CN114364105A - 10 KM-level intelligent lighting control system for emergency rescue of ultra-long highway tunnel - Google Patents
10 KM-level intelligent lighting control system for emergency rescue of ultra-long highway tunnel Download PDFInfo
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Abstract
The invention discloses a 10 KM-level intelligent lighting control system for emergency rescue of an ultra-long highway tunnel, which comprises an emergency lighting system for providing emergency rescue lighting for vehicles when a traffic accident occurs in the tunnel, a collecting device for collecting tunnel image information, an identification module for identifying abnormal information, an event judgment module for judging accident information, a section division module for dividing tunnel section information, an instruction generation module for generating a corresponding control instruction and a control module for controlling the emergency lighting system to provide emergency lighting.
Description
Technical Field
The invention relates to the technical field of tunnel lighting, in particular to a 10 KM-level intelligent lighting control system for emergency rescue of super-long highway tunnels.
Background
The ultra-long tunnel has the characteristics of long line, limited space, special environment, high rescue difficulty after accidents, difficult evacuation and the like, and due to the influence of factors such as annual increase of traffic flow, increase of transportation volume of dangerous goods, acceleration of vehicle driving speed and the like, the dangerousness of emergencies such as vehicle faults, traffic accidents and even fire disasters in the tunnel is greatly increased, so that the accident loss and the accident severity are far higher than those of a common road section.
Most of the existing tunnel lighting devices can not adjust light, the operation mode is relatively fixed, the lighting brightness modes of all sections are equivalent, the working mode has potential safety hazards, and the processing mode is single in the face of emergency. And the existing emergency rescue lighting in the tunnel lacks effective guidance for drivers and conductors, rescuers and supervisory personnel, so that the problems of overlong crowd evacuation time, incapability of effectively controlling accidents and difficulty in rescue are caused, and the traffic efficiency is influenced by increasing the time for traffic control.
Disclosure of Invention
In view of the above, the present invention provides a 10 KM-class ultra-long highway tunnel emergency rescue intelligent lighting control system, so as to solve the problems in the prior art that the evacuation time of people is too long after a traffic accident occurs in a tunnel, the accident cannot be effectively controlled, and the rescue is difficult.
In order to achieve the above object, the present invention provides a 10 KM-class intelligent lighting control system for ultra-long highway tunnel emergency rescue, comprising:
the emergency lighting system is used for providing emergency rescue lighting for the vehicle when a traffic accident occurs in the tunnel;
the acquisition device is used for acquiring real-time images of all road sections in the tunnel and splicing the real-time images to form complete image information in the tunnel;
the identification module is used for identifying the running state of the vehicle in the tunnel according to the image information, and extracting the running track of the abnormal vehicle and/or the site traffic condition to form abnormal information when the running state of the vehicle is abnormal;
the event judgment module is used for matching the abnormal information with a preset traffic accident and generating accident information corresponding to the traffic accident when the matching is successful, wherein the accident information comprises a traffic accident type and an accident position;
the section dividing module is used for judging the influence degree of the traffic accident according to the accident information and dividing the tunnel into an accident section, an influence section and a non-influence section based on the influence degree to form tunnel section information;
the instruction generation module is used for respectively generating corresponding emergency instructions, evacuation instructions and holding instructions in the accident zone, the affected zone and the non-affected zone according to the accident information and the tunnel zone information; and
and the control module is used for controlling the emergency lighting system of the accident zone to provide emergency lighting according to a set emergency lighting rule based on the confirmation request and according to the emergency instruction, controlling the emergency lighting system of the affected zone to provide evacuation lighting according to a set evacuation lighting rule according to the evacuation instruction, and controlling the emergency lighting system of the non-affected zone to keep a current lighting state according to the keeping instruction.
Further, the system also comprises an evacuation path generation module;
the evacuation path generation module is used for calculating the shortest distance evacuation path between the non-traffic accident vehicle in the tunnel and the tunnel entrance and exit according to the tunnel section information, the real-time position of each vehicle in the tunnel, the designed entrance and exit position of the tunnel and the position of each transverse passage entrance to form corresponding evacuation path information;
the instruction generating module is further used for generating the evacuation instruction in the influence section according to the evacuation path information;
the control module is also used for controlling emergency lighting systems along the evacuation path to provide evacuation lighting according to set evacuation lighting rules based on the confirmation request and according to the evacuation instructions.
Further, the evacuation path generating module includes:
the position acquisition submodule is used for acquiring the real-time positions of all vehicles in the tunnel, the positions of the entrance and the exit of the tunnel and the positions of all transverse passage openings according to the real-time image information;
the node configuration submodule is used for configuring the entrance and the exit of the tunnel and each transverse passage opening into link nodes according to a construction design drawing of the tunnel, setting the passing direction of each link node and numbering each link node in sequence according to the direction from the tunnel entrance to the transverse passage opening and then to the tunnel exit;
the path linking submodule is used for performing path linking on the real-time position of each vehicle and each link node with the passing direction according to the real-time position of the non-traffic accident vehicle in the tunnel, the tunnel entrance and exit positions and the positions of all transverse passage ports to generate a plurality of feasible paths; and
and the path screening submodule is used for screening the feasible paths with the shortest distance between each vehicle and the tunnel entrance and exit from the feasible paths to form evacuation paths, and further forming evacuation path information of each vehicle.
