Highway traffic situation perception analysis method based on cloud computing technology

Abstract

The invention relates to the technical field of expressway traffic state analysis, and discloses an expressway traffic situation perception analysis method based on a cloud computing technology. According to the highway traffic situation perception analysis method based on the cloud computing technology, multi-data fusion is carried out on the actual weather, the number of vehicles, the average speed of the vehicles and the time period of congestion of a highway section, the congestion of the highway is scored, a no-pass signal or a no-pass signal is generated according to the congestion score, and the highway traffic situation perception analysis method based on the cloud computing technology is realized. The traffic control department can timely make corresponding countermeasures for the congested road sections according to the received signals, control the entrances of the expressway sections of the corresponding areas, relieve the number of vehicles on the congested road sections and avoid the situation that the vehicles cannot run normally when the vehicles are congested and cannot run normally. And meanwhile, a traffic control department is helped to dredge and dredge a congested road section, and the traffic dredging difficulty of the traffic control department is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of highway traffic status analysis, and in particular to a highway traffic situation perception and analysis method based on cloud computing technology. Background Art

[0002] Highway traffic situation awareness relies on a variety of sensors and technologies, including but not limited to coil vehicle detectors, video cameras, radar equipment, etc. These technologies can capture traffic flow data in real time, such as vehicle speed, traffic volume, vehicle location, etc., to achieve a comprehensive perception of traffic situation, so as to facilitate real-time monitoring of highway road conditions.

[0003] However, at present, the road conditions of highways are mainly judged by video surveillance, and it is impossible to integrate multiple data for comprehensive analysis of highway conditions. In bad weather, it is impossible to timely predict whether there are any abnormalities on the highway surface, which delays the decision-making of the traffic management department. More vehicles are unable to avoid congested sections in time, resulting in more vehicles being stuck on the highway. At the same time, it will increase the length of congested sections, making it difficult to direct traffic. Summary of the invention

[0004] 1. Technical issues to be resolved

[0005] In view of the deficiencies in the prior art, the present invention provides a highway traffic situation perception and analysis method based on cloud computing technology, which has the advantages that the traffic control department can formulate corresponding countermeasures for congested sections in a timely manner according to the received signals, control the entrances to the highway sections in the corresponding areas, alleviate the number of vehicles in the congested sections, and avoid that when congestion occurs and normal driving cannot be carried out, there are still vehicles entering, thereby increasing the congested area. At the same time, it helps the traffic control department to clear and guide the congested sections, reduces the difficulty of the traffic control department in guiding traffic, and solves the above-mentioned problems.

[0006] (II) Technical solution

[0007] To achieve the above object, the present invention provides the following technical solution: a highway traffic situation awareness and analysis method based on cloud computing technology, comprising the following steps:

[0008] S1. Divide the highway into several areas and assign continuous unique digital numbers to each of these areas;

[0009] S2. Obtain road data of each area, including vehicle quantity data and vehicle speed data in the area, obtain vehicle quantity data entering the entrance of each area, and obtain vehicle quantity data staying in the service area of ​​each area;

[0010] S3, calculating the growth rate of the number of vehicles in each area and the average speed of vehicles in each area, and judging whether the corresponding area is congested according to the growth rate of vehicles and the average speed of vehicles;

[0011] S4. When the corresponding area is determined to be a congested section, the weather data and time period data of the area are obtained, and the congestion score is calculated based on the weather data, the number of vehicles entering the corresponding area entrance, the number of vehicles staying in the corresponding area service area, and the time period data;

[0012] S5. After the congestion score is calculated, the congestion score is compared with the congestion score threshold. When the congestion score threshold is exceeded, it means that the highway road surface in the area is seriously congested, and it is necessary to close the highway entrance to vehicles to alleviate the congestion. When it is lower than the congestion score threshold, it means that the highway road surface in the area is congested, but it is passable, and it is necessary to control the number of vehicles entering the highway entrance to alleviate the congestion.

[0013] Preferably, the data on the number of vehicles in the area is represented as Cs, the data on the vehicle driving speed is represented as Sd, and the total number of vehicle driving speed data obtained is the same as the data on the number of vehicles obtained, the data on the number of vehicles entering the entrance is represented as Sr, and the data on the number of vehicles staying in the service area is represented as Ts.

