Road traffic incident analysis method based on multi-source data fusion

Abstract

The present invention discloses a road traffic incident analysis method based on multi-source data fusion, which relates to the technical field of road traffic analysis, including collecting road traffic data through multi-source data sensors and pre-processing; analyzing and detecting road traffic incidents through the collected road traffic data and implementing treatment measures; predicting future road traffic conditions, formulating and executing traffic control measures based on the prediction results; managing, displaying and storing data, and implementing data protection measures. The beneficial effects of the present invention are as follows: the present invention detects road traffic incidents by collecting road traffic data, implements treatment measures based on the detection results, and re-collects road traffic data after the road traffic incident is processed to predict future road traffic conditions, determine the intensity of future road control measures, and thus more efficiently formulate road control strategies, improve the accuracy and real-time nature of traffic incident prediction, and greatly improve the response speed and efficiency of traffic management.

Description

Technical Field

[0001] The present invention relates to the technical field of road traffic analysis, in particular to a road traffic incident analysis method based on multi-source data fusion. Background Art

[0002] In the field of road traffic incident analysis methods based on multi-source data fusion, the development of technology has gradually evolved from simple data collection and analysis to complex data fusion, event prediction and real-time response systems. Early research mainly focused on the collection and analysis of single data sources (such as road cameras and induction coils), relying on basic image processing technology and traffic flow monitoring to analyze road conditions. With the development of technology, more types of data sources have been added, including but not limited to vehicle GPS data, social media data, weather information, etc., making the analysis of traffic events more comprehensive and accurate. In addition, the introduction of machine learning and artificial intelligence technologies, especially the application of deep learning algorithms in image recognition and time series prediction, has greatly improved the accuracy of road traffic event detection and prediction. However, despite the continuous advancement of technology, the current traffic event analysis methods still face many challenges. With the sharp increase in the amount of data, the existing methods face tremendous pressure in data preprocessing, storage and real-time analysis, which limits their application in large and complex traffic networks. In addition, they are not intelligent and automated enough in the prediction of traffic events and the formulation and implementation of control measures, which reduces the efficiency and effectiveness of traffic management. Summary of the invention

[0003] In view of the problems existing in the above-mentioned existing road traffic incident analysis method based on multi-source data fusion, the present invention is proposed.

[0004] Therefore, the problem to be solved by the present invention is that the existing methods face tremendous pressure in data preprocessing, storage and real-time analysis, and are not intelligent and automated enough in the prediction of traffic events and the formulation and implementation of control measures, which reduces the efficiency and effectiveness of traffic management.

[0005] To solve the above technical problems, the present invention provides the following technical solutions: a road traffic incident analysis method based on multi-source data fusion, which includes collecting road traffic data through multi-source data sensors and performing preprocessing; detecting road traffic incidents through the collected road traffic data analysis and implementing treatment measures; predicting future road traffic conditions, formulating and executing traffic control measures based on the prediction results; managing, displaying and storing data, and implementing data protection measures.

[0006] As a preferred solution of the road traffic incident analysis method based on multi-source data fusion described in the present invention, the collecting of road traffic data through multi-source data sensors and preprocessing thereof refers to collecting road traffic data through multi-source data sensors, including vehicle type, vehicle speed, vehicle density, road conditions, road signs, weather conditions, traffic light information and road monitoring camera data, cleaning and filtering the data, and converting the data into a unified format.

[0007] As a preferred solution of the road traffic incident analysis method based on multi-source data fusion of the present invention, wherein: the road traffic incident analysis and detection through the collected road traffic data refers to detecting the road traffic incident through the collected and processed road traffic data:

[0008] The road traffic information extraction function is defined as:

[0009] in is the information processing function, is the number of Gaussian distributions, is the weight of the nth Gaussian distribution in the mixture, and , For the k-th type of data collected by the i-th sensor, is the mean of the nth Gaussian distribution, is the variance of the nth Gaussian distribution, is the road traffic information extraction function, The data collected by the i-th sensor is is the weight parameter adjusted according to the data type k, The total number of data types collected by the sensor; define the complex information filtering function as: in is a complex information filtering function, is the jth preprocessed road parameter, for The average value of for The standard deviation of is the hyperbolic tangent function, To adjust the parameters; the comprehensive road traffic incident detection algorithm is:

[0010] in is the road traffic incident detection indicator, is the detection time window, is the average speed of the vehicle at time t, is the weight parameter of the average vehicle speed, is the vehicle density at time t, is the weight parameter of vehicle density, is the weight parameter of the road traffic information extraction function, is the number of road traffic incidents in a specific time period, is the weight parameter of the number of road traffic incidents, is the weight parameter of the complex information filtering function, is the total number of road parameter types, and road traffic incident detection is performed by inputting road data into a road traffic incident detection algorithm.

