CN108122408B - Road condition monitoring method and device and system for monitoring road conditions - Google Patents

Road condition monitoring method and device and system for monitoring road conditions Download PDF

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CN108122408B
CN108122408B CN201611066966.0A CN201611066966A CN108122408B CN 108122408 B CN108122408 B CN 108122408B CN 201611066966 A CN201611066966 A CN 201611066966A CN 108122408 B CN108122408 B CN 108122408B
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passing time
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CN108122408A (en
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樊婷婷
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China Telecom Corp Ltd
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    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/01—Detecting movement of traffic to be counted or controlled
    • G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
    • G08G1/0125—Traffic data processing
    • G08G1/0133—Traffic data processing for classifying traffic situation
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/01—Detecting movement of traffic to be counted or controlled
    • G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
    • G08G1/0137—Measuring and analyzing of parameters relative to traffic conditions for specific applications
    • G08G1/0141—Measuring and analyzing of parameters relative to traffic conditions for specific applications for traffic information dissemination

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Abstract

The invention discloses a road condition monitoring method, a road condition monitoring device and a system for monitoring road conditions, and relates to the technical field of Internet of things, wherein the method comprises the following steps: acquiring the passing time of a vehicle passing through a traffic intersection; determining section attributes corresponding to a current passing road section where the vehicle is located, and acquiring passing duration experience thresholds corresponding to the section attributes; and comparing the passage time with the passage time experience threshold, and determining the current congestion state of the traffic intersection based on the comparison result. According to the method, the device and the system, the passing time experience threshold corresponding to the attribute of the current section is obtained to be used as the judgment basis of the road condition, so that the influence of factors such as time and weather can be reduced, and the judgment is more accurate; the experience threshold of the passage time can be corrected at regular time, the method can adapt to irregular changes of road conditions, weather and other factors, the receiving sensitivity is improved by adopting the LoRa technology, and data of a plurality of nodes can be received and processed in parallel.

Description

Road condition monitoring method and device and system for monitoring road conditions
Technical Field
The invention relates to the technical field of internet of things, in particular to a road condition monitoring method and device and a system for monitoring road conditions.
Background
With the rapid growth of vehicle reserves, congestion has become an important social problem. In the current traffic management system, most intersections carry out traffic guidance through traffic light systems, most traffic lights are controlled through preset programs, and the mismatch between traffic light passing modes and passing time designs and actual road conditions becomes one of important reasons of traffic jam. The existing traffic light control system can not immediately analyze the real-time traffic passing conditions of the crossing and rapidly adjust the passing mode or the passing time of the traffic light to different directions, thereby striving to command traffic in an optimal traffic light command mode at all the crossings and reducing the possibility of traffic jam caused by unreasonable traffic light command mode. With the development of the internet of things, the application of the internet of things in the traffic industry is more and more extensive, the system for monitoring the road condition can complete the work of judging the congestion condition of the road condition, providing reference for traffic management, providing prompt information for passing vehicles and the like, but in the aspect of judging the road condition of an intersection or a special section, the existing system for monitoring the road condition only judges according to the experience value of fixed driving time, and the judgment accuracy is not high.
Disclosure of Invention
In view of the above, one technical problem to be solved by the present invention is to provide a road condition monitoring method, a road condition monitoring device and a system for monitoring road conditions.
According to an aspect of the present invention, there is provided a road condition monitoring method, including: acquiring the passing time of a vehicle passing through a traffic intersection; determining section attributes corresponding to a current passing road section where the vehicle is located, and acquiring passing duration experience thresholds corresponding to the section attributes; and comparing the passage time with the experience threshold of the passage time, and determining the current congestion state of the traffic intersection based on the comparison result.
Optionally, the determining a section attribute corresponding to a current passing road section where the vehicle is located and acquiring a passing duration experience threshold corresponding to the section attribute includes: acquiring the road type of a current passing road section where a vehicle is located, wherein the road type comprises the following steps: roundabouts, city trunks, national roads; determining the segment attribute based on the road type and a differentiating dimension, wherein the differentiating dimension comprises: time, weather; and acquiring the experience threshold of the passage duration corresponding to the section attribute according to the mapping relation between the section attribute and the experience threshold.