[0014] Preferably, the calculation expression of the growth rate of the number of vehicles in each area is as follows:

[0015]

[0016] In the formula, Cz i , Cs i And qCs i The subscript i represents the unique digital number corresponding to each area, Cz represents the growth rate of the number of vehicles in the area, and qCs i Indicates the number of vehicles in the area obtained this time, the number of vehicles in the area obtained last time, Cs i -qCs i It indicates the difference between the vehicle quantity data in the area obtained this time and the vehicle quantity data in the area obtained last time. The difference is divided by the vehicle quantity data in the area obtained last time to get the growth rate of the vehicle quantity in the area. i When it is a negative value, it means that the number of vehicles in the area is decreasing. i When Cz is positive, it means that the number of vehicles in the area is increasing. i When it is 0, it means that the number of vehicles in the area has not changed.

[0017] Preferably, the calculation expression of the average speed of vehicles in each area is:

[0018]

[0019] In the formula, the subscript i represents the unique digital number corresponding to each area, the superscript 1 to n represents the vehicle speed data corresponding to each vehicle in the area, and the n in the denominator represents that the value of the vehicle quantity data Cs in the area is n.

[0020] Preferably, the method for determining whether the corresponding area is congested is:

[0021] A1. Compare the calculated growth rate of the number of vehicles in each area with the preset threshold value of the number of vehicles growth. When the growth rate of the number of vehicles in a certain area or the growth rate of the number of vehicles in multiple areas exceeds the preset threshold value of the number of vehicles growth, generate a congestion signal 1;

[0022] A2. Compare the calculated average speed of vehicles in each area with the minimum speed limit of the expressway. When the average speed of vehicles in a certain area or the average speed of vehicles in multiple areas is lower than the minimum speed limit of the expressway, generate congestion signal 2;

[0023] A3. When congestion signal 1 and congestion signal 2 are generated at the same time, it is determined that the corresponding area is in a congested state.

[0024] Preferably, the weather data is sunny, cloudy, rainy, snowy or foggy, wherein sunny is represented by Tq 1 , cloudy day is represented by Tq 2 And rain, snow and fog are represented by Tq 3 The corresponding area entrance vehicle entry data is represented by Sy i , the subscript i is the digital number of the corresponding area, and the data of the number of vehicles parked in the service area of ​​the corresponding area is represented by Tl i , the subscript i represents the digital number of the corresponding area, and the time period data includes morning, noon or night, wherein morning is represented by tz, noon is represented by tw, and night is represented by ty.

[0025] Preferably, when the weather data is sunny, the weather data is expressed as Tq 1 , Tq 1 The value is 0.2. When the weather data is cloudy, the weather data is expressed as Tq 2 , Tq 2 The value is 0.2. When the weather data is rainy, snowy or foggy, the weather data is expressed as Tq 3 , Tq 3 The value is 0.8.

[0026] Preferably, when the time period data is morning, the time period data is expressed as tz, and the value of tz is 0.1; when the time period data is noon, the time period data is expressed as tw, and the value of tw is 0.3; when the time period data is night, the time data is expressed as ty, and the value of ty is 0.8.

[0027] Preferably, the congestion score calculation expression is:

[0028] Pf=q 1 *T I +q 2 *Sy i +q 3 *Tl i +q 4 *tr

[0029] In the formula, Tq I Indicates sunny day Tq 1 Or cloudy Tq 2 Or rain, snow, fog, Tq 3 , tr means the time period data is morning tz or afternoon tw or night ty, q 1 ,q 2 ,q 3 and q 4 are weight 1, weight 2, weight 3 and weight 4 respectively, and q 1 +q 2 +q 3 +q 4 =1,q 1 ,q 2 ,q 3 and q 4 is a constant term, and Pf is the congestion score.

[0030] Preferably, when the congestion score exceeds the congestion score threshold, a no-travel signal prohibiting high-speed entrance is generated;

[0031] When the congestion score is lower than the congestion score threshold, a highway entrance restricted access signal is generated.