[0011] As a preferred solution of the road traffic incident analysis method based on multi-source data fusion described in the present invention, the implementation of the processing measures refers to the road traffic incident detection algorithm to detect the road traffic incident and then calculate the road traffic incident detection index and the preset threshold value. and Compare and judge the road traffic conditions, < :

[0012] like < , it means that the road traffic conditions are good and no traffic incidents have occurred. The collection and detection of road traffic data should be maintained, and the multimodal sensors on the road should be regularly maintained and repaired;

[0013] like ≤ < , it means that the road traffic situation is general, but it does not affect normal road traffic. The traffic light interval is adjusted, warning lights and voice reminders are set on sections with heavy traffic and prone to accidents to remind vehicles to drive safely, and traffic control staff are notified to stand by to prevent road traffic incidents;

[0014] like ≥ , it means that the road traffic conditions are bad and a road traffic incident has occurred. The traffic lights are adjusted to restrict traffic on the road section where the traffic incident occurred. The traffic control staff are notified to arrive at the road section where the traffic incident occurred and the collected road traffic data is sent to the staff for review to assist the staff in handling the traffic incident. Warning lights are set up on the road section where the traffic incident occurred. The staff simultaneously guides the traffic vehicles and opens a temporary traffic area until the traffic incident is handled and the road traffic is restored.

[0015] As a preferred solution of the road traffic incident analysis method based on multi-source data fusion described in the present invention, the prediction of future road traffic conditions refers to recollecting road traffic data after the road traffic incident is handled to predict future road traffic conditions: in For future time The predicted value of road traffic conditions, is the road traffic condition value at time t, time point At time t and between, For time point The average vehicle speed, For time point The rate of change of traffic speed, is the adjustment parameter of the traffic speed change rate, is a composite function, is the adjustment parameter of the composite function, For time point The vehicle density, For time point The impact of traffic measures, and To adjust the parameters.

[0016] As a preferred solution of the road traffic incident analysis method based on multi-source data fusion described in the present invention, wherein: the formulation of traffic control measures based on the prediction results and the execution thereof refer to evaluating the intensity of the road traffic control measures after obtaining the road traffic situation prediction results: in From time t to The comprehensive intensity of road traffic control measures during the period, For time point The predicted value of road traffic conditions, is the i-th traffic road section at time point The level of traffic activity, is the weight coefficient of the i-th traffic road section, is the total number of traffic road sections detected, and To adjust the parameters, is the i-th traffic road section at time Vehicle density, is the probability of traffic incidents occurring on the ith traffic road section, and is the adjustment parameter affecting the vehicle density and traffic incident occurrence probability of the i-th traffic road section. Road traffic control measures are formulated and implemented according to the comprehensive intensity of road traffic control measures.

[0017] As a preferred solution of the road traffic incident analysis method based on multi-source data fusion described in the present invention, wherein: the management and display of data refers to the traffic control center summarizing all collected and calculated data, and comprehensively displaying them through a display screen in combination with table and graphic formats. When a road traffic incident is detected, an alarm is automatically activated to notify the staff to pay attention to the road traffic incident, and the road traffic data of the section where the road traffic incident occurred is simultaneously displayed through the display screen to assist the staff in understanding the specific circumstances of the road traffic incident, and allow the staff to actively query the collected road traffic data.

[0018] As a preferred solution of the road traffic incident analysis method based on multi-source data fusion described in the present invention, wherein: the data storage and implementation of data protection measures refer to the traffic control center aggregating and collecting all data and storing the data in the database, setting data security passwords and data permissions, each data permission corresponds to a unique data security password, the database regularly performs integrity checks on the stored data, when the staff accesses the data, the database keeps full monitoring records, and after the access is completed, the access data is tested to generate test records and stored synchronously.

[0019] A computer device comprises: a memory and a processor; the memory stores a computer program, characterized in that: when the processor executes the computer program, the steps of the road traffic incident analysis method based on multi-source data fusion are implemented.

[0020] A computer-readable storage medium having a computer program stored thereon, characterized in that: when the computer program is executed by a processor, the steps of the road traffic incident analysis method based on multi-source data fusion are implemented.