Further, the collection device comprises:
the cameras are uniformly arranged along the length direction of the tunnel and are used for acquiring real-time images of all road sections in the tunnel, wherein critical areas of effective monitoring ranges of two adjacent cameras are mutually connected or have overlapped parts; and
and the image splicing submodule is used for splicing the real-time images of all road sections in the tunnel to form complete and continuous image information in the tunnel.
Further, the identification module comprises:
the image preprocessing submodule is used for extracting the moving vehicles in the image information by adopting a background difference method and marking the outlines of the moving vehicles to form a tracking target;
the target tracking submodule is used for segmenting image information according to frames to obtain a video frame sequence of a tracking target, respectively tracking each moving vehicle by taking the same tracking target as a unit for each frame image of the video frame sequence, and predicting the position of the next frame of the tracking target by combining a Kalman filtering algorithm;
the abnormal information identification model is used for identifying the movement speed and the movement direction of a moving vehicle in the video frame sequence by taking the video frame sequence as input, judging that the running state of the moving vehicle is abnormal when the movement speed and the movement direction of the moving vehicle are not matched with a preset parameter change threshold value, and outputting a vehicle running abnormal signal;
the abnormal information extraction submodule is used for extracting the running track and/or the site traffic condition of the moving vehicle with abnormal running state in the video frame sequence according to the vehicle running abnormal signal to form the abnormal information; and
and the model training submodule is used for performing iterative training on the abnormal information identification model by taking the acquired historical traffic accident data as a training set until the set loss function tends to be stable or the maximum iteration times is reached, and finishing the training.
Further, the segment dividing module includes:
the tunnel segmentation sub-module is used for segmenting the tunnel into a plurality of sub-tunnel segments according to the position of the transverse channel according to a construction design drawing of the tunnel;
the statistic and calculation submodule is used for extracting the image of each sub-tunnel section from the image information, counting the proportion of all vehicles in each image in the image and calculating the cross section traffic occupancy of each sub-tunnel section;
the comparison submodule is used for comparing the section traffic occupancy with a set first threshold and a set second threshold to obtain the influence degree of each sub-tunnel section when a traffic accident occurs, and the first threshold is smaller than the second threshold; and
and the section determining submodule is used for determining the section category of each sub-tunnel section into an accident section, an influence section and a non-influence section according to the comparison result of the comparison submodule to form the tunnel section information.
Further, the statistic and calculation submodule calculates the section traffic occupancy in each sub-tunnel section by adopting the following formula:
wherein: o isiIs the section traffic occupancy, L, of the ith sub-tunnel segmentiIs the total area occupied by all vehicles in the image of the ith sub-tunnel segment, DiThe total area corresponding to the image of the ith sub-tunnel segment, i ═ 1, 2.
Furthermore, the emergency lighting system comprises emergency lighting lamps which are uniformly arranged on two side walls of the tunnel along the length direction of the tunnel, and the emergency lighting lamps have various illumination colors and flicker frequencies which can be combined to form corresponding lighting rules; the emergency lighting rules are set in one-to-one correspondence with the traffic accident types.
Further, the system also comprises a traffic management server and an alarm module;
the traffic management server is used for realizing data interaction with the control module, storing and displaying the accident information, and generating an emergency triggering signal based on a confirmation request of a manager for the accident information or a system delay automatic confirmation request;
the instruction generating module is also used for generating an alarm instruction according to the emergency trigger signal;
and the alarm module is used for executing corresponding warning according to the alarm instruction.
Further, the control module includes:
the upper computer is used for displaying and storing accident information;
the controller host is used for respectively sending control instructions to each accident zone, each affected zone and each non-affected zone according to the emergency trigger signals and the corresponding emergency instructions, evacuation instructions and holding instructions; and
and the zone control extensions are used for controlling emergency lighting systems in zones of the controller to provide emergency lighting according to set emergency lighting rules, provide evacuation lighting according to set evacuation lighting rules or keep the current lighting state according to control instructions sent by the controller host.
According to the scheme, the acquisition device, the identification module and the event judgment module are arranged, and whether a traffic accident occurs in the tunnel or not can be judged doubly by combining the acquired image information with the preset traffic accident, so that the determination precision of the traffic accident is improved; by arranging the section division module, the tunnel can be divided into accident sections, affected sections and non-affected sections according to the influence degree of the traffic accident on each section of the tunnel after the traffic accident happens, and the emergency lighting systems in the corresponding sections are respectively controlled according to different section types to provide lighting for the tunnel according to set emergency lighting rules and evacuation lighting rules or the original lighting state, so that vehicles and drivers in the tunnel can be rescued and evacuated at the fastest speed, the traffic jam caused by the rescue is reduced, and the accident loss is reduced to the maximum extent.