[0032] Compared with the prior art, the present invention provides a highway traffic situation awareness and analysis method based on cloud computing technology, which has the following beneficial effects:

[0033] The present invention integrates multiple data such as actual weather conditions, number of vehicles, average speed of vehicles, and time period of congestion on a highway section, scores the congestion on the highway, generates a no-travel signal or a restricted-travel signal according to the congestion score, and sends the generated no-travel signal or restricted-travel signal to the traffic control department. The traffic control department can formulate corresponding countermeasures for the congested sections in a timely manner according to the received signals, control the entrances to the highway sections in the corresponding areas, alleviate the number of vehicles on the congested sections, and avoid vehicles entering when normal driving is impossible due to congestion, thereby increasing the congested area. At the same time, it helps the traffic control department to clear and guide the congested sections, and reduces the difficulty of the traffic control department in guiding traffic. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 It is a schematic diagram of the steps of the method of the present invention. DETAILED DESCRIPTION

[0035] 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.

[0036] The actual weather, number of vehicles, average speed of vehicles, and congestion time of the expressway are integrated to score the congestion of the expressway, and corresponding measures are taken according to the score to help the traffic management department better regulate the traffic flow of the expressway and avoid relying on traditional video surveillance to monitor the status of the expressway. For this purpose, a highway traffic situation awareness and analysis method based on cloud computing technology is proposed. Please refer to Figure 1 , the method comprises the following steps:

[0037] S1. Divide the highway surface into several areas, and generate continuous unique digital numbers for each of these areas. The digital numbers can be divided according to the name of the highway section, the number of kilometers of the section, the direction of travel and other data, so that the divided areas have shifted digital numbers. The congested sections can be quickly determined based on these numbers, and the sections adjacent to the congested sections can be selected to intervene in the traffic of the highway.

[0038] S2. Obtain road surface data of each area, which includes vehicle quantity data and vehicle driving speed data in the area, obtain vehicle quantity data entering the entrance of each area, and obtain vehicle quantity data staying in the service area of ​​each area. The vehicle quantity data in the area is represented as Cs, the vehicle driving speed data is represented as Sd, and the total number of vehicle driving speed data obtained is the same as the vehicle quantity data obtained, the vehicle quantity data entering the entrance is represented as Sr, and the vehicle quantity data staying in the service area is represented as Ts. By obtaining the vehicle quantity in the area, vehicle quantity data entering the entrance of each area, vehicle driving speed, and vehicle data staying in the service area of ​​each area, the potential load status of the highway in the area can be timely grasped, so as to analyze according to these data and judge whether the highway is congested.

[0039] S3, calculate the growth rate of the number of vehicles in each area and the average speed of vehicles in each area, and determine whether the corresponding area is congested based on the vehicle growth rate and the vehicle uniform speed.

[0040] The calculation expression for the growth rate of the number of vehicles in each area is as follows:

[0041]

[0042] In the formula, Cz i , Cs i And qCs i The subscript i represents the unique digital number corresponding to each area, Cz represents the growth rate of the number of vehicles in the area, and qCs i Indicates the number of vehicles in the area obtained this time, the number of vehicles in the area obtained last time, Cs i -qCs i It indicates the difference between the vehicle quantity data in the area obtained this time and the vehicle quantity data in the area obtained last time. The difference is divided by the vehicle quantity data in the area obtained last time to get the growth rate of the vehicle quantity in the area. i When it is a negative value, it means that the number of vehicles in the area is decreasing. i When Cz is positive, it means that the number of vehicles in the area is increasing. i When it is 0, it means that the number of vehicles in the area has not changed. For example, when the area is A, the growth rate of the number of vehicles in the area is Cz A .

