Municipal engineering traffic accident emergency treatment method

Abstract

The invention discloses a municipal engineering traffic accident emergency processing method, which collects accident related information in real time through equipment such as a sensor, an automobile data recorder and a traffic camera, and transmits the accident related information to an emergency resource scheduling platform in real time through a wireless network or an Internet of Things platform to ensure rapid and accurate transmission of the information. Therefore, the time delay of manual information confirmation and transmission is greatly reduced; the AI algorithm and the real-time traffic data are utilized, the driving speed and the optimal driving time of the emergency resources are calculated, and the optimal distribution strategy of the emergency resources is further calculated, so that the high efficiency and the reasonability of resource distribution are ensured, and the rescue response time can be remarkably shortened; the emergency resource scheduling platform can perform information sharing and real-time linkage with a plurality of departments such as police, a medical emergency center, a traffic management department and a fire brigade, so that efficient coordination among the departments is ensured, and the problems of response delay and unreasonable resource allocation caused by information asymmetry in a traditional system are avoided.

Description

Technical Field

[0001] The invention relates to the technical field of municipal engineering, and in particular to an emergency treatment method for municipal engineering traffic accidents. Background Art

[0002] In the face of sudden traffic accidents, how to handle accidents quickly and effectively has become a major problem in modern urban traffic management. Traditional emergency response platforms usually rely on manual scheduling and post-event response, which is inefficient. In addition, when faced with variable conditions such as heavy traffic, complex weather, and road congestion, the scheduling and deployment of resources are not accurate enough, resulting in long rescue response times and untimely cleaning of the accident site, which in turn affects the efficiency of traffic and accident handling. Specifically, the current emergency response methods usually have the following shortcomings:

[0003] Slow response speed: The existing system mainly relies on manual scheduling and lacks the support of real-time dynamic data. Time delays may occur during multi-party coordination and information transmission.

[0004] Low resource scheduling efficiency: Rescue resource allocation is usually carried out according to a fixed pattern, lacking real-time analysis of on-site conditions, which can easily lead to unreasonable resource scheduling, such as scheduling resources far away from the accident site or scheduling inappropriate rescue vehicles.

[0005] Insufficient route optimization: Due to the lack of full use of real-time traffic data, rescue vehicles may be affected by traffic congestion, resulting in longer driving time and affecting the overall rescue efficiency.

[0006] Lack of intelligent analysis methods: Traditional systems are unable to use historical data and AI algorithms to optimize rescue strategies, resulting in an inability to effectively reduce rescue time or improve the accuracy of accident handling. Summary of the invention

[0007] The purpose of this section is to summarize some aspects of embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the specification abstract and the invention title of this application to avoid blurring the purpose of this section, the specification abstract and the invention title, and such simplifications or omissions cannot be used to limit the scope of the present invention.

[0008] Therefore, in order to solve the above technical problems, the present invention provides the following technical solutions: a method for emergency handling of traffic accidents in municipal engineering, comprising the following specific steps:

[0009] S1: Automatically collect accident-related information after a traffic accident occurs;

[0010] S2: After the accident information is confirmed, it will be shared with relevant departments immediately to avoid delayed response due to information lag;

[0011] S3: The emergency resource dispatching platform uses real-time traffic data and AI algorithms to calculate the travel speed V of emergency resources. i (t) and the optimal travel time T opt,i ;

[0012] S4: Based on the above calculation data, generate the optimal emergency resource scheduling strategy R opt ;

[0013] S5: Dynamically optimize the route of the rescue vehicle and adjust the route based on real-time traffic conditions;

[0014] S6: The emergency resource dispatch platform monitors the rescue progress and coordinates the actions of multiple departments.

[0015] As a preferred solution of the method for emergency handling of municipal engineering traffic accidents described in the present invention, after a traffic accident occurs, accident-related information such as the accident location, accident severity, weather conditions, traffic flow, etc. are automatically collected through sensors, driving recorders or traffic cameras installed on the road.

