Intelligent scenic spot traffic optimization system

Abstract

The invention, which belongs to the traffic optimization system field, discloses an intelligent scenic area traffic optimization system comprising an image acquisition module, a sound acquisition module, a data analysis module, an early warning emergency module, a people-vehicle shunting module, a route planning module and a notification module. The image acquisition module is used for acquiring image information of a scenic spot road through a camera and sending the acquired image information to the data analysis module; the sound acquisition module is used for acquiring sound information of a scenic spot road through a sound sensor and sending the acquired sound information to the data analysis module; the data analysis module is used for receiving and analyzing the collected information, outputting an analysis result and sending the analysis result to the early warning emergency module; and the early warning emergency module is used for sending risk early warning of a corresponding level according to the analysis result, and sending corresponding emergency measures to the notification module according to the level of the risk early warning. According to the invention, the visitor flow management can be optimized, and the safety and experience of tourists are ensured.

Description

Technical Field

[0001] The present invention relates to the field of traffic optimization systems, and in particular to a smart scenic spot traffic optimization system. Background Art

[0002] As people's living standards improve, more and more people choose to visit scenic spots to relax their bodies and minds, which leads to extremely congested traffic in popular scenic spots during holidays. In order to ease the traffic pressure in scenic spots, each scenic spot usually optimizes it when it is congested. The scenic spot traffic optimization system is a comprehensive system that aims to intelligently upgrade and optimize the traffic management in the scenic spot through modern information technology and communication technology, so as to improve the efficiency of traffic management, the travel experience of tourists and the overall operation level of the scenic spot.

[0003] When the existing scenic area traffic optimization system is used, it usually simply collects road pedestrian and vehicle flow information, and then uses it to divert traffic on roads with large pedestrian and vehicle flows. However, the flow of people in scenic spots is a double-edged sword for tourist experience and safety management. On the one hand, the bustling scene of people crowding can create a strong tourism atmosphere and increase tourists' sense of participation and fun, especially for some scenic spots with themes of culture, festivals or specific activities. This lively atmosphere is an indispensable part. However, on the other hand, when the flow of people in a scenic area exceeds its carrying capacity, it will bring a series of safety hazards and management problems. First, the crowding situation is likely to lead to accidents such as pushing and trampling between tourists, increasing the risk of injury to tourists. Secondly, too many tourists will also bring huge pressure to the transportation, sanitation, facilities and other aspects of the scenic area, which may lead to traffic congestion, garbage accumulation, damage to facilities and other problems, thereby affecting the tourists' tour experience. To this end, how to balance this contradiction, optimize the flow of people management, and ensure the safety and experience of tourists has become a problem that needs to be solved urgently.

[0004] Therefore, those skilled in the art provide a smart scenic area traffic optimization system to solve the problems raised in the above background technology. Summary of the invention

[0005] The purpose of the present invention is to provide a smart scenic area traffic optimization system that can optimize passenger flow management, ensure the safety and experience of tourists, and solve the problems raised in the above-mentioned background technology.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] A smart scenic area traffic optimization system, including an image acquisition module, a sound acquisition module, a data analysis module, an early warning and emergency module, a pedestrian and vehicle diversion module, a route planning module and a notification module;

[0008] The image acquisition module is used to collect image information of scenic area roads through a camera, and send the collected image information to the data analysis module; the sound acquisition module is used to collect sound information of scenic area roads through a sound sensor, and send the collected sound information to the data analysis module; the data analysis module is used to receive the collected information and analyze it, output the analysis results and send them to the early warning and emergency module; the early warning and emergency module is used to issue risk warnings of corresponding levels according to the analysis results, and send corresponding emergency measures to the notification module according to the level of the risk warning, and package the level of the risk warning together with the analysis results and send them to the pedestrian and vehicle diversion module and the route planning module; the pedestrian and vehicle diversion module is used to formulate a pedestrian and vehicle diversion plan according to the received data, and send the pedestrian and vehicle diversion plan to the notification module and the route planning module; the route planning module is used to formulate a route planning plan according to the received data, and send the route planning plan to the notification module; the notification module is used to notify pedestrians and drivers in the scenic area of ​​the pedestrian and vehicle diversion plan and the route planning plan, and notify the scenic area staff of the emergency measures.