Drawings
Fig. 1 is a block diagram of a 10 KM-class ultra-long highway tunnel emergency rescue intelligent lighting control system according to the present invention.
Fig. 2 is a block diagram of the acquisition module in fig. 1.
Fig. 3 is a block diagram of the identification module in fig. 1.
Fig. 4 is a block diagram of a structure of a section division module in fig. 1.
Fig. 5 is a control block diagram of the evacuation path generating module of fig. 1.
Fig. 6 is a control block diagram of the control module of fig. 1.
Fig. 7 is a block diagram illustrating an emergency rescue intelligent lighting control system for a 10 KM-class ultra-long highway tunnel according to another embodiment of the present invention.
Detailed Description
The following is further detailed by way of specific embodiments:
examples
Although the emergency rescue intelligent lighting control system of the embodiment is described by taking a 10 KM-grade highway tunnel as an example, the emergency rescue intelligent lighting control system is not limited to be used for emergency rescue lighting of a 10 KM-grade highway tunnel, but also can be used for emergency rescue lighting of other highway tunnels with longer grade or shorter grade, so that when a traffic accident occurs in the tunnel, vehicles and drivers and passengers in the tunnel are guided to evacuate in time, and the influence of the accident is further reduced to the maximum extent.
Fig. 1 is a control block diagram of a smart lighting control system for emergency rescue in a 10 KM-class ultra-long highway tunnel according to the present embodiment. The emergency lighting system comprises an emergency lighting system 1, a collecting device 2, an identification module 3, an event judgment module 4, a section division module 5, an evacuation path generation module 6, an instruction generation module 7 and a control module 8. Wherein:
the emergency lighting system 1 can provide emergency rescue lighting for vehicles when traffic accidents happen in the tunnel; which specifically includes emergency lighting and evacuation lighting in the event of a traffic accident. Emergency lighting system 1 includes along the even emergency lighting lamp that sets up on the wall of tunnel both sides of tunnel length direction, and each emergency lighting lamp all has multiple illumination and scintillation frequency to illumination and the combination of scintillation frequency through different colours form multiple lighting rules, emergency lighting and sparse illumination when realizing the emergence traffic accident in the tunnel.
The acquisition device 2 can acquire real-time images of all road sections in the tunnel, and the acquired real-time images are spliced through an image splicing technology to form complete image information in the whole tunnel in an arranging mode.
Specifically, as shown in fig. 2, the collecting device 2 includes a plurality of cameras 21 and an image splicing submodule 22 that are uniformly arranged on the side wall of the tunnel along the length direction of the tunnel, the cameras 21 can collect real-time images of the tunnel corresponding to the road section, and the critical areas of the effective monitoring ranges of two adjacent cameras 21 are mutually connected or have an overlapping part, so that the collected real-time images of the tunnel have no visual area blind spot, and reach the maximum value, thereby increasing the accuracy of traffic accident judgment. The image stitching submodule 22 may be connected to each camera 21 through a video distributor to receive the real-time images of the corresponding road section in the tunnel collected by each camera 21, and stitch the real-time images to form a complete and continuous seamless panoramic image in the tunnel through an image stitching algorithm, so as to obtain image information in the tunnel and transmit the image information to the identification module 3.
The identification module 3 receives the image information of the image splicing submodule 22, identifies and judges the driving state of the vehicle in the tunnel according to the image information, wherein the driving state comprises a normal driving state and an abnormal driving state, and extracts the driving track and/or the site traffic condition of the abnormal vehicle to form abnormal information when the driving state of the vehicle is judged to be abnormal.
As shown in fig. 3, the recognition module 3 includes a model training sub-module 31, an image preprocessing sub-module 32, a target tracking sub-module 33, an abnormal information recognition model 34, and an abnormal information extraction sub-module 35. In this embodiment, the abnormal information recognition model 34 is implemented based on a neural network, and the abnormal information recognition model 34 may be trained by the model training submodule 31, so that after the training is completed, the abnormal information recognition model 34 may recognize the parameter of the moving vehicle in the image information and determine whether the driving state is abnormal based on the video frame sequence processed by the image preprocessing submodule 32 and the target tracking submodule 33. Wherein:
the model training submodule 31 takes historical traffic accident data acquired in a traffic control department or through a crawling manner as a training set, inputs the training set into the abnormal information identification model 34, extracts corresponding parameters based on forward propagation of the abnormal information identification model 34 (namely, a neural network), reversely inputs the obtained parameters into the abnormal information identification model 34 to perform iterative training until a set loss function tends to be stable or reaches the maximum iteration number, completes training to obtain the trained abnormal information identification model 34, and further uses the abnormal information identification model 34 for identification of moving vehicle parameters in image information and judgment of abnormal driving state.