[0016] As a preferred solution of the municipal engineering traffic accident emergency handling method described in the present invention, after the accident information is confirmed, the data is instantly shared with multiple relevant departments, including police, medical emergency, traffic management department and fire brigade, through a wireless network or Internet of Things platform after encrypted transmission; information sharing ensures data security through encrypted transmission.

[0017] As a preferred solution of the method for emergency handling of municipal engineering traffic accidents described in the present invention, emergency resources include ambulances, fire trucks, police cars, etc.

[0018] As a preferred solution of the method for emergency handling of municipal engineering traffic accidents described in the present invention, the emergency resource dispatching platform gives priority to selecting the emergency resources that are closest to the accident site and most suitable for handling such accidents.

[0019] As a preferred solution of the municipal engineering traffic accident emergency handling method of the present invention, the emergency resource scheduling platform evaluates the response time of each emergency resource, including the vehicle speed V i (t) and the optimal travel time T of the path opt,i , by integrating the response time of all emergency resources, calculate and output the minimized emergency resource allocation result R opt .

[0020] As a preferred solution of the method for emergency handling of municipal engineering traffic accidents of the present invention, wherein: the driving speed V i (t) Calculated based on dynamic factors such as road conditions, traffic flow, weather conditions, etc. The calculation formula is: Where T(t) is the traffic flow at time t, in vehicles per hour; W(t) is the weather condition, a function that affects the road speed, with a range of [0.5, 1]. The worse the weather, the smaller the value; V max is the maximum speed of emergency resources (in kilometers per hour); γ is the impact coefficient of traffic flow; T max is the maximum traffic flow of the road section; ∈ is a very small positive number, which is used to prevent the formula from having singular values ​​when T(t) is zero; C(t) is the degree of road congestion, which is calculated comprehensively by traffic flow and road conditions, ranging from [0,1], where 0 means no congestion and 1 means severe congestion.

[0021] As a preferred solution of the municipal engineering traffic accident emergency handling method of the present invention, the emergency resource dispatching platform calculates the optimal travel time T of the rescue emergency resources. opt,i , T opt,i The calculation formula is:

[0022]

[0023] As a preferred solution of the method for emergency handling of municipal engineering traffic accidents of the present invention, the emergency resource scheduling strategy is calculated based on minimizing the response time, and the calculation formula is: Among them, the objective function R opt : represents the optimal emergency resource allocation combination among multiple emergency resources, and obtains the best rescue plan by minimizing the overall response time and cost;

[0024] α is the adjustment coefficient, which is used to adjust the impact of the accident severity S(t) on the formula. The value range is [0,1]. The more serious the accident, the larger the value. S(t) is a function of the accident severity, which represents the degree of change of the accident at time t. The exponential function exp(-αS(t))) is used to ensure that the weight of serious accidents is higher in the calculation.

[0025] Traffic flow T(t): represents the traffic flow at time t. When the traffic flow is high, the rescue vehicle's form time increases. function, so that the impact of traffic flow is decreasing, and ∈ is a small positive number, which is used to prevent the formula from having singular values ​​when T(t) is zero;

[0026] Availability of emergency resourcesA i (t): represents the availability coefficient of the i-th type of emergency resource (such as ambulance, fire truck, etc.) at time t; the higher the availability, the higher the priority of this type of emergency resource in allocation; this part is strongly related to the actual availability of emergency resources, ensuring the dynamic and flexible allocation of emergency resources;

[0027] Distance attenuation factor Li (t) γ :L i (t) represents the distance between the accident site and the i-th type of emergency resource at time t, and γ is the adjustment attenuation coefficient, which is used to control the impact of distance on accident rescue; the closer emergency resources are given priority, and the farther the distance, the longer the corresponding time;

[0028] Weight factor β i : represents the importance weight of the i-th type of emergency resources, reflecting the difference in demand for different types of rescue emergency resources in accidents. The weight is determined by factors such as the type and severity of the accident and can be optimized through historical data;

[0029] Integral term: represents the dynamic calculation at different time points in the entire rescue process, integrating the information in time to ensure that the changes in the time dimension are fully considered and cover the continuity of the rescue;

[0030] Summation term: Used to sum the priorities of all types of emergency resources to ensure that the contribution of each type of emergency resource is taken into account.

