;
the WiFi probe network card 304 is used for detecting external WiFi signals and intensity and supporting Ethernet ports, WiFi and external USB flash disks to transmit data; the router 305 has a WiFi internet access function and supports a hot spot opening function.
The WiFi detectors 202 are installed on the two sides of the tunnel at a height of 1-1.5 meters, and the maximum detection distance of each WiFi detector 202 is 300 meters with a radius of 200-.
The remote computing center 102 includes a vehicle locating unit 203, an accident detection unit 205, and a data storage unit 204;
the vehicle positioning unit 203 positions the target vehicle in real time according to the received signal information of the target vehicle; the accident detection unit 205 determines whether an accident occurs according to the real-time positioning data of the target vehicle, and the accident detection unit 205 sends the determination result to the accident warning module 103 through the ethernet after determining that the accident occurs; the data storage unit 204 stores the position results, calculation results, and determination results of the vehicle positioning unit 203 and the accident detection unit 205.
In the vehicle positioning unit 203, a signal attenuation model is adopted to calculate the Euclidean distance of the RSSI signal strength, and the distance between the target vehicle and the WiFi detector 202 is determined; and positioning the specific position of the target vehicle based on a classical trilateral positioning model.
In the accident detection module, judging the time-varying situation of vehicle positioning according to the specific position of a target vehicle, analyzing the speed, the relative speed and the relative position of all vehicles, and judging that a traffic accident exists in a detection area if the speed of the target vehicle is far lower than the normal running speed or the longitudinal distance between two vehicles on the same lane is smaller than the length of a normal car;
the accident early warning module 103 comprises a traffic information board 206, the traffic information board 206 is connected with the accident detection unit 205 of the remote computing center 102 through the ethernet, and displays accident early warning information according to the received judgment result, wherein the accident early warning information comprises the visibility of the front tunnel entrance, the traffic flow in the tunnel, the weather and the auxiliary information of time and date.
The accident early warning module 103 transmits the accident early warning information displayed on the traffic information board 206 back to the traffic control command center for recording, so as to facilitate the control of the personnel in the control command center.
In this embodiment, a work flow of the tunnel vehicle accident detection and early warning system based on the WiFi detection technology, as shown in fig. 2, includes the following steps:
step S1: starting the device, the WiFi detector 202 acquires the mac address, RSSI signal strength and corresponding timestamp of the on board unit 201;
step S2: the WiFi detector 202 transmits the uploaded data such as the Mac address, the RSSI signal strength and the timestamp of the vehicle-mounted unit 201 to the remote computing center 102;
step S3: the vehicle positioning unit 203 of the remote computing center 102 preprocesses the acquired data, calculates the distance, realizes vehicle positioning, and stores the position result in the data storage unit 204, as shown in fig. 3, specifically as follows:
the vehicle positioning unit 203 preprocesses the collected data and screens out invalid data using the 3 sigma criterion.
The vehicle positioning unit 203 performs filtering processing on the data by a kalman filter algorithm.
The vehicle positioning unit 203 calculates the distance between the vehicle-mounted unit 201 and the WiFi detector 202 by using an RSSI-distance logarithm model.
The vehicle positioning unit 203 uses trilateration to position the on-board unit 201 according to the distances between the on-board unit 201 and the WiFi detectors 202.
Step S4: the accident detection unit 205 in the remote computing center 102 performs speed calculation on the real-time positioning data, analyzes the speed, the relative position, and the like of all vehicles, determines whether an accident occurs, and stores the calculation result and the determination result in the data storage unit 204, as shown in fig. 3, specifically as follows:
the accident detection unit 205 calculates the average speed of the on-board unit 201 within the adjacent time stamp.
The accident detection unit 205 compares the average speed of the vehicle-mounted units 201 in the adjacent timestamps with the vehicle average speed threshold value when an accident occurs, and determines that a traffic accident occurs when the average speed of the vehicle-mounted units 201 in the consecutive 5 adjacent timestamps is lower than the vehicle average speed threshold value when the accident occurs or the longitudinal distance between two vehicles in the same lane is smaller than the length of a normal car.
Step S5: the accident detection unit 205 in the remote computing center 102, when determining that an accident occurs, communicates with the accident early warning module 103, starts an accident early warning function, and sends accident early warning information to the traffic information board 206, specifically as follows:
when the accident early warning module 103 receives the accident early warning information of the accident detection unit 205, the tunnel traffic accident emergency plan is started, and the severity of the traffic accident is further determined by linking with other devices.
The above description is only for the preferred embodiment of the present invention, and is not intended to limit the present invention in any way, and all simple modifications, equivalent changes and modifications made to the above embodiment according to the technical spirit of the present invention are within the scope of the technical solution of the present invention.