Specifically, the image preprocessing submodule 32 receives the image information, detects a moving vehicle in the image information by using a background difference method based on a video image processing technology, and enables the moving vehicle in the image information to include only the moving vehicle in a foreground image through adaptive threshold segmentation, morphological denoising, shadow removing and vehicle contour identification after the moving vehicle is detected, and forms a tracking target by using the moving vehicle.
The target tracking submodule 33 receives the image information processed by the image preprocessing submodule 32, and divides the image information by frames to obtain a video frame sequence of the tracked target. In this embodiment, the target tracking sub-module 33 tracks the same target in each frame by using a feature matching method; during specific implementation, a Camshift tracker can be established for each detected moving vehicle (namely, the same tracking target), so that tracking of a plurality of moving vehicles (namely, a plurality of tracking targets) is realized, the position of the next frame of the tracking target is predicted by combining with a Kalman filtering algorithm, and the problem of partial shielding of the vehicles can be solved, so that the complete moving track and the on-site traffic state image of the moving vehicle in the video frame sequence can be obtained.
The abnormal information identification model 34 takes the video frame sequence processed by the target tracking sub-module 33 as input, identifies the motion speed and the motion direction of the moving vehicle in the video frame sequence based on the forward propagation of the neural network, judges that the running state of the moving vehicle is abnormal when the motion speed and the motion direction of the moving vehicle are not matched with a preset parameter change threshold, and outputs a vehicle running abnormal signal. In this embodiment, the preset parameter change threshold may be set according to rules such as speed limit and restriction in the tunnel.
The abnormal information extraction submodule 35 receives the abnormal signal output by the abnormal information identification model 34, extracts the running track and/or the field traffic condition of the moving vehicle with abnormal running state from the video frame sequence to form the abnormal information, so as to be used for automatic judgment of the subsequent traffic accident.
The event determination module 4 receives the abnormal information extracted by the abnormal information extraction submodule 35, matches the abnormal information with a preset traffic accident, and generates accident information corresponding to the traffic accident when the matching is successful, wherein the accident information includes a traffic accident type and an accident position. In this embodiment, the types of traffic accidents in the tunnel at least include i, ii, iii, and iv traffic accidents, the i traffic accidents mainly include fire, the ii traffic accidents mainly include rear-end collision, two-vehicle collision, and the like, the iii traffic accidents mainly include collision of vehicles against the inner wall of the tunnel, and the iv traffic accidents mainly include side-turning of vehicles, and the like. In the concrete implementation, the method can be implemented based on a machine learning algorithm, namely, a neural network model is trained by extracting characteristic values of historical data of the four types of traffic accidents as training samples, when abnormal information is received, the characteristic values of the abnormal information are extracted, and the characteristic values are circularly compared with a set threshold value, so that the judgment of the type and the position of the traffic accidents is realized.
The section dividing module 5 receives the accident information, calculates the section traffic occupancy of each section in the tunnel according to the accident information, judges the influence degree of the traffic accident on each section in the tunnel according to the section traffic occupancy, and divides the tunnel into an accident section, an influence section and a non-influence section based on the influence degree to form tunnel section information.
As shown in fig. 4, the segment dividing module 5 includes a tunnel segmentation sub-module 51, a statistics and calculation sub-module 52, a ratio sub-module 53 and a segment determination sub-module 54. Wherein:
the tunnel segmentation sub-module 51 segments the tunnel into a plurality of sub-tunnel segments according to the positions of the cross passages according to the construction design drawing of the tunnel obtained from the relevant department. In other alternative embodiments, the tunnel may be divided into several sub-tunnel segments according to the installation position of the camera 21 or emergency lighting lamp, or even the installation position of the ventilation opening in the tunnel.
The statistics and calculation submodule 52 extracts an image of each sub-tunnel segment from the image information according to the segmentation condition of the tunnel segmentation submodule 51 on the tunnel, detects and counts the number of vehicles in each image based on a cross-section traffic occupancy determination method of video image processing, approximately represents the area of each vehicle in the image as the total number of all pixels in each sub-tunnel segment, and calculates the cross-section traffic occupancy in each sub-tunnel segment by a statistical pixel accumulation summation method. Specifically, the total area L of all vehicles in the ith sub-tunnel segment in the image of the corresponding sub-tunnel segment is obtained in a mode of average standard summationiComparing the total area occupied by all vehicles in the image of the ith sub-tunnel segment with that of the image of the ith sub-tunnel segmentCalculating the total area to obtain the cross section traffic occupancy O of each sub-tunnel sectioni：
Wherein: o isiIs the section traffic occupancy, L, of the ith sub-tunnel segmentiIs the total area occupied by all vehicles in the image of the ith sub-tunnel segment, DiThe total area corresponding to the image of the ith sub-tunnel segment, i ═ 1, 2.