[0009] As a further solution of the present invention: the specific process of the data analysis module analyzing the information collected by the image acquisition module is:

[0010] Mark each road in the scenic area as Ai, i = 1...n, where n is a positive integer;

[0011] Perform image recognition on the image information collected from road Ai, count the number of pedestrians on road Ai and mark them as B, and then count the number of sightseeing vehicles on road Ai and mark them as C;

[0012] Calculate the real-time congestion weight value V = (B + 3 * C) of the current road Ai;

[0013] Compare the real-time congestion weight value V with the preset congestion weight value v. If V>v, plan the road Ai to the first sequence. If V≤v, plan the road Ai to the second sequence.

[0014] The number of roads Ai in the first sequence is counted and marked as D. If D>0, it means that there are congested roads in the current scenic area. If D=0, it means that there are no congested roads in the current scenic area.

[0015] As a further solution of the present invention: the specific process of the data analysis module analyzing the information collected by the sound collection module is:

[0016] Perform speech recognition on the sound information collected from road AI, and then perform natural language processing to filter out the sources of tourists’ dissatisfaction;

[0017] Count the number of dissatisfied sound sources of tourists corresponding to road Ai and mark them as E;

[0018] Sort each road Ai in the first sequence from large to small according to the corresponding E to generate a priority list;

[0019] A priority list is output as a result of the analysis of the sound information.

[0020] As a further solution of the present invention: the data analysis module can perform a comprehensive analysis on the information collected by the image acquisition module and the sound acquisition module to determine whether there is an emergency situation, specifically:

[0021] By performing image recognition on the image information collected from the road Ai, it is determined whether there is a fight on the current road Ai. If so, it means that there is an emergency on the current road Ai. If not, it goes to the next step;

[0022] By performing image recognition on the image information collected from the road Ai, it is determined whether there is a confrontation between the two parties on the current road Ai. If so, it proceeds to the next step. If not, it means that there is no emergency situation on the current road Ai.

[0023] Sound information is collected from the area where the confrontation between the two parties occurs on the road Ai for voice recognition to determine whether there are insulting words. If so, it means that there is an emergency situation on the current road Ai. If not, it means that there is no emergency situation on the current road Ai.

[0024] As a further solution of the present invention: the early warning and emergency response module issues risk warnings and corresponding emergency measures specifically as follows:

[0025] Compare the number D of roads Ai in the first sequence with a preset value d;

[0026] If 0<D≤d, a first-level risk warning is issued, and the corresponding emergency measure is "dispatching at least one staff member to each road Ai in the first sequence to maintain order";

[0027] If d<D≤2*d, a second-level risk warning is issued, and the corresponding emergency measures are "dispatching at least two staff members to each road Ai in the first sequence to maintain order and limit the number of people entering the scenic area";

[0028] If 2*d<D, a third-level risk warning is issued, and the corresponding emergency measures are "dispatching at least three staff members to each road Ai in the first sequence to maintain order and closing the entrance to the scenic area at the same time";

[0029] If an emergency situation exists on the current road Ai, the early warning emergency module sends an emergency measure to the notification module, which is "dispatch at least five staff members to the road Ai where the emergency situation exists to maintain order and evacuate pedestrians on the road Ai at the same time."

[0030] As a further solution of the present invention: the specific process of the pedestrian and vehicle diversion module formulating the pedestrian and vehicle diversion plan is as follows:

[0031] Obtain the current location P1 of the sightseeing vehicle on the road Ai in the first sequence, and obtain the current location p1 of the pedestrian on the road Ai in the first sequence;

[0032] If the risk warning level is level 1, the destination P2 is planned for the sightseeing vehicle, and the straight-line distance between P2 and P1 is 500 meters. At the same time, the destination p2 is planned for the pedestrian, and the straight-line distance between P2 and P1 is 200 meters.