[0031] As a preferred solution of the method for emergency handling of municipal engineering traffic accidents described in the present invention, the emergency resource dispatching platform gives priority to selecting the rescue emergency resources that are closest to the accident site and most suitable to minimize the response time.

[0032] As a preferred solution of the municipal engineering traffic accident emergency handling method described in the present invention, after the accident handling is completed, data is collected and analyzed, and an accident handling report is generated to optimize future emergency resource scheduling strategies, and deep learning technology is used to improve the accuracy of emergency resource allocation.

[0033] Beneficial effects of the present invention:

[0034] 1. The present invention uses sensors, driving recorders, traffic cameras and other equipment to collect accident-related information in real time, including accident location, accident severity, traffic flow, weather conditions, etc. These data are transmitted to the emergency resource dispatching platform in real time through wireless networks or Internet of Things platforms to ensure the rapid and accurate transmission of information, thereby greatly reducing the time delay of manual information confirmation and transmission.

[0035] 2. The present invention utilizes AI algorithms and real-time traffic data to calculate the driving speed and optimal driving time of emergency resources, and further calculates the optimal allocation strategy for emergency resources. The algorithm not only takes into account traffic flow and road congestion, but also combines multi-dimensional factors such as weather conditions and accident severity, thereby ensuring the efficiency and rationality of resource allocation. Compared with the fixed allocation mode in the prior art, the present invention can significantly shorten the rescue response time, especially in complex and changeable traffic environments.

[0036] 3. By real-time monitoring of traffic conditions, the present invention can dynamically adjust the driving route of rescue vehicles to avoid traffic congestion areas. Compared with traditional static path planning methods, it can optimize the driving route according to real-time conditions and reduce the time it takes for rescue vehicles to arrive at the accident scene.

[0037] 4. The emergency resource dispatching platform of the present invention can share information and conduct real-time linkage with multiple departments such as the police, medical emergency center, traffic management department, fire brigade, etc., to ensure efficient coordination among departments and avoid response delays and unreasonable resource allocation problems caused by information asymmetry in traditional systems. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them:

[0039] Figure 1 It is the overall workflow diagram of the present invention. DETAILED DESCRIPTION

[0040] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0041] 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.

[0042] 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 does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0043] Example 1

[0044] Reference Figure 1 , which is the first embodiment of the present invention, provides a method for emergency handling of traffic accidents in municipal engineering, comprising the following specific steps:

[0045] S1: Automatically collect accident-related information such as accident location, accident severity, weather conditions, traffic flow, etc. through sensors, dashcams or traffic cameras installed on the road;

[0046] S2: After the accident information is confirmed, the data is instantly shared (encrypted transmission) with multiple relevant departments, including the police, medical emergency, traffic management department and fire brigade, through wireless networks or IoT platforms;

[0047] S3: The emergency resource dispatching platform uses real-time traffic data and AI algorithms to calculate the driving speed V of emergency resources (including ambulances, fire trucks, police cars, etc.) i (t) and the optimal travel time T opt,i ; The emergency resource dispatching platform evaluates the response time of each emergency resource, including the vehicle speed V i (t) and the optimal travel time T of the path opt,i .

[0048] Specifically, the driving speed V i (t) Calculated based on dynamic factors such as road conditions, traffic flow, weather conditions, etc. The calculation formula is:

[0049] Where T(t) is the traffic flow at time t, in vehicles / hour;

[0050] W(t) is a function of weather conditions that affects road speed, with a value range of [0.5,1]. The worse the weather, the smaller the value.

[0051] V max is the maximum travel speed of emergency resources (in kilometers per hour);

[0052] γ is the influence coefficient of traffic flow;

[0053] T max is the maximum traffic flow of the road section, which is a small quantity to prevent singular values ​​from appearing when the traffic flow is 0;

[0054] C(t) is the degree of road congestion, which is calculated based on traffic flow and road conditions. Its value range is [0,1], where 0 indicates no congestion and 1 indicates severe congestion.