The comparison submodule 53 receives the section traffic occupancy of each sub-tunnel segment, and compares the section traffic occupancy with a first threshold and a second threshold set to obtain the influence degree of each sub-tunnel segment when a traffic accident occurs.
The section determining submodule 54 determines the section category of each sub-tunnel section as an accident section, an affected section and a non-affected section according to the comparison result of the comparison submodule 53, and forms the tunnel section information. In this embodiment, when the section traffic occupancy is smaller than a first threshold, the sub-tunnel segment is determined as a non-affected zone; when the section traffic occupancy is greater than or equal to a first threshold and smaller than a second threshold, determining the sub-tunnel segment as an influence segment; and when the section traffic occupancy is greater than or equal to a second threshold value, determining the sub-tunnel segment as an accident segment. When the affected zone is determined, according to the accident zone and the driving direction of the current tunnel, all the sections from the rear of the accident zone to the entrance of the tunnel can be determined as affected zones, and all the sections from the front of the corresponding accident zone to the exit of the tunnel can be determined as non-affected zones.
In other alternative embodiments, the segment dividing module 5 may also determine the traffic accident for each road in the tunnel by calculating the average speed of the vehicle in each sub-tunnel segment per unit time according to the accident informationThe degree of influence of the segment. Specifically, the statistical and calculation sub-module 52 may calculate the average speed of the vehicle per unit time of each sub-tunnel segment using the following formula
Wherein:
the centroid positions of the moving vehicle relative to the x axis at the time t and the time t-1 respectively;
the centroid positions of the moving vehicle relative to the y axis at the time t and the time t-1 respectively; and m is the total number of vehicles passing through the ith sub-tunnel segment.
Correspondingly, the ratio pair submodule 53 compares the average speed of the vehicle per unit time of each sub-tunnel segment
And determining the influence degree of the traffic accident in the corresponding sub-tunnel segment according to the mapping relation with the influence grade of the traffic accident, and determining the segment type of each sub-tunnel segment by the segment determining submodule 54 according to the corresponding influence degree.
The evacuation path generating module 6 receives the tunnel section information, determines the accident section and the influence section, obtains the real-time positions of the vehicles in the accident section and the influence section in the tunnel, the designed entrance and exit positions of the tunnel and the positions of the cross gates based on the image information, and calculates the shortest distance evacuation path between the non-traffic accident vehicles in the accident section and the influence section in the tunnel and the entrance and exit of the tunnel to form corresponding evacuation path information.
As shown in fig. 5, the evacuation path generating module 6 includes a location obtaining submodule 61, a node configuring submodule 62, a path linking submodule 63, and a path filtering submodule 64. Wherein:
the position obtaining submodule 61 may obtain real-time positions of each vehicle in the tunnel, tunnel entrance/exit positions, and positions of each cross passage according to the real-time image information, so as to calculate feasible paths and determine evacuation paths subsequently.
The node configuration submodule 62 configures the entrance and exit of the tunnel and each transverse passage port as a link node according to a construction design drawing of the tunnel obtained from a relevant department, sets a passing direction of each link node, and each link node passes in a single direction, and then sequentially numbers each link node according to the direction from the tunnel entrance to the transverse passage port and then to the tunnel exit, thereby forming a link node sequence having a passing direction.
The path linking submodule 63 receives the real-time positions of the non-traffic accident vehicles in the tunnel, the tunnel entrance and exit positions and the positions of all the transverse passage openings, performs path linking on the real-time positions of all the vehicles and all the link nodes with the passing direction (when a traffic accident happens, all the link nodes corresponding to the accident section fail, and should be removed during the path linking), and can generate a plurality of feasible paths leaving the tunnel for all the vehicles.
The path screening submodule 64 receives all the feasible paths, and screens out a feasible path with the shortest distance between each vehicle and the tunnel entrance from the feasible paths as the evacuation path of the vehicle, so as to form the evacuation path information of each vehicle.
The instruction generating module 7 can generate an emergency instruction for correspondingly controlling the emergency lighting lamp in the section in the accident section and a holding instruction for correspondingly controlling the emergency lighting lamp in the section in the non-influence section according to the accident information and the tunnel section information; and generating an evacuation instruction for correspondingly controlling emergency lighting lamps in the zone in the affected zone according to the accident information, the tunnel zone information and the evacuation path information.
The control module 8 may control the emergency lighting system 1 of the accident zone to provide emergency lighting according to the set emergency lighting rule based on the confirmation request and according to the emergency instruction, control the emergency lighting system 1 of the affected zone (i.e. along the generated evacuation path) to provide evacuation lighting according to the set evacuation lighting rule according to the evacuation instruction, and control the emergency lighting system 1 of the non-affected zone to maintain the current lighting state according to the maintenance instruction. In this embodiment, the confirmation request may be sent to the control module 8 by a traffic management server 9, and in a specific implementation, the traffic management server 9 may implement data interaction with the control module 8 in a wireless manner, store and display the accident information, determine, based on the accident information, whether the accident information really occurs, or determine, based on the accident information, whether the system automatically delays to confirm the accident information after a preset time is counted down, and generate an emergency trigger signal based on the confirmation request and send the emergency trigger signal to the control module 8.