[0033] If the risk warning level is level 2, then P3 and P4 are planned as destinations for sightseeing vehicles, and the straight-line distance between P3 and P4 and P1 is one kilometer. At the same time, P3 and P4 are planned as destinations for pedestrians, and the straight-line distance between P3 and P4 and P1 is three hundred meters.

[0034] If the risk warning level is level three, the destinations P5, P6 and P7 are planned for sightseeing vehicles. The straight-line distance between P5, P6 and P7 and P1 is two kilometers. At the same time, the destinations p5, p6 and p7 are planned for pedestrians. The straight-line distance between p5, p6 and p7 and p1 is four hundred meters.

[0035] As a further solution of the present invention: the specific process of the route planning module formulating the route planning solution is:

[0036] If the risk warning level is level 1, a vehicle driving route from P1 to P2 and a pedestrian driving route from P1 to P2 are generated;

[0037] If the risk warning level is level 2, the vehicle driving routes from P1 to P3 and P4, and the pedestrian driving routes from P1 to P3 and P4 are generated;

[0038] If the risk warning level is level three, vehicle driving routes from P1 to P5, P6 and P7, and pedestrian driving routes from P1 to P5, P6 and P7 are generated.

[0039] As a further solution of the present invention: when generating the vehicle driving routes and pedestrian driving routes, roads in the second sequence are preferably selected.

[0040] As a further solution of the present invention: the notification module includes a scenic area loudspeaker, a scenic area announcement display screen and a background terminal display screen, wherein the scenic area loudspeaker and the scenic area announcement display screen are used to broadcast the pedestrian and vehicle diversion plan and route planning plan to pedestrians and drivers in the scenic area, and the background terminal display screen is used to display the emergency measures corresponding to the current level of risk warning to the scenic area staff.

[0041] Compared with the prior art, the present invention has the following beneficial effects:

[0042] 1. This application first uses image recognition to determine which roads in the scenic area have excessive traffic and pedestrian flow, and then uniformly divides these roads that exceed the standard into the first sequence. Then, through voice recognition and natural language processing, it is determined whether the pedestrians on these roads are dissatisfied with the scenic area or immersed in this lively atmosphere. Then, the roads that are more dissatisfied with the crowded phenomenon are optimized first. This can not only ease the traffic in the scenic area, but also soothe the dissatisfaction of users, improve user experience, and reduce accidents such as pushing and trampling among tourists. In addition, it can adopt different diversion plans according to different levels of risk warnings, and formulate diversion destinations of different distances for pedestrians and sightseeing vehicles on the scenic area roads, effectively alleviating the traffic pressure on the scenic area roads. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 This is a structural block diagram of a smart scenic area traffic optimization system. DETAILED DESCRIPTION

[0044] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0045] As mentioned in the background technology of this application, it has been found that the existing scenic area traffic optimization system usually simply collects road pedestrian and vehicle flow information when in use, and then uses this to divert traffic on roads with large pedestrian and vehicle flows. However, the flow of people in the scenic area is a double-edged sword for tourist experience and safety management. On the one hand, the bustling scene of people crowding can create a strong tourism atmosphere, increase the sense of participation and fun of tourists, especially for some scenic spots with culture, festivals or specific activities as the theme, this lively atmosphere is an indispensable part. However, on the other hand, when the flow of people in the scenic area exceeds its carrying capacity, it will bring a series of safety hazards and management problems. First, the situation of crowding people is easy to lead to accidents such as pushing and trampling between tourists, increasing the risk of tourists being injured. Secondly, too many tourists will also bring huge pressure to the transportation, sanitation, facilities and other aspects of the scenic area, which may cause traffic congestion, garbage accumulation, damage to facilities and other problems, thereby affecting the tourists' tour experience, and there are certain defects.

[0046] In order to solve the above-mentioned defects, the present application discloses a smart scenic spot traffic optimization system, which can optimize the flow of people management and ensure the safety and experience of tourists.

[0047] The following will describe in detail how the solution of the present application solves the above technical problems in conjunction with the accompanying drawings.