Optionally, collecting the passing time of the vehicle passing through the traffic intersection within a preset period time; determining a new passing time length empirical value based on the collected passing time length; and judging whether the new passing time length empirical value meets a preset empirical value correction rule, if so, updating the mapping relation between the section attribute and the empirical threshold, taking the new passing time length empirical value as the passing time length empirical threshold corresponding to the section attribute, and storing the replaced passing time length empirical threshold.
Optionally, the determining a new transit time experience value based on the collected transit time includes:
determining the new transit time empirical value T within the (n + 1) th cycle timen+1；
Wherein the content of the first and second substances,
Figure BDA0001164581790000021
tifor the ith vehicle passage duration, viThe passing time for passing through the traffic intersection is tiK is the total number of the collected vehicle passing time.
Optionally, the determining whether the new transit time experience value meets a preset experience value correction rule includes: obtaining the average value of all passing time length experience threshold values corresponding to the section attributes
Figure BDA0001164581790000023
(ii) a Determining the historical empirical value variance of the empirical threshold of all the passing time lengths
Figure BDA0001164581790000022
Wherein, TiThe ith passing duration empirical threshold corresponding to the section attribute is obtained, and m is the number of all passing duration empirical thresholds corresponding to the section attribute;
setting a fluctuation threshold q, when judging
Figure BDA0001164581790000031
And if so, determining that the new passing time length empirical value meets a preset empirical value correction rule.
Optionally, the LoRa communication module mounted on the vehicle sends the position information of the vehicle and the identity information of the vehicle to the LoRa gateway in real time; and receiving the position information sent by the LoRa gateway, and determining the passing time of the vehicle passing through the traffic intersection based on the position information and by combining an electronic map.
Optionally, after determining the current congestion state of the traffic intersection, sending congestion state information to the LoRa communication module through the LoRa gateway, so as to inform a vehicle of road conditions; wherein the types of congestion status information include: voice and text.
According to another aspect of the present invention, there is provided a traffic monitoring device, comprising: the information acquisition module is used for acquiring the passing time of the vehicle passing through the traffic intersection; the section mapping module is used for determining section attributes corresponding to a current passing road section where the vehicle is located and acquiring passing duration experience thresholds corresponding to the section attributes; and the road condition analysis module is used for comparing the passing time with the passing time experience threshold and determining the current congestion state of the traffic intersection based on the comparison result.
Optionally, the section mapping module is specifically configured to obtain a road type of a passing road section where the vehicle is currently located, where the road type includes: roundabouts, city trunks, national roads; determining the segment attribute based on the road type and a differentiating dimension, wherein the differentiating dimension comprises: time, weather; and acquiring the experience threshold of the passage duration corresponding to the section attribute according to the mapping relation between the section attribute and the experience threshold.
Optionally, the information acquisition module is further configured to acquire a passing time length of the vehicle passing through the traffic intersection within a preset period time length; the experience value correction module is used for determining a new passing time length experience value based on the collected passing time length; and judging whether the new passing time length empirical value meets a preset empirical value correction rule, if so, updating the mapping relation between the section attribute and the empirical threshold, taking the new passing time length empirical value as the passing time length empirical threshold corresponding to the section attribute, and storing the replaced passing time length empirical threshold.
Optionally, the empirical value correction module includes: an empirical value calculating unit for determining a new transit time period empirical value T within the n +1 th cycle time periodn+1；
Wherein the content of the first and second substances,
Figure BDA0001164581790000041
tifor the ith vehicle passage duration, viThe passing time for passing through the traffic intersection is tiK is the total number of the collected vehicle passing time.
Optionally, the empirical value correction module includes: a correction rule judging unit for obtaining the average value of all the transit time experience threshold values corresponding to the section attributes
Figure BDA0001164581790000044
(ii) a Determining the historical empirical value variance of the empirical thresholds of all the transit times:
Figure BDA0001164581790000042
wherein, TiThe ith passing duration empirical threshold corresponding to the section attribute is obtained, and m is the number of all passing duration empirical thresholds corresponding to the section attribute;
the correction rule judging unit sets a fluctuation threshold q when judging
Figure BDA0001164581790000043
And if so, determining that the new passing time length empirical value meets a preset empirical value correction rule.