As shown in fig. 6, the control module 8 includes an upper computer 81, a controller host 82, and a plurality of segment control extensions 83. In this embodiment, the upper computer 81 performs data transmission with the controller host 82 through an RS485 bus to monitor the entire system, and display and store accident information; the controller host 82 and the segment control extension 83 realize data transmission by using a CAN bus technology. Wherein:
the controller host 82 sends control instructions to each accident zone, affected zone and non-affected zone respectively according to the emergency trigger signal and the corresponding emergency instruction, evacuation instruction and holding instruction, so as to control the corresponding zone control extension 83 to execute corresponding control operation.
The zone control extension 83 controls the emergency lighting systems 1 in its zone to provide emergency lighting according to the set emergency lighting rule, provide evacuation lighting according to the set evacuation lighting rule, or maintain the current lighting state according to the control command sent by the controller host 82.
In the embodiment, the lighting rules (including emergency lighting rules and evacuation lighting rules) are set in one-to-one correspondence with the traffic accident types. Specifically, the method comprises the following steps:
the lighting rule corresponding to the class I traffic accident is as follows:
controlling the emergency illuminating lamps at two sides of the accident section to be bright red, and warning the vehicle and the drivers to be far away from the accident section; controlling the brightness of emergency illuminating lamps at two sides of the influence zone to be green, and flashing in sequence according to evacuation path information and a set evacuation illumination rule to form an optical flow to guide vehicles and drivers to evacuate according to an evacuation path; and controlling the red light and the blue light to alternately flash around the fire-fighting equipment box and the emergency escape passage to induce the drivers and passengers to self-rescue, extinguish fire and escape; the flashing frequency of the emergency illuminating lamp is 3 Hz. Meanwhile, the color of the normal driving illuminating lamp in the tunnel is adjusted to be yellow or other light with strong penetrability.
The lighting rule corresponding to the II-type traffic accidents is as follows:
if the vehicles collide with each other without influencing adjacent lanes, the emergency illuminating lamp of the lane at one side of the accident zone is controlled to be bright red, the emergency illuminating lamp of the lane at the other side of the accident zone is controlled to be bright green, and the emergency illuminating lamps sequentially flash according to evacuation path information and set evacuation illumination rules to form light streams so as to guide the vehicles and drivers to evacuate according to the evacuation paths; if the vehicles collide with each other and affect the adjacent lanes, the emergency illuminating lamps in the accident zone are controlled to be bright red, the emergency illuminating lamps on the two sides of the affected zone are bright green, the emergency illuminating lamps sequentially flash according to evacuation path information and set evacuation illumination rules to form light streams, and the vehicles and drivers are guided to evacuate according to the evacuation paths; and controlling the red light and the blue light to alternately flash around the fire-fighting equipment box and the emergency escape passage to induce the drivers and passengers to self-rescue, extinguish fire and escape; the flashing frequency of the emergency illuminating lamp is 2 Hz. Meanwhile, the color of the normal driving illuminating lamp in the tunnel is adjusted to be yellow or other light with strong penetrability.
The lighting rule corresponding to the III-type traffic accident is as follows:
generally, when a vehicle collides with the side wall to only affect the driving of one lane, the emergency illuminating lamp of the lane at one side, where an accident occurs, is controlled to be bright red, the emergency illuminating lamp of the lane at the other side is controlled to be bright green, and the emergency illuminating lamps sequentially flash according to the evacuation path information and the set evacuation illumination rule to form a light stream, so that the vehicle and the drivers and passengers are guided to evacuate according to the evacuation path. Meanwhile, the color of the normal driving illuminating lamp in the tunnel is adjusted to be yellow or other light with strong penetrability.
The lighting rule corresponding to the IV-type traffic accidents is as follows:
for the side turning of the small vehicle, drivers and passengers can generally self-rescue and recover the correct posture of the vehicle, so that the emergency illuminating lamps are only required to be controlled to be bright green, if the drivers and passengers cannot self-rescue, the emergency illuminating lamps in the accident zone are controlled to be bright red, the emergency illuminating lamps on two sides of the accident zone are influenced to be bright green, the emergency illuminating lamps sequentially flash according to evacuation path information and set evacuation illumination rules to form light streams, and the vehicles and the drivers and passengers are guided to evacuate according to the evacuation paths. Meanwhile, the color of the normal driving illuminating lamp in the tunnel is adjusted to be yellow or other light with strong penetrability.
The emergency lighting lamp of this embodiment can adopt the wisdom light of area control, and has independent address, can combine emergency lighting lamp and collection system 2 as an organic whole, reduces purchasing cost and construction cost to this embodiment adopts the centralized control mode of centralized power supply, sets up the battery in emergency lighting lamp is inside, can real time monitoring emergency lighting lamp's operating condition, reducible emergency lighting lamp's maintenance and operation cost reach energy-concerving and environment-protective purpose.