[0048] See also Figure 1 In an embodiment of the present invention, a smart scenic area traffic optimization system includes an image acquisition module, a sound acquisition module, a data analysis module, an early warning emergency module, a pedestrian and vehicle diversion module, a route planning module and a notification module; the image acquisition module is used to collect image information of scenic area roads through a camera, and send the collected image information to the data analysis module; the sound acquisition module is used to collect sound information of scenic area roads through a sound sensor, and send the collected sound information to the data analysis module; the data analysis module is used to receive the collected information and analyze it, output the analysis result and send it to the early warning emergency module; the early warning emergency module is used to issue a risk warning of a corresponding level according to the analysis result, and send corresponding emergency measures to the notification module according to the level of the risk warning, and package the level of the risk warning together with the analysis result and send it to the pedestrian and vehicle diversion module and the route planning module; the pedestrian and vehicle diversion module is used to formulate a pedestrian and vehicle diversion plan according to the received data, and send the pedestrian and vehicle diversion plan to the notification module and the route planning module; the route planning module is used to formulate a route planning plan according to the received data, and send the route planning plan to the notification module; the notification module is used to notify pedestrians and drivers in the scenic area of ​​the pedestrian and vehicle diversion plan and the route planning plan, and notify the scenic area staff of the emergency measures. This application first uses image recognition to determine which roads in the scenic area have excessive traffic and pedestrian flow, and then divides these roads that exceed the standard into a first sequence. Subsequently, it uses voice recognition and natural language processing to determine whether the pedestrians on these roads are dissatisfied with the scenic area or immersed in the lively atmosphere. This is then used to optimize those roads where pedestrians are more dissatisfied with the crowded phenomenon. This can not only ease traffic in the scenic area, but also soothe users' dissatisfaction, improve user experience, and reduce accidents such as pushing and trampling among tourists.

[0049] In this embodiment, the specific process of the data analysis module analyzing the information collected by the image acquisition module is as follows: mark each road in the scenic area as Ai, i=1···n, where n is a positive integer; perform image recognition on the image information collected from the road Ai, count the number of pedestrians on the road Ai and mark it as B, and then count the number of sightseeing vehicles on the road Ai and mark it as C; calculate the real-time congestion weight value V=(B+3*C) of the current road Ai; compare the real-time congestion weight value V with the preset congestion weight value v, if V>v, then plan the road Ai to the first sequence, if V≤v, then plan the road Ai to the second sequence; count the number of roads Ai in the first sequence, mark it as D, if D>0, it means that there are congested roads in the current scenic area, if D=0, it means that there are no congested roads in the current scenic area. Image recognition is an existing known conventional technology, which refers to the technology of using computers to process, analyze and understand images to identify targets and objects of various different modes. It is an important field in computer science and a practical application of artificial intelligence.

[0050] In this embodiment, the specific process of the data analysis module analyzing the information collected by the sound collection module is as follows: performing speech recognition on the sound information collected from the road Ai, and then performing natural language processing to filter out the sources of tourists' dissatisfaction; counting the number of tourists' dissatisfaction sources corresponding to the road Ai and marking them as E; sorting each road Ai in the first sequence from large to small according to the corresponding E to generate a priority list; and outputting the priority list as the analysis result of the sound information. Speech recognition is an existing well-known technology, including the following steps: (1) preprocessing, preprocessing the collected speech signal, including noise suppression, endpoint detection, pre-emphasis and other steps to improve the accuracy of the speech recognition system. (2) feature extraction, extracting effective acoustic features from the preprocessed speech signal, such as Mel Frequency Cepstral Coefficients (MFCC), etc. These features will be used in the subsequent recognition process. (3) decoding and recognition, using the trained speech recognition model, converting the extracted acoustic features into text. This process usually involves complex algorithms such as pattern matching and probability statistics. Natural language processing is also a well-known technology, including the following steps: (1) Word segmentation and part-of-speech tagging, which involves segmenting the identified text and tagging the part of speech of each word to facilitate subsequent analysis and understanding. (2) Sentiment analysis, which uses sentiment analysis technology in natural language processing to judge the sentiment tendency of tourists' complaints. This usually involves methods such as matching sentiment dictionaries and predicting sentiment classification models. (3) Semantic understanding, which further understands the specific content of tourists' complaints and identifies key information, such as the object, cause, and degree of the complaint. This may require combining multiple resources such as domain knowledge bases and contextual information.