Claims (10)
1. The tunnel vehicle accident detection and early warning device based on RSSI is characterized by comprising a WiFi detection module (101), a remote computing center (102) and an accident early warning module (103);
the WiFi detection module (101) comprises an on-board unit (OBU) (201) installed in a target vehicle and a WiFi detector (202) installed in a tunnel, and receives information sent by the on-board unit (201) in the target vehicle and transmits the information to the remote computing center (102); the remote computing center (102) detects and processes the accident according to the received information and sends the processing result to the accident early warning module (103); and the accident early warning module (103) carries out accident early warning according to the processing result.
2. The RSSI-based tunnel vehicle accident detection and early warning device of claim 1, wherein the on-board unit (201) comprises a storage module (302), a DSRC communication module (301) and a power supply module (303), the WiFi detector (202) comprises a WiFi probe network card (304) and a router (305);
the WiFi probe network card (304) collects detection request frame signal information sent by a DSRC communication module (301) through a DSRC wireless communication technology, receives signal information of a target vehicle, comprises a mac address, RSSI signal strength and a corresponding timestamp of the vehicle-mounted unit (201), and sends the signal information to the remote computing center (102) through a local area network.
3. The RSSI-based tunnel vehicle accident detection and early warning device of claim 2, wherein the power supply module (303) is powered by a solar panel and a lithium battery.
4. The RSSI-based tunnel vehicle accident detection and early warning device of claim 2, wherein the WiFi probe network card (304) and the router (305) adopt a DS-007 detector, and the functions of the WiFi probe network card (304) and the router (305) are integrated.
5. The RSSI-based tunnel vehicle accident detection and early warning device of claim 2, wherein the WiFi probe network card (304) is capable of detecting external WiFi signals and intensity and supporting Ethernet, WiFi and external USB flash disk to transmit data; the router (305) has the function of connecting WiFi internet and supports the function of starting hot spots.
6. The RSSI-based tunnel vehicle accident detection and early warning device of claim 1, wherein the WiFi detectors (202) are installed at both sides of the tunnel at a height of between 1-1.5 m.
7. The RSSI-based tunnel vehicle accident detection and warning device of claim 1, wherein the maximum detection distance of each WiFi detector (202) is 200-300 m in radius.
8. The RSSI-based tunnel vehicle accident detection and early warning device of claim 1, wherein the remote computing center (102) comprises a vehicle locating unit (203), an accident detection unit (205) and a data storage unit (204);
the vehicle positioning unit (203) positions the target vehicle in real time according to the received signal information of the target vehicle; the accident detection unit (205) judges whether an accident occurs according to the real-time positioning data of the target vehicle, and after the accident occurs, the accident detection unit (205) sends a judgment result to the accident early warning module (103) through the Ethernet; a data storage unit (204) stores the position results, calculation results, and determination results of the vehicle positioning unit (203) and the accident detection unit (205).
9. The RSSI-based tunnel vehicle accident detection and early warning device of claim 8, wherein the accident early warning module (103) comprises a traffic information board (206), the traffic information board (206) is connected with the accident detection unit (205) of the remote computing center (102) through Ethernet, and accident early warning information is displayed according to the received judgment result, wherein the accident early warning information comprises the visibility of the front tunnel entrance, the traffic flow in the tunnel, the weather and the auxiliary information of time and date.
10. The RSSI-based tunnel vehicle accident detection and early warning device of claim 9, wherein the accident early warning module (103) transmits the accident early warning information displayed on the traffic information board (206) back to the traffic control command center for recording.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114743378A (en) * | 2022-05-16 | 2022-07-12 | 青岛理工大学 | Method and system for monitoring traffic flow in tunnel |
| CN114999219A (en) * | 2022-06-23 | 2022-09-02 | 重庆城市综合交通枢纽（集团）有限公司 | Underground parking lot vehicle running state sensing system |
| CN115131964A (en) * | 2022-06-23 | 2022-09-30 | 重庆交通大学 | Tunnel traffic flow sensing system |
| CN115346396A (en) * | 2022-06-27 | 2022-11-15 | 浙江大华技术股份有限公司 | Blind area early warning method, device, system, terminal and computer readable storage medium |
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2021
- 2021-05-08 CN CN202120982224.2U patent/CN216110866U/en active Active
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114743378A (en) * | 2022-05-16 | 2022-07-12 | 青岛理工大学 | Method and system for monitoring traffic flow in tunnel |
| CN114999219A (en) * | 2022-06-23 | 2022-09-02 | 重庆城市综合交通枢纽（集团）有限公司 | Underground parking lot vehicle running state sensing system |
| CN115131964A (en) * | 2022-06-23 | 2022-09-30 | 重庆交通大学 | Tunnel traffic flow sensing system |
| CN115131964B (en) * | 2022-06-23 | 2024-02-20 | 重庆交通大学 | Tunnel traffic flow sensing system |
| CN115346396A (en) * | 2022-06-27 | 2022-11-15 | 浙江大华技术股份有限公司 | Blind area early warning method, device, system, terminal and computer readable storage medium |
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