In the 10 KM-level intelligent lighting control system for emergency rescue of the ultra-long highway tunnel according to the embodiment, the system is set with various types of traffic accidents as references, and when the situation of the running track or the traffic scene of a certain vehicle is detected to be matched with the defined traffic accident type, the situation is automatically judged as the traffic accident of the type; whether a traffic accident occurs in the tunnel is judged doubly through the recognition module 3 and the event judgment module 4, the accuracy of judging the traffic accident in the tunnel can be improved, and then when the traffic accident occurs in the tunnel, an evacuation path is automatically calculated according to divided tunnel section information, the emergency lighting system 1 is controlled to guide vehicles and drivers and passengers to evacuate timely according to different lighting rules, rescue and evacuation can be carried out at the highest speed, traffic jam caused by the traffic jam is reduced, and accident loss is reduced to the maximum extent.
As another embodiment of the present invention, as shown in fig. 7, the embodiment further includes an alarm module 10, which is used for sending an alarm to remind a rescue team or other rescuers when a traffic accident occurs in the tunnel, so as to guide the rescuers to quickly arrive at the scene, thereby improving the rescue efficiency. Specifically, the instruction generating module 7 may further generate an alarm instruction according to the emergency trigger signal; and the alarm module 10 executes corresponding warning according to the alarm instruction so as to prompt rescuers.
The foregoing is merely an example of the present invention and common general knowledge of known specific structures and features of the embodiments is not described herein in any greater detail. It should be noted that, for those skilled in the art, without departing from the structure of the present invention, several changes and modifications can be made, which should also be regarded as the protection scope of the present invention, and these will not affect the effect of the implementation of the present invention and the practicability of the present invention.
Claims (10)
1. The utility model provides a 10KM level super extra long highway tunnel emergency rescue wisdom lighting control system which characterized in that includes:
the emergency lighting system is used for providing emergency rescue lighting for the vehicle when a traffic accident occurs in the tunnel;
the acquisition device is used for acquiring real-time images of all road sections in the tunnel and splicing the real-time images to form complete image information in the tunnel;
the identification module is used for identifying the running state of the vehicle in the tunnel according to the image information, and extracting the running track of the abnormal vehicle and/or the site traffic condition to form abnormal information when the running state of the vehicle is abnormal;
the event judgment module is used for matching the abnormal information with a preset traffic accident and generating accident information corresponding to the traffic accident when the matching is successful, wherein the accident information comprises a traffic accident type and an accident position;
the section dividing module is used for judging the influence degree of the traffic accident according to the accident information and dividing the tunnel into an accident section, an influence section and a non-influence section based on the influence degree to form tunnel section information;
the instruction generation module is used for respectively generating corresponding emergency instructions, evacuation instructions and holding instructions in the accident zone, the affected zone and the non-affected zone according to the accident information and the tunnel zone information; and
and the control module is used for controlling the emergency lighting system of the accident zone to provide emergency lighting according to a set emergency lighting rule based on the confirmation request and according to the emergency instruction, controlling the emergency lighting system of the affected zone to provide evacuation lighting according to a set evacuation lighting rule according to the evacuation instruction, and controlling the emergency lighting system of the non-affected zone to keep a current lighting state according to the keeping instruction.
2. The intelligent 10 KM-class ultra-long highway tunnel emergency rescue lighting control system according to claim 1, further comprising an evacuation path generation module;
the evacuation path generation module is used for calculating the shortest distance evacuation path between the non-traffic accident vehicle in the tunnel and the tunnel entrance and exit according to the tunnel section information, the real-time position of each vehicle in the tunnel, the designed entrance and exit position of the tunnel and the position of each transverse passage entrance to form corresponding evacuation path information;
the instruction generating module is further used for generating the evacuation instruction in the influence section according to the evacuation path information;
the control module is also used for controlling emergency lighting systems along the evacuation path to provide evacuation lighting according to set evacuation lighting rules based on the confirmation request and according to the evacuation instructions.
3. The intelligent 10 KM-class ultra-long highway tunnel emergency rescue lighting control system according to claim 2, wherein the evacuation path generating module comprises:
the position acquisition submodule is used for acquiring the real-time positions of all vehicles in the tunnel, the positions of the entrance and the exit of the tunnel and the positions of all transverse passage openings according to the real-time image information;
the node configuration submodule is used for configuring the entrance and the exit of the tunnel and each transverse passage opening into link nodes according to a construction design drawing of the tunnel, setting the passing direction of each link node and numbering each link node in sequence according to the direction from the tunnel entrance to the transverse passage opening and then to the tunnel exit;
the path linking submodule is used for performing path linking on the real-time position of each vehicle and each link node with the passing direction according to the real-time position of the non-traffic accident vehicle in the tunnel, the tunnel entrance and exit positions and the positions of all transverse passage ports to generate a plurality of feasible paths; and
and the path screening submodule is used for screening the feasible paths with the shortest distance between each vehicle and the tunnel entrance and exit from the feasible paths to form evacuation paths, and further forming evacuation path information of each vehicle.