[0051] In this embodiment, the data analysis module can perform a comprehensive analysis on the information collected by the image acquisition module and the sound acquisition module to determine whether there is an emergency situation, specifically: by performing image recognition on the image information collected from the road Ai, determine whether there is a fight on the current road Ai, if so, it means that there is an emergency situation on the current road Ai, if not, proceed to the next step; by performing image recognition on the image information collected from the road Ai, determine whether there is a confrontation between the two sides on the current road Ai, if so, proceed to the next step, if not, it means that there is no emergency situation on the current road Ai; collect sound information from the area where the confrontation between the two sides occurs on the road Ai for voice recognition to determine whether there are insulting words, if so, it means that there is an emergency situation on the current road Ai, if not, it means that there is no emergency situation on the current road Ai. This setting can quickly determine whether there is a fight or the possibility of a fight on the current road Ai.

[0052] In this embodiment, the early warning and emergency module issues risk warnings and corresponding emergency measures as follows: compare the number D of roads Ai in the first sequence with the preset value d; if 0<D≤d, a first-level risk warning is issued, and the corresponding emergency measures are "dispatching at least one staff member to each road Ai in the first sequence to maintain order"; if d<D≤2*d, a second-level risk warning is issued, and the corresponding emergency measures are "dispatching at least two staff members to each road Ai in the first sequence to maintain order, and limiting the number of people entering the scenic area"; if 2*d<D, a third-level risk warning is issued, and the corresponding emergency measures are "dispatching at least three staff members to each road Ai in the first sequence to maintain order, and closing the entrance to the scenic area"; if the current road Ai has an emergency, the early warning and emergency module sends an emergency measure to the notification module, which is "dispatching at least five staff members to maintain order on the road Ai where the emergency exists, and evacuating pedestrians on the road Ai". This setting ensures that risk warnings of different levels can be handled reasonably.

[0053] In this embodiment, the specific process of the pedestrian-vehicle diversion module formulating the pedestrian-vehicle diversion plan is as follows: obtaining the current location P1 of the sightseeing vehicle on the road Ai in the first sequence, and obtaining the current location p1 of the pedestrian on the road Ai in the first sequence; if the level of the risk warning is level one, the destination P2 is planned for the sightseeing vehicle, and the straight-line distance between P2 and P1 is five hundred meters. At the same time, the destination p2 is planned for the pedestrian, and the straight-line distance between p2 and p1 is two hundred meters; if the level of the risk warning is level two, the destinations P3 and P4 are planned for the sightseeing vehicle, and the straight-line distance between P3 and P4 and P1 is one kilometer. At the same time, the destinations p3 and p4 are planned for the pedestrian, and the straight-line distance between p3 and p4 and p1 is three hundred meters; if the level of the risk warning is level three, the destinations P5, P6 and P7 are planned for the sightseeing vehicle, and the straight-line distance between P5, P6 and P7 and P1 is two kilometers. At the same time, the destinations p5, p6 and p7 are planned for the pedestrian, and the straight-line distance between p5, p6 and p7 and p1 is four hundred meters. This setting can adopt different diversion plans according to different levels of risk warnings, and set diversion destinations at different distances for pedestrians and sightseeing vehicles on scenic roads, effectively alleviating traffic pressure on scenic roads.

[0054] In this embodiment, the specific process of the route planning module formulating the route planning scheme is: if the level of risk warning is level one, the vehicle driving route from P1 to P2 and the pedestrian driving route from p1 to p2 are generated; if the level of risk warning is level two, the vehicle driving route from P1 to P3 and P4 and the pedestrian driving route from p1 to p3 and p4 are generated; if the level of risk warning is level three, the vehicle driving route from P1 to P5, P6 and P7 and the pedestrian driving route from p1 to p5, p6 and p7 are generated.

[0055] In this embodiment, the vehicle driving route and the pedestrian driving route are preferably generated by using the roads in the second sequence. This setting ensures that the vehicle driving route and the pedestrian driving route pass through fewer congested sections.