Optionally, the LoRa communication module mounted on the vehicle sends the position information of the vehicle and the identity information of the vehicle to the LoRa gateway in real time; the information acquisition module is further used for receiving the position information sent by the LoRa gateway and determining the passing time of the vehicle passing through the traffic intersection based on the position information and by combining an electronic map.
Optionally, the method further comprises: the road condition information output module is used for sending congestion state information to the LoRa communication module through the LoRa gateway after determining the current congestion state of the traffic intersection and is used for notifying the road condition of the vehicle; wherein the types of congestion status information include: voice and text.
According to another aspect of the present invention, there is provided a system for monitoring road conditions, comprising: the road condition monitoring device is described above.
Optionally, the method further comprises: the location that the loRa gateway set up includes: and (6) traffic intersection.
According to the road condition monitoring method and device and the system for monitoring the road condition, the passing time experience threshold corresponding to the attribute of the current section is obtained to be used as the judgment basis of the road condition, so that the influence of factors such as time and weather can be reduced, and the judgment is more accurate; the experience threshold of the passing time length can be corrected at regular time, the irregular change of factors such as road conditions and weather can be adapted, and the accuracy of judging the road condition is improved; the vehicle information acquisition adopts the LoRa technology, so that the receiving sensitivity is improved, the data of a plurality of nodes can be received and processed in parallel, the construction and the deployment are easy, and the cost of the node terminal is low; the traffic condition of the intersection on the vehicle driving route can be monitored, judged and issued in real time, the road condition prompt is given to the driver, and the driving and route adjustment of the driver are assisted.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic flow chart of an embodiment of a road condition monitoring method according to the present invention;
fig. 2 is a schematic flow chart illustrating another embodiment of the road condition monitoring method according to the present invention;
fig. 3 is a schematic block diagram of a traffic monitoring device according to an embodiment of the present invention;
fig. 4 is a block diagram of an empirical value calibration module in an embodiment of a traffic monitoring device according to the present invention.
Detailed Description
The present invention now will be described more fully hereinafter with reference to the accompanying drawings, in which exemplary embodiments of the invention are shown. The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention. The technical solution of the present invention is described in various aspects below with reference to various figures and embodiments.
Fig. 1 is a schematic flow chart of an embodiment of a road condition monitoring method according to the present invention, as shown in fig. 1:
step 101, obtaining the passing time of the vehicle passing through the intersection.
Step 102, determining a section attribute corresponding to a current passing road section where the vehicle is located, and acquiring a passing duration experience threshold corresponding to the section attribute.
Acquiring the road type of a current passing road section where a vehicle is located, wherein the road type comprises the following steps: roundabouts, city trunks, national roads, etc. Determining a segment attribute based on a road type and a differentiation dimension, the differentiation dimension comprising: time, weather, etc. The current weather can be determined by acquiring weather information in real time and analyzing videos, for example, if the vehicle is judged to start a wiper to run by analyzing monitoring videos, the current weather is determined to be rainy; and judging that the vehicle turns on the fog light by analyzing the monitoring video, and determining that the vehicle is in the foggy day currently. The section attributes of the road are divided through dimensions such as time and weather, and the section attributes can be a night passing section, a peak passing section, a rainy day passing section and the like.
And 103, comparing the passing time with the passing time experience threshold, and determining the current congestion state of the intersection based on the comparison result.
And acquiring a passing time length experience threshold corresponding to the current section attribute according to the mapping relation between the section attribute and the experience threshold. For example, the experience threshold of the passage duration corresponding to the section attributes of the night passage section, the peak passage section, the rainy day passage section and the like may be obtained, and the passage duration may be compared with the experience threshold of the passage duration. By dividing the road passing condition into sections and mapping the section attributes and the experience threshold, the passing time length experience threshold corresponding to different section attributes is used as the judgment basis of the road condition, so that the influence of factors such as time, weather and the like can be reduced.
There are various judgment methods for determining the current congestion state of the intersection based on the comparison result. For example, the transit time period may be a statistical value of transit times of all vehicles in a period of time, if the transit time period is greater than the transit time period experience threshold, congestion is determined to occur, and the congestion level is determined based on the difference between the transit time period of the current vehicle and the transit time period experience threshold.