[0021] The beneficial effects of the present invention are as follows: the present invention detects road traffic incidents by collecting road traffic data, implements processing measures based on the detection results, and re-collects road traffic data after the road traffic incidents are processed to predict future road traffic conditions, determine the intensity of future road control measures, and thus more efficiently formulate road control strategies, thereby improving the accuracy and real-time nature of traffic event predictions and greatly improving the response speed and efficiency of traffic management. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0023] Figure 1The figure is a flowchart of a road traffic incident analysis method based on multi-source data fusion.

[0024] Figure 2 This is a structural diagram of the road traffic incident analysis process.

[0025] Figure 3 Schematic diagram of the structure developed for road traffic control measures. DETAILED DESCRIPTION

[0026] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific embodiments of the present invention are described in detail below in conjunction with the accompanying drawings.

[0027] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0028] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor is it a separate or selective embodiment that is mutually exclusive with other embodiments.

[0029] Example 1

[0030] Reference Figure 1~Figure 3 , which is the first embodiment of the present invention, and provides a road traffic incident analysis method based on multi-source data fusion. The road traffic incident analysis method based on multi-source data fusion includes the following steps:

[0031] S1, collect road traffic data through multi-source data sensors and perform pre-processing;

[0032] Specifically, collecting road traffic data through multi-source data sensors and preprocessing it means collecting road traffic data through multi-source data sensors, including vehicle type, vehicle speed, vehicle density, road conditions, road signs, weather conditions, traffic light information, and road monitoring camera data, cleaning and filtering the data, and converting it into a unified format.

[0033] Traffic data collected by multi-source data sensors can provide a comprehensive view of road usage, which is essential for accurately analyzing road traffic conditions and events. Multi-dimensional data collection makes the analysis more comprehensive and can better understand traffic flow patterns and potential safety issues. The preprocessing steps include data cleaning and filtering and format conversion, which are the key to ensuring data quality and the effectiveness of subsequent analysis. Cleaning and filtering can remove erroneous, duplicated or irrelevant data and improve the accuracy of data analysis. Format conversion ensures that data from different sources can be processed uniformly, laying a solid foundation for data fusion and analysis. By fusing different data sources into a unified data model, a more in-depth and comprehensive analysis of traffic conditions can be provided. Data fusion technology enables comprehensive judgment of traffic conditions from multiple angles and levels, improving the ability to identify and respond to complex traffic events.

[0034] S2. Detect road traffic incidents through analysis of collected road traffic data and implement treatment measures;

[0035] Specifically, detecting road traffic incidents by analyzing the collected road traffic data means detecting road traffic incidents by collecting and processing the road traffic data: the road traffic information extraction function is defined as: in is the information processing function, is the number of Gaussian distributions, is the weight of the nth Gaussian distribution in the mixture, and , For the k-th type of data collected by the i-th sensor, is the mean of the nth Gaussian distribution, is the variance of the nth Gaussian distribution, is the road traffic information extraction function, The data collected by the i-th sensor is is the weight parameter adjusted according to the data type k, The total number of data types collected by the sensor; define the complex information filtering function as: in is a complex information filtering function, is the jth preprocessed road parameter, for The average value of for The standard deviation of is the hyperbolic tangent function, To adjust the parameters; the comprehensive road traffic incident detection algorithm is:

[0036] in is the road traffic incident detection indicator, is the detection time window, is the average speed of the vehicle at time t, is the weight parameter of the average vehicle speed, is the vehicle density at time t, is the weight parameter of vehicle density, is the weight parameter of the road traffic information extraction function, is the number of road traffic incidents in a specific time period, is the weight parameter of the number of road traffic incidents, is the weight parameter of the complex information filtering function, is the total number of road parameter types, and road traffic incident detection is performed by inputting road data into a road traffic incident detection algorithm.

[0037] The use of Gaussian mixture model to model road traffic data can more accurately capture the complexity and variability of road traffic status. This method can comprehensively consider multiple factors and improve the accuracy of event detection by allocating weights to different types of traffic data (such as vehicle speed and density). By introducing the hyperbolic tangent function and adjusting parameters, the present invention can effectively identify and filter abnormal information and reduce false alarms. This method is crucial to improving the accuracy and reliability of road traffic event detection. An efficient road traffic event detection algorithm is constructed by integrating road traffic information extraction function and complex information filtering function. This algorithm can not only monitor road traffic conditions in real time, but also accurately predict and identify potential traffic events by analyzing multiple factors such as average vehicle speed and vehicle density. It is of great significance for traffic management departments to formulate effective traffic control measures and early warning systems, and can significantly improve road use efficiency and reduce traffic accidents.