[0055] Specifically, the emergency resource dispatching platform calculates the optimal travel time T of the rescue emergency resources opt,i , T opt,i The calculation formula is:

[0056] S4: Based on the above calculation data, generate the optimal emergency resource scheduling strategy R opt (Minimized emergency resource allocation results);

[0057] The emergency resource dispatching platform gives priority to the rescue emergency resources that are closest to the accident site and most suitable to minimize the response time. Specifically, the emergency resource dispatching strategy is calculated based on minimizing the response time, and the calculation formula is: Among them, the objective function R opt : represents the optimal emergency resource allocation combination among multiple emergency resources, and obtains the best rescue plan by minimizing the overall response time and cost;

[0058] α is the adjustment coefficient, which is used to adjust the impact of the accident severity S(t) on the formula. The value range is [0,1]. The more serious the accident, the larger the value. S(t) is a function of the accident severity, which represents the degree of change of the accident at time t. The exponential function exp(-αS(t))) is used to ensure that the weight of serious accidents is higher in the calculation.

[0059] Traffic flow T(t): represents the traffic flow at time t. When the traffic flow is high, the rescue vehicle's form time increases. function, so that the impact of traffic flow is decreasing, and ∈ is a small positive number, which is used to prevent the formula from having singular values ​​when T(t) is zero;

[0060] Availability of emergency resourcesA i (t): represents the availability coefficient of the i-th type of emergency resource (such as ambulance, fire truck, etc.) at time t; the higher the availability, the higher the priority of this type of emergency resource in allocation; this part is strongly related to the actual availability of emergency resources, ensuring the dynamic and flexible allocation of emergency resources;

[0061] Distance attenuation factor L i (t) γ :L i (t) represents the distance between the accident site and the i-th type of emergency resource at time t, and γ is the adjustment attenuation coefficient, which is used to control the impact of distance on accident rescue; the closer emergency resources are given priority, and the farther the distance, the longer the corresponding time;

[0062] Weight factor β i : represents the importance weight of the i-th type of emergency resources, reflecting the difference in demand for different types of rescue emergency resources in accidents. The weight is determined by factors such as the type and severity of the accident and can be optimized through historical data;

[0063] Integral term: represents the dynamic calculation at different time points in the entire rescue process, integrating the information in time to ensure that the changes in the time dimension are fully considered and cover the continuity of the rescue;

[0064] Summation term: Used to sum the priorities of all types of emergency resources to ensure that the contribution of each type of emergency resource is taken into account.

[0065] S5: Dynamically optimize the route of the rescue vehicle and adjust the route based on real-time traffic conditions;

[0066] S6: Emergency resource dispatch platform monitors rescue progress and coordinates the actions of multiple departments;

[0067] S7: After the accident is handled, data is collected and analyzed to generate an accident handling report to optimize future emergency resource scheduling strategies and use deep learning technology to improve the accuracy of emergency resource allocation.

[0068] The method for emergency handling of municipal engineering traffic accidents proposed in the present invention can effectively solve many deficiencies in the prior art. Through automated data collection, real-time transmission, the introduction of AI algorithms, and dynamic optimization of the emergency resource scheduling platform, a method for emergency handling of municipal engineering traffic accidents with high intelligence, fast response, and reasonable scheduling is formed, which significantly improves the efficiency and accuracy of emergency handling of traffic accidents.

[0069] Example 2

[0070] This is the second embodiment of the present invention. This embodiment is different from the first embodiment in that in order to verify the superiority of the municipal engineering traffic accident emergency handling method described in the present invention over the prior art, a section of urban main road was selected for testing. This section of road has a large daily traffic volume, congestion occurs from time to time, and traffic accidents occur frequently. The experiment selected different types of traffic accident scenes for comparative testing, including minor scratch accidents and serious multi-vehicle rear-end collision accidents.