The existing road condition monitoring method adopts a fixed empirical value to judge congestion, and the misjudgment rate is high. According to the road condition monitoring method of the embodiment, the section attributes and the experience threshold are mapped, the passing time length experience threshold corresponding to different section attributes is used as the judgment basis of the road condition of the road, the road condition of the intersection can be judged dynamically according to the current section attributes, the influence of factors such as time and weather is reduced, the judgment is more accurate, and the existing equipment is not forcibly controlled or changed.
Fig. 2 is a schematic flow chart of another embodiment of the road condition monitoring method according to the present invention, as shown in fig. 2:
step 201, collecting the time length of the vehicle passing through the intersection in a preset period time length. The cycle time may be 30 minutes, 40 minutes, etc.
Step 202, determining a new transit time experience value based on the collected transit time.
And 203, judging whether the experience value of the new passing time meets a preset experience value correction rule, if so, entering a step 204, and if not, entering the next period to acquire the passing time of the vehicle passing through the intersection.
And 204, updating the mapping relation between the section attributes and the experience threshold, taking the new passing time length experience value as the passing time length experience threshold corresponding to the section attributes, storing the replaced passing time length experience threshold, entering the next period, and collecting the passing time length of the vehicle passing through the intersection.
The road condition monitoring method in the embodiment can correct the experience threshold of the crossing passing time at regular time, can adapt to irregular changes of factors such as road conditions and weather, and improves the accuracy of road condition judgment.
There are various ways to determine the new transit time experience value. For example, by weighted time statistics, the empirical value of the new transit time duration in the (n + 1) th cycle duration is determined to be Tn+1；
Figure BDA0001164581790000071
tiFor the ith vehicle passage duration, viThe passing time for passing the intersection is tiK is the total number of the collected vehicle passing time. For example, collectingThe total number of the vehicle passing time periods is 5, which are respectively 5.0, 6.0, 5.2, 5.9 and 7.0 seconds, and the vehicle passing time periods through the intersection are respectively 5.0, 6.0, 5.2, 5.9 and 7.0 seconds and are respectively 6, 7, 9, 10 and 11. And substituting the acquired data into the formula to calculate a new passing time length empirical value.
The empirical value correction rule may be various. For example, the average of all transit time experience thresholds corresponding to the section attributes is obtained
Figure BDA0001164581790000081
Determining historical experience value variance of experience threshold values for all transit times
Figure BDA0001164581790000082
Wherein, TiThe number of the ith passing time length empirical threshold values corresponding to the section attributes is m, and the number of all passing time length empirical threshold values corresponding to the section attributes is m. For example, if the number of all passage time length experience thresholds corresponding to the passage section with the section attribute of overcast and rainy days is 8, 8 passage time length experience thresholds are substituted into the above expression to be calculated. The all-transit-time experience threshold includes the currently used and replaced transit-time experience thresholds.
Setting a fluctuation threshold q, when judging
Figure BDA0001164581790000083
And if so, determining that the experience value of the new passing time meets the preset correction rule of the experience value. The fluctuation threshold q may be adjusted according to design requirements.
The Long Rang (ultra-Long distance and low power consumption data transmission technology) uses a linear frequency modulation spread spectrum modulation technology, so that the low power consumption characteristic like FSK (frequency shift keying) modulation is kept, the communication distance is obviously increased, the network efficiency is improved, and the interference is eliminated, namely, terminals with different spread spectrum sequences transmit at the same time by using the same frequency without mutual interference, therefore, a concentrator/gateway developed on the basis of the Long Rang technology can receive and process data of a plurality of nodes in parallel, and the system capacity is greatly expanded. The LoRa mainly operates in the global free frequency band (i.e., unlicensed frequency band), including 433MHz, 868MHz, 915MHz, etc.
The LoRa technology has the functions of ranging and positioning. And the LoRa communication module installed on the vehicle sends the position information and the identity information of the vehicle to the LoRa gateway in real time. And receiving the position information sent by the LoRa gateway, and determining the passing time of the vehicle passing through the intersection based on the position information and in combination with the electronic map. The position information of the vehicle can also be acquired by a GPS device of the vehicle and sent to the LoRa gateway through a LoRa communication module installed on the vehicle.