[0038] Further, implementing treatment measures refers to calculating the preset threshold of the road traffic incident detection index after detecting the road traffic incident through the road traffic incident detection algorithm. and Compare and judge the road traffic conditions, < :like < , it means that the road traffic conditions are good and no traffic incidents have occurred. The collection and detection of road traffic data should be maintained, and the multimodal sensors on the road should be regularly maintained and repaired;

[0039] like ≤ < , it means that the road traffic situation is general, but it does not affect normal road traffic. The traffic light interval is adjusted, warning lights and voice reminders are set on sections with heavy traffic and prone to accidents to remind vehicles to drive safely, and traffic control staff are notified to stand by to prevent road traffic incidents;

[0040] like ≥ , it means that the road traffic conditions are bad and a road traffic incident has occurred. The traffic lights are adjusted to restrict traffic on the road section where the traffic incident occurred. The traffic control staff are notified to arrive at the road section where the traffic incident occurred and the collected road traffic data is sent to the staff for review to assist the staff in handling the traffic incident. Warning lights are set up on the road section where the traffic incident occurred. The staff simultaneously guides the traffic vehicles and opens a temporary traffic area until the traffic incident is handled and the road traffic is restored.

[0041] When the road traffic incident detection indicators show that the traffic conditions are good, the continuous monitoring and regular maintenance of the system ensure the continuity and accuracy of traffic data collection. This active monitoring mechanism helps to identify and prevent potential traffic risks in real time and maintain smooth road traffic. In this way, traffic congestion and accidents can be effectively prevented, thereby improving road safety and traffic efficiency. In general traffic conditions, by adjusting the traffic light interval and setting warning measures (such as lights and voice reminders), drivers can be reminded to drive safely and reduce the probability of accidents. In addition, traffic control staff are notified to stand by to quickly respond to any traffic conditions that may escalate. This combination of early warning mechanism and readiness helps to respond to emergencies in a timely manner and alleviate possible traffic congestion. When faced with poor road traffic conditions, measures such as emergency adjustment of traffic lights, setting warning lights and rapid dispatch of traffic control staff can quickly and effectively respond to serious traffic congestion or accidents. This rapid response mechanism not only helps to relieve traffic pressure, but also reduces the impact of accidents on traffic flow, ensures that the accident scene is handled in a timely manner, and finally restores normal road traffic.

[0042] S3. Predict future road traffic conditions, formulate and implement traffic control measures based on the prediction results;

[0043] Specifically, predicting future road traffic conditions means re-collecting road traffic data after a road traffic incident is handled to predict future road traffic conditions: in For future time The predicted value of road traffic conditions, is the road traffic condition value at time t, time point At time t and between, For time point The average vehicle speed, For time point The rate of change of traffic speed, is the adjustment parameter of the traffic speed change rate, is a composite function, is the adjustment parameter of the composite function, For time point The vehicle density, For time point The impact of traffic measures, and To adjust the parameters used to control the vehicle density and the impact of traffic measures.

[0044] After a road traffic incident is handled, recollecting road traffic data is a key step to ensure the accuracy of the prediction model. This process helps capture the immediate changes in road traffic conditions after the incident is handled and provides the latest input data for the prediction of future traffic conditions. By comprehensively considering multiple factors such as the average vehicle speed, the rate of change of traffic speed and its adjustment parameters, and the impact of traffic measures, the road traffic conditions at a specific point in time can be accurately predicted. This prediction capability is of great value to traffic management departments in formulating future traffic control measures and optimizing road use plans. By introducing the adjustment parameters of the rate of change of traffic speed and the adjustment parameters of the composite function, the impact of various factors on the prediction of future traffic conditions can be flexibly balanced. This balance ensures that the prediction results take into account the analysis of historical and real-time data, and fully evaluate the effectiveness of traffic control measures, thereby improving the accuracy and reliability of the prediction.

[0045] Furthermore, traffic control measures are formulated and implemented based on the forecast results. After obtaining the road traffic situation forecast results, the intensity of road traffic control measures is evaluated: in From time t to The comprehensive intensity of road traffic control measures during the period, For time point The predicted value of road traffic conditions, is the i-th traffic road section at time point The level of traffic activity, is the weight coefficient of the ith traffic road section, is the total number of traffic road sections detected, and To adjust the parameters, is the i-th traffic road section at time Vehicle density, is the probability of traffic incidents occurring on the ith traffic road section, and is the adjustment parameter affecting the vehicle density and traffic incident occurrence probability of the ith traffic road section. Road traffic control measures are formulated and implemented according to the comprehensive intensity of road traffic control measures. The intensity of road traffic control measures affects the formulation of specific road traffic control measures, such as adjusting traffic signals, restricting lane switching, speed limits, temporary traffic bans, etc.