[0071] Among them, sensor equipment includes traffic flow sensors, driving recorders, and traffic cameras installed on the road, which are used to obtain real-time data after an accident occurs.

[0072] Wireless network platform: used to share data to the emergency resource dispatch platform after an accident occurs.

[0073] Rescue vehicles: Three types of rescue vehicles were selected, namely police cars, ambulances and fire trucks, and all vehicles were equipped with GPS devices.

[0074] Data collection: After a traffic accident occurs, the specific location of the accident, the severity of the accident, the current road traffic flow, weather conditions, and the number and types of vehicles involved in the accident are collected in real time through traffic flow sensors, driving recorders and other equipment.

[0075] Data transmission and analysis: The collected data is transmitted to the emergency resource dispatching platform in real time through the wireless network platform or the Internet of Things platform. Based on the real-time data, the platform automatically calculates the optimal driving speed V of the rescue vehicle. i (t), optimal travel time T opt,i , and determine the optimal scheduling strategy R for emergency resources opt .

[0076] Algorithm and route optimization: Using AI algorithms and real-time traffic data, the optimal route for rescue vehicles is automatically calculated, and the rescue route is dynamically adjusted based on real-time traffic conditions to reduce rescue time. opt Calculate the optimal emergency resource scheduling strategy and allocate the rescue vehicle closest to the accident site to ensure that rescue resources can reach the accident site in the shortest time possible.

[0077] Real-time monitoring and feedback: During the accident handling process, the dispatch platform monitors the progress of the rescue vehicles in real time and adjusts the rescue route in a timely manner based on the real-time data from the sensors. At the same time, the dispatch system keeps information synchronized with the police, medical emergency center, traffic management department and fire brigade to ensure multi-party cooperation.

[0078] Test data recording and summary: After the test, the system automatically generates an accident handling report and analyzes the efficiency of emergency resource allocation during the accident handling process. The report will be used to optimize future emergency resource allocation strategies and scheduling priority models.

[0079]

[0080]

[0081] From the above table, it can be clearly seen that the present invention has significant advantages in emergency response time. Under the existing technology, the dispatch time of emergency resources is relatively long, resulting in a high response time. However, by using the optimized emergency resource dispatch strategy described in the present invention, combined with factors such as real-time traffic flow, accident severity and path length, the present invention can have significant improvements in shortening the travel time of rescue vehicles, reducing the response time by an average of about 32.3%.

[0082] For example, in the vehicle spontaneous combustion accident of test number 3, the response time of the prior art was 14 minutes, while the present invention reduced it to 8 minutes by optimizing the rescue path in real time, and the optimization ratio reached 42.9%. This is mainly attributed to the fact that the present invention uses real-time traffic data analysis and dynamically adjusts the rescue path, thereby avoiding delays caused by traffic congestion.

[0083] In addition, in the multi-vehicle collision accident of test number 4, due to the high severity of the accident, the response time of the prior art is 35 minutes, while the present invention combines formula R opt , prioritized the most suitable rescue emergency resources and automatically optimized vehicle routes, ultimately shortening the response time to 24 minutes, a reduction of 31.4%.

[0084] In summary, the present invention is significantly superior to the prior art in terms of accuracy and efficiency in emergency resource scheduling. Especially in complex accident scenarios, the present invention can significantly reduce the response time of rescue vehicles and improve the overall efficiency of emergency handling.

[0085] 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 method for emergency handling of traffic accidents in municipal engineering, characterized by: The specific steps include: S1: Automatically collect accident-related information after a traffic accident occurs; S2: After the accident information is confirmed, it will be shared with relevant departments immediately to avoid delayed response due to information lag; S3: The emergency resource dispatching platform uses real-time traffic data and AI algorithms to calculate the travel speed V of emergency resources. i (t) and the optimal travel time T opt,i ; S4: Based on the above calculation data, generate the optimal emergency resource scheduling strategy R opt ; S5: Dynamically optimize the route of the rescue vehicle and adjust the route based on real-time traffic conditions; S6: The emergency resource dispatch platform monitors the rescue progress and coordinates the actions of multiple departments.