After the current congestion state of the intersection is determined, the congestion state information is sent to an LoRa communication module through an LoRa gateway based on vehicle identity information, road condition notification is carried out on the vehicle, and the types of the congestion state information comprise: speech, text, etc.
The vehicle information acquisition adopts the application of the LoRa technology, improves the receiving sensitivity, can receive and process the data of a plurality of nodes in parallel, is easy to construct and deploy, and has low cost of the node terminal. In the vehicle running process, the traffic condition of the intersection on the vehicle running route can be monitored, judged and issued in real time, the road condition prompt is given to a driver, and the driving and route adjustment of the driver are assisted.
According to the road condition monitoring method in the embodiment, vehicle driving data are collected through the LoRa communication module/gateway in a set time period, new passing time experience values in different sections are obtained through a weighted time window statistical method, whether the new experience values are effective or not is judged according to set correction rules, if yes, the existing experience values are replaced to serve as new analysis basis of road condition conditions, accuracy of judgment on conditions such as road congestion is improved, judgment is more accurate, and if the analysis result meets the condition of road congestion, congestion reminding information is output.
In one embodiment, as shown in fig. 3, the present invention provides a road condition monitoring device 30, including: the system comprises an information acquisition module 31, a section mapping module 32, a road condition analysis module 33, an empirical value correction module 34 and a road condition information output module 35. The information acquisition module 31 acquires the passing time of the vehicle passing through the intersection. The section mapping module 32 determines a section attribute corresponding to a current passing road section where the vehicle is located, and obtains a passing duration experience threshold corresponding to the section attribute. The road condition analysis module 33 compares the passing time with the passing time experience threshold, and determines the current congestion state of the intersection based on the comparison result.
The section mapping module 32 obtains a road type of a passing road section where the vehicle is currently located, where the road type includes: roundabouts, city trunks, national roads, etc. The segment mapping module 32 determines segment attributes based on road type and differentiating dimensions, including: time, weather, etc. The section mapping module 32 obtains the experience threshold of the passage duration corresponding to the section attribute according to the mapping relationship between the section attribute and the experience threshold.
The information acquisition module 31 acquires the passing time of the vehicle passing through the intersection within a preset period time. The experience value correction module 34 determines a new transit time length experience value based on the acquired transit time length, determines whether the new transit time length experience value meets a preset experience value correction rule, if so, updates the mapping relationship between the section attribute and the experience threshold value, takes the new transit time length experience value as a transit time length experience threshold value corresponding to the section attribute, and stores the replaced transit time length experience threshold value.
As shown in fig. 4, the empirical value correction module 34 includes: an empirical value calculation unit 341 and a correction rule judgment unit 342. The empirical value calculation unit 341 determines the new transit time period empirical value T in the n +1 th cycle time periodn+1。
Figure BDA0001164581790000101
tiFor the ith vehicle passage duration, viThe passing time for passing the intersection is tiK is the total number of the collected vehicle passing time.
The correction rule judgment unit 342 acquires the average value of all transit time length empirical thresholds corresponding to the section attribute
Figure BDA0001164581790000102
Determining history of experience thresholds for all transit timesVariance of empirical value
Figure BDA0001164581790000103
TiThe number of the ith passing time length empirical threshold corresponding to the section attribute is m, and the m is the number of all passing time length empirical thresholds corresponding to the section attribute;
the correction rule judging unit 342 sets the fluctuation threshold q, when judged
Figure BDA0001164581790000104
And if so, determining that the experience value of the new passing time meets the preset correction rule of the experience value.
And the LoRa communication module installed on the vehicle sends the position information and the identity information of the vehicle to the LoRa gateway in real time. The information acquisition module 31 receives the position information sent by the LoRa gateway, and determines the passing time of the vehicle passing through the intersection based on the position information and by combining with the electronic map. After determining the current congestion state of the intersection, the traffic information output module 35 sends the congestion state information to the LoRa communication module through the LoRa gateway, so as to inform the vehicle of the traffic conditions, where the types of the congestion state information include: speech, text, etc.