4. The intelligent 10 KM-class ultra-long highway tunnel emergency rescue lighting control system according to claim 1, wherein the collecting device comprises:
the cameras are uniformly arranged along the length direction of the tunnel and are used for acquiring real-time images of all road sections in the tunnel, wherein critical areas of effective monitoring ranges of two adjacent cameras are mutually connected or have overlapped parts; and
and the image splicing submodule is used for splicing the real-time images of all road sections in the tunnel to form complete and continuous image information in the tunnel.
5. The intelligent 10 KM-class ultra-long highway tunnel emergency rescue lighting control system according to claim 1, wherein the identification module comprises:
the image preprocessing submodule is used for extracting the moving vehicles in the image information by adopting a background difference method and marking the outlines of the moving vehicles to form a tracking target;
the target tracking submodule is used for segmenting image information according to frames to obtain a video frame sequence of a tracking target, respectively tracking each moving vehicle by taking the same tracking target as a unit for each frame image of the video frame sequence, and predicting the position of the next frame of the tracking target by combining a Kalman filtering algorithm;
the abnormal information identification model is used for identifying the movement speed and the movement direction of a moving vehicle in the video frame sequence by taking the video frame sequence as input, judging that the running state of the moving vehicle is abnormal when the movement speed and the movement direction of the moving vehicle are not matched with a preset parameter change threshold value, and outputting a vehicle running abnormal signal;
the abnormal information extraction submodule is used for extracting the running track and/or the site traffic condition of the moving vehicle with abnormal running state in the video frame sequence according to the vehicle running abnormal signal to form the abnormal information; and
and the model training submodule is used for performing iterative training on the abnormal information identification model by taking the acquired historical traffic accident data as a training set until the set loss function tends to be stable or the maximum iteration times is reached, and finishing the training.
6. The intelligent 10 KM-class ultra-long highway tunnel emergency rescue lighting control system according to claim 1, wherein the segment dividing module comprises:
the tunnel segmentation sub-module is used for segmenting the tunnel into a plurality of sub-tunnel segments according to the position of the transverse channel according to a construction design drawing of the tunnel;
the statistic and calculation submodule is used for extracting the image of each sub-tunnel section from the image information, counting the proportion of all vehicles in each image in the image and calculating the cross section traffic occupancy of each sub-tunnel section;
the comparison submodule is used for comparing the section traffic occupancy with a set first threshold and a set second threshold to obtain the influence degree of each sub-tunnel section when a traffic accident occurs, and the first threshold is smaller than the second threshold; and
and the section determining submodule is used for determining the section category of each sub-tunnel section into an accident section, an influence section and a non-influence section according to the comparison result of the comparison submodule to form the tunnel section information.
7. The intelligent 10KM lighting control system for emergency rescue in ultra-long highway tunnel according to claim 6, wherein the statistic and calculation sub-module calculates the cross-sectional traffic occupancy rate in each sub-tunnel segment by using the following formula:
wherein: o isiIs the section traffic occupancy, L, of the ith sub-tunnel segmentiIs the total area occupied by all vehicles in the image of the ith sub-tunnel segment, DiThe total area corresponding to the image of the ith sub-tunnel segment, i ═ 1, 2.
8. The intelligent 10 KM-class ultra-extra-long highway tunnel emergency rescue lighting control system according to claim 1, wherein the emergency lighting system comprises emergency lights uniformly arranged on two side walls of the tunnel along the length direction of the tunnel, and the emergency lights have a plurality of lighting colors and flickering frequencies which can be combined to form corresponding lighting rules; the emergency lighting rules are set in one-to-one correspondence with the traffic accident types.
9. The intelligent 10KM lighting control system for emergency rescue in super-extra-long road tunnel according to claim 1, further comprising a traffic management server and an alarm module;
the traffic management server is used for realizing data interaction with the control module, storing and displaying the accident information, and generating an emergency triggering signal based on a confirmation request of a manager for the accident information or a system delay automatic confirmation request;
the instruction generating module is also used for generating an alarm instruction according to the emergency trigger signal;
and the alarm module is used for executing corresponding warning according to the alarm instruction.
10. The intelligent 10 KM-class ultra-long highway tunnel emergency rescue lighting control system according to claim 9, wherein the control module comprises:
the upper computer is used for displaying and storing accident information;
the controller host is used for respectively sending control instructions to each accident zone, each affected zone and each non-affected zone according to the emergency trigger signals and the corresponding emergency instructions, evacuation instructions and holding instructions; and
and the zone control extensions are used for controlling emergency lighting systems in zones of the controller to provide emergency lighting according to set emergency lighting rules, provide evacuation lighting according to set evacuation lighting rules or keep the current lighting state according to control instructions sent by the controller host.
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