2. The method for emergency handling of municipal engineering traffic accidents according to claim 1, characterized in that: After a traffic accident occurs, relevant information including the accident location, accident severity, weather conditions, and traffic flow accidents are automatically collected through sensors, dashcams, or traffic cameras installed on the road.

3. The method for emergency handling of municipal engineering traffic accidents according to claim 2, characterized in that: After the accident information is confirmed, the data is encrypted and transmitted instantly through wireless networks or IoT platforms and shared with multiple relevant departments, including police, medical emergency, traffic management departments and fire departments.

4. The method for emergency handling of municipal engineering traffic accidents as claimed in claim 3, characterized in that: Emergency resources include ambulances, fire trucks, and police cars.

5. The method for emergency handling of municipal engineering traffic accidents according to claim 4, characterized in that: The emergency resource dispatching platform gives priority to the emergency resources that are closest to the accident site and most suitable for handling this type of accident.

6. The method for emergency handling of municipal engineering traffic accidents according to claim 5, characterized in that: The emergency resource dispatching platform evaluates the response time of each emergency resource, including the vehicle speed V i (t) and the optimal travel time T of the path opt,i , by integrating the response time of all emergency resources, calculate and output the minimized emergency resource allocation result R opt .

7. The method for emergency handling of municipal engineering traffic accidents according to claim 6, characterized in that: Travel speed V i The calculation formula of (t) is: Where, T(t): traffic flow at time t; W(t): weather conditions; V max : Maximum speed of emergency resources; γ: Traffic flow influence coefficient; T max : The maximum traffic flow of the road section; C(t): The degree of road congestion; ∈ is a very small positive number, which is used to prevent the formula from having singular values ​​when T(t) is zero.

8. The method for emergency handling of traffic accidents in municipal engineering as claimed in claim 7, characterized in that: The emergency resource dispatching platform calculates the optimal travel time T of rescue emergency resources through the integral formula opt,i , specifically:

9. The method for emergency handling of traffic accidents in municipal engineering as claimed in claim 8, characterized in that: Emergency resource scheduling strategy opt The calculation is based on minimizing the response time, and the calculation formula is: Wherein, α is the adjustment coefficient, which is used to adjust the impact of the accident severity S(t) on the formula. The range is [0,1]. The more serious the accident, the larger the value. S(t) is a function of the accident severity, which represents the degree of change of the accident at time t. The exponential function exp(-αS(t))) is used to ensure that the weight of serious accidents is higher in the calculation. Traffic flow T(t): represents the traffic flow at time t. When the traffic flow is high, the rescue vehicle's form time increases. Function, which makes the impact of traffic flow decreasing; Availability of emergency resourcesA i (t): represents the availability coefficient of the i-th type of emergency resource at time t; the higher the availability, the higher the priority of this type of emergency resource in allocation; this part is strongly related to the actual availability of emergency resources, ensuring the dynamic and flexible allocation of emergency resources; Distance attenuation factor L i (t) γ :L i (t) represents the distance between the accident site and the i-th type of emergency resource at time t, and γ is the adjustment attenuation coefficient, which is used to control the impact of distance on accident rescue; the closer emergency resources are given priority, and the farther the distance, the longer the corresponding time; Weight factor β i : represents the importance weight of the i-th type of emergency resources, reflecting the difference in demand for different types of rescue emergency resources in an accident. The weight is determined by factors related to the type and severity of the accident; Integral term: represents the dynamic calculation at different time points in the entire rescue process, integrating the information in time to ensure that the changes in the time dimension are fully considered and cover the continuity of the rescue; Summation term: Used to sum the priorities of all types of emergency resources to ensure that the contribution of each type of emergency resource is taken into account.

10. The method for emergency handling of municipal engineering traffic accidents according to claim 9, characterized in that: After the accident is handled, the data is collected and analyzed to generate an accident handling report to optimize future emergency resource scheduling strategies and use deep learning technology to improve the accuracy of emergency resource allocation.

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