In one embodiment, the present invention provides a system for monitoring road conditions, comprising: as above road condition monitoring devices, LoRa gateway, the position that LoRa gateway set up includes: traffic intersections, and the like.
According to the road condition monitoring method in the embodiment, the section attribute corresponding to the current passing road section of the vehicle is determined, the passing time experience threshold corresponding to the current section attribute is obtained to serve as the judgment basis of the road condition of the road, the road condition can be judged according to the current section attribute, the influence of factors such as time and weather is reduced, the judgment is more accurate, and the existing equipment is not forcibly controlled or changed; the experience threshold of the crossing passing time can be corrected at regular time, the method can adapt to irregular changes of factors such as road conditions and weather, and the accuracy of judging the road conditions is improved; the vehicle information acquisition adopts the application of the LoRa technology, so that the receiving sensitivity is improved, the data of a plurality of nodes can be received and processed in parallel, the construction and the deployment are easy, and the cost of the node terminal is low; in the vehicle running process, the traffic condition of the intersection on the vehicle running route can be monitored, judged and issued in real time, the road condition prompt is given to a driver, and the driving and route adjustment of the driver are assisted.
The method and system of the present invention may be implemented in a number of ways. For example, the methods and systems of the present invention may be implemented in software, hardware, firmware, or any combination of software, hardware, and firmware. The above-described order for the steps of the method is for illustrative purposes only, and the steps of the method of the present invention are not limited to the order specifically described above unless specifically indicated otherwise. Furthermore, in some embodiments, the present invention may also be embodied as a program recorded in a recording medium, the program including machine-readable instructions for implementing a method according to the present invention. Thus, the present invention also covers a recording medium storing a program for executing the method according to the present invention.
The description of the present invention has been presented for purposes of illustration and description, and is not intended to be exhaustive or limited to the invention in the form disclosed. Many modifications and variations will be apparent to practitioners skilled in this art. The embodiment was chosen and described in order to best explain the principles of the invention and the practical application, and to enable others of ordinary skill in the art to understand the invention for various embodiments with various modifications as are suited to the particular use contemplated.

Claims (8)

1. A road condition monitoring method is characterized by comprising the following steps:
acquiring the passing time of a vehicle passing through a traffic intersection;
determining a section attribute corresponding to a current passing road section where a vehicle is located, and acquiring a passing duration experience threshold corresponding to the section attribute;
the method comprises the following steps of obtaining the road type of a current passing road section where a vehicle is located, wherein the road type comprises the following steps: roundabouts, city trunks, national roads; determining the segment attribute based on the road type and a differentiating dimension, the differentiating dimension comprising: time, weather; acquiring the experience threshold of the passing time length corresponding to the section attribute according to the mapping relation between the section attribute and the experience threshold;
collecting the passing time of a vehicle passing through a traffic intersection in a preset period time; determining a new passing time length empirical value based on the collected passing time length; judging whether the new passing time length empirical value meets a preset empirical value correction rule or not, if so, updating the mapping relation between the section attribute and an empirical threshold, taking the new passing time length empirical value as the passing time length empirical threshold corresponding to the section attribute, and storing the replaced passing time length empirical threshold;
comparing the passing time with the passing time experience threshold, and determining the current congestion state of the traffic intersection based on the comparison result;
the determining a new transit time experience value based on the collected transit time includes:
determining the new transit time empirical value T within the (n + 1) th cycle timen+1；
Wherein the content of the first and second substances,
Figure FDA0002811372300000011
tifor the ith vehicle passage duration, viThe passing time for passing through the traffic intersection is tiK is the total number of the collected vehicle passing time;
the step of judging whether the experience value of the new passing time meets a preset experience value correction rule comprises the following steps:
obtaining the average value of all passing time length experience threshold values corresponding to the section attributes
Figure FDA0002811372300000012
Determining the historical empirical value variance of the empirical thresholds of all the transit times:
Figure FDA0002811372300000021
wherein, TiIs the ith and the sectionThe passing time length experience threshold corresponding to the attribute, wherein m is the number of all passing time length experience thresholds corresponding to the section attribute;
setting a fluctuation threshold q, when judging
Figure FDA0002811372300000022
And if so, determining that the new passing time length empirical value meets a preset empirical value correction rule.