[0056] In this embodiment, the notification module includes a scenic area loudspeaker, a scenic area announcement display screen and a background terminal display screen. Among them, the scenic area loudspeaker and the scenic area announcement display screen are used to broadcast the pedestrian and vehicle diversion plan and route planning plan to pedestrians and drivers in the scenic area, and the background terminal display screen is used to display the emergency measures corresponding to the current level of risk warning to the scenic area staff.

[0057] The present invention first determines which roads in the scenic area have excessive traffic and pedestrian flow through image recognition, and then uniformly divides these roads that exceed the standard into the first sequence, and then determines whether the pedestrians on these roads are dissatisfied with the scenic area or immersed in this lively atmosphere through voice recognition and natural language processing, and then optimizes those roads that are more dissatisfied with the crowded phenomenon, which can not only ease the traffic in the scenic area, but also soothe the dissatisfaction of users and improve user experience, and reduce accidents such as pushing and trampling among tourists. In addition, it can adopt different diversion plans according to different levels of risk warnings, and formulate diversion destinations of different distances for pedestrians and sightseeing vehicles on the scenic area roads, effectively alleviating the traffic pressure on the scenic area roads.

[0058] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

[0059] What is described above is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A smart scenic area traffic optimization system, characterized in that: It includes image acquisition module, sound acquisition module, data analysis module, early warning and emergency module, pedestrian and vehicle diversion module, route planning module and notification module; The image acquisition module is used to collect image information of the scenic area road through a camera, and send the collected image information to the data analysis module; The sound collection module is used to collect sound information of scenic area roads through sound sensors, and send the collected sound information to the data analysis module; the data analysis module is used to receive and analyze the collected information, output the analysis results and send them to the early warning and emergency module; the early warning and emergency module is used to issue risk warnings of corresponding levels according to the analysis results, and send corresponding emergency measures to the notification module according to the level of risk warnings, and package the level of risk warnings together with the analysis results and send them to the pedestrian and vehicle diversion module and the route planning module; The pedestrian and vehicle diversion module is used to formulate a pedestrian and vehicle diversion plan according to the received data, and send the pedestrian and vehicle diversion plan to the notification module and the route planning module; The route planning module is used to formulate a route planning plan according to the received data and send the route planning plan to the notification module; The notification module is used to notify pedestrians and drivers in the scenic area of ​​the pedestrian and vehicle diversion plan and the route planning plan, and to notify the scenic area staff of the emergency measures.

2. According to claim 1, a smart scenic spot traffic optimization system is characterized in that: The specific process of the data analysis module analyzing the information collected by the image acquisition module is as follows: Mark each road in the scenic area as Ai, i = 1...n, where n is a positive integer; Perform image recognition on the image information collected from road Ai, count the number of pedestrians on road Ai and mark them as B, and then count the number of sightseeing vehicles on road Ai and mark them as C; Calculate the real-time congestion weight value V = (B + 3 * C) of the current road Ai; Compare the real-time congestion weight value V with the preset congestion weight value v. If V>v, plan the road Ai to the first sequence. If V≤v, plan the road Ai to the second sequence. The number of roads Ai in the first sequence is counted and marked as D. If D>0, it means that there are congested roads in the current scenic area. If D=0, it means that there are no congested roads in the current scenic area.

3. A smart scenic area traffic optimization system according to claim 2, characterized in that: The specific process of the data analysis module analyzing the information collected by the sound collection module is as follows: Perform speech recognition on the sound information collected from road AI, and then perform natural language processing to filter out the sources of tourists’ dissatisfaction; Count the number of dissatisfied sound sources of tourists corresponding to road Ai and mark them as E; Sort each road Ai in the first sequence from large to small according to the corresponding E to generate a priority list; A priority list is output as a result of the analysis of the sound information.