[0043] The calculation expression of the average speed of vehicles in each area is:

[0044]

[0045] In the formula, the subscript i represents the unique digital number corresponding to each area, the superscripts 1 to n represent the vehicle speed data corresponding to each vehicle in the area, and the denominator n represents the number of vehicles in the area. The value of Cs is n. Similarly, when the area is A, the average speed of vehicles in the area is Ysd A ;

[0046] By calculating the regional vehicle growth rate, we can objectively reflect the state of the increase in traffic volume in each road section within the time interval. At the same time, by calculating the uniform speed of vehicles in each area, we can objectively reflect the speed of vehicles in each area. The faster the speed, the smoother the road in the area. The slower the speed, the more congested the road in the area. Therefore, we can combine these two values ​​to judge whether the road in the corresponding area is congested. The judgment method is as follows:

[0047] 1. Compare the calculated growth rate of the number of vehicles in each area with the preset threshold value of the number of vehicles. When the growth rate of the number of vehicles in a certain area or the growth rate of the number of vehicles in multiple areas exceeds the preset threshold value of the number of vehicles, generate a congestion signal 1;

[0048] 2. Compare the calculated average speed of vehicles in each area with the minimum speed limit of the expressway. When the average speed of vehicles in a certain area or the average speed of vehicles in multiple areas is lower than the minimum speed limit of the expressway, a congestion signal 2 is generated;

[0049] 3. When congestion signal 1 and congestion signal 2 are generated at the same time, it is determined that the corresponding area is in a congested state;

[0050] When only congestion signal 1 appears, it means that there are many vehicles entering the road section, but it does not affect the normal passage of vehicles according to the highway speed limit. When only congestion signal 2 appears, it means that the number of vehicles in the area has not increased, but some vehicles are driving slower due to their own reasons, resulting in a decrease in the average speed of vehicles in the area, but it does not affect the normal passage of vehicles through the area. When these two signals appear at the same time, it means that the number of vehicles in the area has increased and affected the speed of vehicles in the area. This situation can be understood as congestion in the area, which has affected the normal passage of vehicles through the area.

[0051] S4. When the corresponding area is determined to be a congested road section, the weather data and time period data of the area are obtained, and the congestion score is calculated based on the weather data, the number of vehicles entering the corresponding area entrance, the number of vehicles staying in the corresponding area service area, and the time period data. The weather data is sunny, cloudy, rainy, snowy, or foggy, where sunny is represented by Tq 1 , cloudy day is represented by Tq 2 And rain, snow and fog are represented by Tq 3 , the corresponding area entrance vehicle entry data is expressed as Sy i, the subscript i is the number of the corresponding area, and the data on the number of vehicles parked in the service area of ​​the corresponding area is represented by Tl i , the subscript i represents the digital number of the corresponding area, and the time period data includes morning, noon or night, where morning is represented by tz, noon is represented by tw, and night is represented by ty. The congestion score calculation expression is:

[0052] Pf=q 1 *T I +q 2 *Sy i +q 3 *Tl i +q 4 *tr

[0053] In the formula, Tq I Indicates sunny day Tq 1 Or cloudy Tq 2 Or rain, snow, fog, Tq 3 , tr means the time period data is morning tz or afternoon tw or night ty, q 1 ,q 2 ,q 3 and q 4 are weight 1, weight 2, weight 3 and weight 4 respectively, and q 1 +q 2 +q 3 +q 4 =1,q 1 ,q 2 ,q 3 and q 4 is a constant term, Pf is the congestion score, and it should be noted that:

[0054] When the weather data is sunny, the weather data is expressed as Tq 1 , Tq 1 The value is 0.2. When the weather data is cloudy, the weather data is expressed as Tq 2 , Tq 2 The value is 0.2. When the weather data is rainy, snowy or foggy, the weather data is expressed as Tq 3 , Tq 3The value is 0.8. When the time period data is in the morning, the time period data is expressed as tz, and the value of tz is 0.1. When the time period data is at noon, the time period data is expressed as tw, and the value of tw is 0.3. When the time period data is at night, the time data is expressed as ty, and the value of ty is 0.8. Different weather and time periods are set to express the impact of different weather and different time periods on congestion. Usually, rain, snow and fog will have a greater impact on highway traffic. When congestion occurs, this impact is even greater. The time period will also have a greater impact on highway traffic. In the morning and noon, the line of sight is better, and the driver can observe the road conditions ahead in time and respond in time, but at noon, affected by the time The driver is prone to drowsiness, so the midday value is greater than the morning value. At night, the driver's vision is poor and he is prone to drowsiness. Therefore, when the highway is congested, the congestion will be greater at night, including driver drowsiness leading to rear-end collisions in congested sections, and short sleep after waiting for a long time while queuing, thereby increasing the duration of congestion. The number of vehicles parked in the service area and the number of vehicles entering the entrance, as the number of vehicles to be increased in the area, will also cause certain interference to the congestion relief. Therefore, the weather, time, the number of vehicles entering the area entrance and the number of vehicles parked in the service area are combined to score the potential congestion of the section, so as to analyze the potential state of congestion on the highway road surface in the area.