2. The method of claim 1, further comprising:
the LoRa communication module installed on the vehicle sends the position information and the identity information of the vehicle to the LoRa gateway in real time;
and receiving the position information sent by the LoRa gateway, and determining the passing time of the vehicle passing through the traffic intersection based on the position information and by combining an electronic map.
3. The method of claim 2, further comprising:
after the current congestion state of the traffic intersection is determined, sending congestion state information to the LoRa communication module through the LoRa gateway for notifying road conditions of vehicles;
wherein the types of congestion status information include: voice and text.
4. A road condition monitoring device, comprising:
the information acquisition module is used for acquiring the passing time of the vehicle passing through the traffic intersection;
the section mapping module is used for determining section attributes corresponding to a current passing road section where the vehicle is located and acquiring passing duration experience thresholds corresponding to the section attributes;
the section mapping module is specifically configured to acquire a road type of a passing road section where a vehicle is currently located, where the road type includes: roundabouts, city trunks, national roads; determining the segment attribute based on the road type and a differentiating dimension, the differentiating dimension comprising: time, weather; acquiring the experience threshold of the passing time length corresponding to the section attribute according to the mapping relation between the section attribute and the experience threshold;
the information acquisition module is also used for acquiring the passing time of the vehicle passing through the traffic intersection within the preset period time;
the experience value correction module is used for determining a new passing time length experience value based on the collected passing time length; judging whether the new passing time length empirical value meets a preset empirical value correction rule or not, if so, updating the mapping relation between the section attribute and an empirical threshold, taking the new passing time length empirical value as the passing time length empirical threshold corresponding to the section attribute, and storing the replaced passing time length empirical threshold;
the road condition analysis module is used for comparing the passing time with the passing time experience threshold and determining the current congestion state of the traffic intersection based on the comparison result;
wherein the empirical value correction module comprises:
an empirical value calculating unit for determining a new transit time period empirical value T within the n +1 th cycle time periodn+1；
Wherein the content of the first and second substances,
Figure FDA0002811372300000031
tifor the ith vehicle passage duration, viThe passing time for passing through the traffic intersection is tiK is the total number of the collected vehicle passing time;
a correction rule judging unit for obtaining the average value of all the transit time experience threshold values corresponding to the section attributes
Figure FDA0002811372300000032
Determining the historical empirical value variance of the empirical thresholds of all the transit times:
Figure FDA0002811372300000033
wherein, TiThe ith passing duration empirical threshold corresponding to the section attribute is obtained, and m is the number of all passing duration empirical thresholds corresponding to the section attribute;
the correction rule judging unit sets a fluctuation threshold q when judging
Figure FDA0002811372300000041
And if so, determining that the new passing time length empirical value meets a preset empirical value correction rule.
5. The apparatus of claim 4, wherein the LoRa communication module installed on the vehicle transmits the position information of the vehicle and the identity information of the vehicle to the LoRa gateway in real time;
the information acquisition module is further used for receiving the position information sent by the LoRa gateway and determining the passing time of the vehicle passing through the traffic intersection based on the position information and by combining an electronic map.
6. The apparatus of claim 5, further comprising:
the road condition information output module is used for sending congestion state information to the LoRa communication module through the LoRa gateway after determining the current congestion state of the traffic intersection and is used for notifying the road condition of the vehicle;
wherein the types of congestion status information include: voice and text.
7. A system for monitoring road conditions, comprising:
a traffic monitoring device as claimed in any one of claims 4 to 6.
8. The system of claim 7, further comprising: the location that the loRa gateway set up includes: and (6) traffic intersection.
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CN101430829B (en) * 2008-12-18 2010-09-29 中国移动通信集团江苏有限公司 Method and system for traffic dispersion based on GSM data network
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CN102354452B (en) * 2011-08-01 2014-03-26 重庆大学 Method for monitoring road conditions in real time based on simplified road network model
CN103514743B (en) * 2013-09-28 2016-01-06 上海电科智能系统股份有限公司 A kind of abnormal traffic state characteristic recognition method of real-time index-matched memory range
CN104021672B (en) * 2014-06-09 2016-09-07 北京世纪高通科技有限公司 A kind of method and apparatus obtaining traffic congestion index

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