4. The intelligent scenic area traffic optimization system according to claim 3 is characterized in that: The data analysis module can perform a comprehensive analysis on the information collected by the image acquisition module and the sound acquisition module to determine whether there is an emergency situation, specifically: By performing image recognition on the image information collected from the road Ai, it is determined whether there is a fight on the current road Ai. If so, it means that there is an emergency on the current road Ai. If not, it goes to the next step; By performing image recognition on the image information collected from the road Ai, it is determined whether there is a confrontation between the two parties on the current road Ai. If so, it proceeds to the next step. If not, it means that there is no emergency situation on the current road Ai. Sound information is collected from the area where the confrontation between the two parties occurs on the road Ai for voice recognition to determine whether there are insulting words. If so, it means that there is an emergency situation on the current road Ai. If not, it means that there is no emergency situation on the current road Ai.

5. The intelligent scenic area traffic optimization system according to claim 4 is characterized in that: The risk warning issued by the early warning emergency module and the corresponding emergency measures are as follows: Compare the number D of roads Ai in the first sequence with a preset value d; If 0<D≤d, a first-level risk warning is issued, and the corresponding emergency measure is "dispatching at least one staff member to each road Ai in the first sequence to maintain order"; If d<D≤2*d, a second-level risk warning is issued, and the corresponding emergency measures are "dispatching at least two staff members to each road Ai in the first sequence to maintain order, and limiting the number of people entering the scenic area"; If 2*d<D, a third-level risk warning is issued, and the corresponding emergency measures are "dispatching at least three staff members to each road Ai in the first sequence to maintain order and closing the entrance to the scenic area at the same time"; If an emergency situation exists on the current road Ai, the early warning emergency module sends an emergency measure to the notification module, which is "dispatch at least five staff members to the road Ai where the emergency situation exists to maintain order, and evacuate pedestrians on the road Ai at the same time." 6. The intelligent scenic area traffic optimization system according to claim 5 is characterized in that: The specific process of the pedestrian and vehicle diversion module formulating the pedestrian and vehicle diversion plan is as follows: Obtain the current location P1 of the sightseeing vehicle on the road Ai in the first sequence, and obtain the current location p1 of the pedestrian on the road Ai in the first sequence; If the risk warning level is level 1, the destination P2 is planned for the sightseeing vehicle, and the straight-line distance between P2 and P1 is 500 meters. At the same time, the destination p2 is planned for the pedestrian, and the straight-line distance between P2 and P1 is 200 meters. If the risk warning level is level 2, then P3 and P4 are planned as destinations for sightseeing vehicles, and the straight-line distance between P3 and P4 and P1 is one kilometer. At the same time, P3 and P4 are planned as destinations for pedestrians, and the straight-line distance between P3 and P4 and P1 is three hundred meters. If the risk warning level is level three, the destinations P5, P6 and P7 are planned for sightseeing vehicles. The straight-line distance between P5, P6 and P7 and P1 is two kilometers. At the same time, the destinations p5, p6 and p7 are planned for pedestrians. The straight-line distance between p5, p6 and p7 and p1 is four hundred meters.

7. The intelligent scenic area traffic optimization system according to claim 6 is characterized in that: The specific process of the route planning module formulating the route planning solution is as follows: If the risk warning level is level 1, a vehicle driving route from P1 to P2 and a pedestrian driving route from P1 to P2 are generated; If the risk warning level is level 2, the vehicle driving routes from P1 to P3 and P4, and the pedestrian driving routes from P1 to P3 and P4 are generated; If the risk warning level is level three, vehicle driving routes from P1 to P5, P6 and P7, and pedestrian driving routes from P1 to P5, P6 and P7 are generated.

8. The intelligent scenic area traffic optimization system according to claim 7 is characterized in that: When generating the vehicle driving route and the pedestrian driving route, the roads in the second sequence are preferably selected.

9. The intelligent scenic area traffic optimization system according to claim 8, characterized in that: The notification module includes a scenic area loudspeaker, a scenic area announcement display screen and a background terminal display screen, wherein the scenic area loudspeaker and the scenic area announcement display screen are used to broadcast pedestrian and vehicle diversion plans and route planning plans to pedestrians and drivers in the scenic area, and the background terminal display screen is used to display emergency measures corresponding to the current level of risk warning to scenic area staff.

Images