[0055] S5. After the congestion score is calculated, the congestion score is compared with the congestion score threshold. When the congestion score threshold is exceeded, it means that the highway road surface in the area is seriously congested, and it is necessary to close the highway entrance to vehicles to alleviate the congestion. When it is lower than the congestion score threshold, it means that the highway road surface in the area is congested, but it is passable, and it is necessary to control the number of vehicles entering the highway entrance to alleviate the congestion.

[0056] It should be noted that all the data obtained above are sent to the cloud computing platform for aggregation and analysis and calculation one by one, and the cloud computing platform is also interconnected with the monitoring department of the traffic control center. When the congestion score calculated by the cloud computing platform exceeds the congestion score threshold set by the traffic control department, a signal prohibiting high-speed entrance and prohibiting passage is generated; when the congestion score is lower than the congestion score threshold, a signal restricting passage at the high-speed entrance is generated, and the generated prohibition signal or restricted passage signal is sent to the traffic control department. The traffic control department can formulate corresponding countermeasures for the congested sections in a timely manner according to the received signals, control the entrances to the high-speed sections in the corresponding areas, alleviate the number of vehicles in the congested sections, and avoid vehicles entering when congestion occurs and normal driving cannot be carried out, thereby increasing the congested area. At the same time, it helps the traffic control department to clear and guide the congested sections and reduce the difficulty of the traffic control department in guiding traffic.

[0057] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A highway traffic situation awareness and analysis method based on cloud computing technology, characterized by: The following steps are involved: S1. Divide the highway into several areas and assign continuous unique digital numbers to each of these areas; S2. Obtaining road surface data of each area, including vehicle quantity data and vehicle speed data in the area, obtaining vehicle quantity data entering the entrance of each area, and obtaining vehicle quantity data staying in the service area of ​​each area; S3, calculating the growth rate of the number of vehicles in each area and the average speed of vehicles in each area, and judging whether the corresponding area is congested according to the growth rate of vehicles and the average speed of vehicles; S4. When the corresponding area is determined to be a congested section, the weather data and time period data of the area are obtained, and the congestion score is calculated based on the weather data, the number of vehicles entering the corresponding area entrance, the number of vehicles staying in the corresponding area service area, and the time period data; S5. After the congestion score is calculated, the congestion score is compared with the congestion score threshold. When the congestion score threshold is exceeded, it means that the highway road surface in the area is seriously congested, and it is necessary to close the highway entrance to vehicles to alleviate the congestion. When it is lower than the congestion score threshold, it means that the highway road surface in the area is congested, but it is passable, and it is necessary to control the number of vehicles entering the highway entrance to alleviate the congestion.

2. The highway traffic situation awareness and analysis method based on cloud computing technology according to claim 1 is characterized by: The data on the number of vehicles in the area is represented by Cs, the data on the vehicle driving speed is represented by Sd, and the total number of vehicle driving speed data obtained is the same as the obtained data on the number of vehicles, the data on the number of vehicles entering the entrance is represented by Sr, and the data on the number of vehicles staying in the service area is represented by Ts.

3. The highway traffic situation awareness and analysis method based on cloud computing technology according to claim 2 is characterized by: The calculation expression of the growth rate of the number of vehicles in each area is as follows: In the formula, Cz i , Cs i And qCs i The subscript i represents the unique digital number corresponding to each area, Cz represents the growth rate of the number of vehicles in the area, and qCs i Indicates the number of vehicles in the area obtained this time, the number of vehicles in the area obtained last time, Cs i -qCs i It indicates the difference between the vehicle quantity data in the area obtained this time and the vehicle quantity data in the area obtained last time. The difference is divided by the vehicle quantity data in the area obtained last time to get the growth rate of the vehicle quantity in the area. i When it is a negative value, it means that the number of vehicles in the area is decreasing. i When Cz is positive, it means that the number of vehicles in the area is increasing. i When it is 0, it means that the number of vehicles in the area has not changed.