[0046] By comprehensively analyzing factors such as predicted traffic conditions, traffic activity levels on each road section, and the probability of traffic incidents, traffic management departments are allowed to evaluate and adjust the comprehensive intensity of traffic control measures. This method makes traffic control decisions more data-driven and improves the accuracy and effectiveness of traffic management. Based on the evaluation results of the comprehensive intensity of traffic control measures, specific traffic control measures can be dynamically formulated and implemented, such as adjusting traffic light cycles, implementing speed limits, or issuing temporary traffic bans. This dynamic adjustment mechanism helps to quickly respond to changes in traffic conditions, reduce traffic congestion and accident rates, and improve road use efficiency. By introducing adjustment parameters, it is possible to balance the impact of predicted traffic conditions and actual traffic activity levels, ensuring the rationality and adaptability of traffic control measures. This balancing strategy helps to achieve refined management of traffic control measures, avoid excessive or insufficient traffic control, and thus optimize traffic fluidity and safety.

[0047] S4. Manage, display and store data, and implement data protection measures.

[0048] Specifically, managing and displaying data means that the traffic control center summarizes all collected and calculated data, and displays them comprehensively through a display screen in table and graphic format. When a road traffic incident is detected, an alarm is automatically activated to notify staff to pay attention to the road traffic incident. At the same time, the road traffic data of the section where the road traffic incident occurred is displayed through the display screen to assist staff in understanding the specific circumstances of the road traffic incident, and allow staff to actively query the collected road traffic data.

[0049] By displaying traffic data in the form of graphics and tables on the display screen, the present invention enables the staff of the traffic control center to quickly and intuitively obtain real-time information on road traffic. The intuitive display of such information helps to improve the speed and accuracy of decision-making, which is particularly important during peak hours and emergency situations. When the system detects a road traffic incident, the automatically activated alarm notification mechanism can immediately remind the staff to ensure that they can pay attention to and handle the traffic incident in a timely manner. This automated alarm system greatly reduces reaction time and improves the efficiency and responsiveness of traffic management.

[0050] Furthermore, storing data and implementing data protection measures means that the traffic control center aggregates and collects all data and stores the data in the database, sets data security passwords and data permissions, and each data permission corresponds to a unique data security password. The database regularly performs integrity checks on stored data. When staff access the data, the database keeps full monitoring records, and after the access is completed, the access data is tested to generate test records and store them synchronously.

[0051] By storing all collected data in a database and setting a data security password, the present invention significantly improves data security. This approach ensures that only authorized users with the correct password can access specific data, effectively preventing unauthorized access and leakage of data. The implementation of data authority management ensures the correct and safe use of data. By assigning specific data access rights to different users or user groups, it is possible to accurately control who can access, modify or delete data, thereby protecting sensitive information from abuse or leakage. Regular integrity testing of data in the database helps to promptly discover and correct any illegal modification, damage or deletion. This measure ensures the accuracy and integrity of the data and provides reliable data support for traffic management and decision-making. Example

[0052] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc., which can store program codes.

[0053] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0054] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0055] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit with a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit with a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0056] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A road traffic incident analysis method based on multi-source data fusion, characterized by: include, Collect road traffic data through multi-source data sensors and perform pre-processing; Detect road traffic incidents through analysis of collected road traffic data and implement treatment measures; Predict future road traffic conditions, formulate and implement traffic control measures based on the prediction results; Manage, display and store data, and implement data protection measures; The collecting of road traffic data through multi-source data sensors and pre-processing thereof refers to collecting road traffic data through multi-source data sensors, including vehicle type, vehicle speed, vehicle density, road surface conditions, road signs, weather conditions, traffic light information, and road monitoring camera data, cleaning and filtering the data, and converting the data into a unified format; The detection of road traffic incidents by analyzing the collected road traffic data refers to detecting road traffic incidents by collecting and processing the road traffic data: The road traffic information extraction function is defined as: in is the information processing function, is the number of Gaussian distributions, is the weight of the nth Gaussian distribution in the mixture, and , For the k-th type of data collected by the i-th sensor, is the mean of the nth Gaussian distribution, is the variance of the nth Gaussian distribution, is the road traffic information extraction function, The data collected by the i-th sensor is is the weight parameter adjusted according to the data type k, The total number of data types collected for the sensor; Define the complex information filtering function as: in is a complex information filtering function, is the jth preprocessed road parameter, for The average value of for The standard deviation of is the hyperbolic tangent function, To adjust the parameters; The comprehensive road traffic incident detection algorithm is: in is the road traffic incident detection indicator, is the detection time window, is the average speed of the vehicle at time t, is the weight parameter of the average vehicle speed, is the vehicle density at time t, is the weight parameter of vehicle density, is the weight parameter of the road traffic information extraction function, is the number of road traffic incidents in a specific time period, is the weight parameter of the number of road traffic incidents, is the weight parameter of the complex information filtering function, is the total number of road parameter types, and road traffic incident detection is performed by inputting road data into a road traffic incident detection algorithm; The implementation of the processing measures refers to the road traffic incident detection algorithm to detect the road traffic incident and then calculate the road traffic incident detection index and the preset threshold and Compare and judge the road traffic conditions, < : like < , it means that the road traffic conditions are good and no traffic incidents have occurred. The collection and detection of road traffic data should be maintained, and the multimodal sensors on the road should be regularly maintained and repaired; like ≤ < , it means that the road traffic situation is general, but it does not affect normal road traffic. The traffic light interval is adjusted, warning lights and voice reminders are set on sections with heavy traffic and prone to accidents to remind vehicles to drive safely, and traffic control staff are notified to stand by to prevent road traffic incidents; like ≥ , it means that the road traffic situation is bad and a road traffic incident has occurred. The traffic lights are adjusted to restrict the traffic on the road section where the traffic incident occurred. The traffic control staff are notified to arrive at the road section where the traffic incident occurred and the collected road traffic data is sent to the staff for review to assist the staff in handling the traffic incident. Warning lights are set on the road section where the traffic incident occurred. The staff will simultaneously guide the traffic vehicles and open a temporary traffic area until the traffic incident is handled and the road traffic is restored; The prediction of future road traffic conditions refers to recollecting road traffic data after the road traffic incident is handled to predict future road traffic conditions: in For future time points The predicted value of road traffic conditions, is the road traffic condition value at time t, time point At time t and between, For time point The average vehicle speed, For time point The rate of change of traffic speed, is the adjustment parameter of the traffic speed change rate, is a composite function, is the adjustment parameter of the composite function, For time point The vehicle density, For time point The impact of traffic measures, and To adjust the parameters.

2. The road traffic incident analysis method based on multi-source data fusion according to claim 1, characterized in that: The formulation and implementation of traffic control measures based on the prediction results refers to evaluating the intensity of road traffic control measures after obtaining the road traffic situation prediction results: in From time t to The comprehensive intensity of road traffic control measures during the period, For time point The predicted value of road traffic conditions, is the i-th traffic road section at time point The level of traffic activity, is the weight coefficient of the ith traffic road section, is the total number of traffic road sections detected, and To adjust the parameters, is the i-th traffic road section at time Vehicle density, is the probability of traffic incidents occurring on the ith traffic road section, and is the adjustment parameter affecting the vehicle density and traffic incident occurrence probability of the i-th traffic road section. Road traffic control measures are formulated and implemented according to the comprehensive intensity of road traffic control measures.

3. The road traffic incident analysis method based on multi-source data fusion as claimed in claim 2, characterized in that: The management and display of data refers to the traffic control center summarizing all collected and calculated data, and displaying them comprehensively through a display screen in a table and graphic format. When a road traffic incident is detected, an alarm is automatically activated to notify staff to pay attention to the road traffic incident. At the same time, the road traffic data of the section where the road traffic incident occurred is displayed through the display screen to assist staff in understanding the specific circumstances of the road traffic incident, and allow staff to actively query the collected road traffic data.

4. The road traffic incident analysis method based on multi-source data fusion as claimed in claim 3, characterized in that: The said data storage and implementation of data protection measures means that the traffic control center aggregates and collects all data and stores the data in a database, sets data security passwords and data permissions, each data permission corresponds to a unique data security password, and the database regularly performs integrity checks on the stored data. When staff access the data, the database keeps full monitoring records, and after the access is completed, the access data is tested to generate test records and store them synchronously.

5. A computer device comprising: Memory and processor; The memory stores a computer program, wherein the processor implements the steps of the method according to any one of claims 1 to 4 when executing the computer program.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 4 are implemented.

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