4. The highway traffic situation awareness and analysis method based on cloud computing technology according to claim 3 is characterized by: The calculation expression of the average speed of vehicles in each area is: In the formula, the subscript i represents the unique digital number corresponding to each area, the superscript 1 to n represents the vehicle speed data corresponding to each vehicle in the area, and the n in the denominator represents that the value of the vehicle quantity data Cs in the area is n.

5. The highway traffic situation awareness and analysis method based on cloud computing technology according to claim 4 is characterized by: The method for determining whether the corresponding area is congested is: A1. Compare the calculated growth rate of the number of vehicles in each area with the preset threshold value of the number of vehicles growth. When the growth rate of the number of vehicles in a certain area or the growth rate of the number of vehicles in multiple areas exceeds the preset threshold value of the number of vehicles growth, generate a congestion signal 1; A2. Compare the calculated average speed of vehicles in each area with the minimum speed limit of the expressway. When the average speed of vehicles in a certain area or the average speed of vehicles in multiple areas is lower than the minimum speed limit of the expressway, generate congestion signal 2; A3. When congestion signal 1 and congestion signal 2 are generated at the same time, it is determined that the corresponding area is in a congested state.

6. The highway traffic situation awareness and analysis method based on cloud computing technology according to claim 5 is characterized by: The weather data is sunny, cloudy, rainy, snowy or foggy, where sunny is represented by tq1, cloudy is represented by tq2, and rainy, snowy or foggy is represented by Tq3. The corresponding area entrance vehicle entry data is represented by Sy i , the subscript i is the digital number of the corresponding area, and the data of the number of vehicles parked in the service area of ​​the corresponding area is represented by Tl i , the subscript i represents the digital number of the corresponding area, and the time period data includes morning, noon or night, wherein morning is represented by tz, noon is represented by tw, and night is represented by ty.

7. The highway traffic situation awareness and analysis method based on cloud computing technology according to claim 6 is characterized by: When the weather data is sunny, the weather data is represented by Tq1, and the value of Tq1 is 0.

2. When the weather data is cloudy, the weather data is represented by Tq2, and the value of Tq2 is 0.

2. When the weather data is rainy, snowy or foggy, the weather data is represented by Tq3, and the value of Tq3 is 0.

8.

8. The highway traffic situation awareness and analysis method based on cloud computing technology according to claim 7 is characterized by: When the time period data is morning, the time period data is expressed as tz, and the value of tz is 0.

1. When the time period data is noon, the time period data is expressed as tw, and the value of tw is 0.

3. When the time period data is night, the time data is expressed as ty, and the value of ty is 0.

8.

9. The highway traffic situation awareness and analysis method based on cloud computing technology according to claim 8 is characterized by: The congestion score calculation expression is: <h2 style=";text-align:left;direction:ltr">Pf=q1*Tq<h2 style=";text-align:left;direction:ltr"> I <h2 style=";text-align:left;direction:ltr"> +q2*Sy<h2 style=";text-align:left;direction:ltr"> i <h2 style=";text-align:left;direction:ltr"> +q3*Tl<h2 style=";text-align:left;direction:ltr"> i <h2 style=";text-align:left;direction:ltr"> +q4*tr In the formula, Tq I represents sunny day Tq1 or cloudy day Tq2 or rainy, snowy or foggy day Tq3, tr represents the time period data is morning tz or afternoon tw or night ty, q1, q2, q3 and q 4 are weight one, weight two, weight three and weight four respectively, and q1+q2+q3+q4=1, q1, q2, q3 and q4 are constant terms, and Pf is represented by the congestion score.

10. The highway traffic situation awareness and analysis method based on cloud computing technology according to claim 9 is characterized by: When the congestion score exceeds the congestion score threshold, a no-entry signal is generated to prohibit the high-speed entrance; When the congestion score is lower than the congestion score threshold, a highway entrance restricted access signal is generated.

Images