CN114299720A - Public service traffic management method and system based on Internet of things - Google Patents
Public service traffic management method and system based on Internet of things Download PDFInfo
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Abstract
The application relates to a public service traffic management system based on thing networking includes: the system comprises a public service platform, an information monitoring unit, a road condition analysis unit and a traffic regulation and control unit; the road condition analysis unit is used for identifying the vehicle running condition according to the information monitoring unit, analyzing the traffic running smoothness or congestion degree, and changing the traffic running smoothness or congestion degree along with the time and the position; and the traffic control unit is used for taking corresponding measures according to the result obtained by the road condition analysis unit. According to the method and the system, the traffic regulation and control strategy is adjusted according to the congestion index, so that the flexibility of system operation is integrally improved; a single congestion index is introduced to pre-judge vehicles to be converged at an evaluation intersection, so that the predictability of the traffic running condition of the road surface is improved; the related congestion indexes are introduced, so that the coordination degree of the intersection to be evaluated and each adjacent intersection is improved; the evaluation frequency of the congestion index is adjusted according to the running conditions of the road surface, so that the adaptability to the traffic running conditions in different time periods is enhanced.
Description
Technical Field
The application relates to the field of public services, in particular to a public service traffic management method and system based on the Internet of things.
Background
In public service systems, traffic management is a very important component. In cities, the quantity of motor vehicles is large, the conditions of intersections and road sections are complicated, and the large-scale dynamic distributed system with high uncertainty needs to be processed for effective control, so that the method is very complicated work. Under the condition that a traffic road is not newly added, the utilization efficiency of the road is improved through reasonable traffic management control, and then the traffic efficiency is improved, so that the method is an effective way for rapidly solving the urban traffic problem.
CN201310395431.8 discloses a method and a system for judging and controlling intersection traffic jam based on an induction detector, wherein the technical scheme is that the system comprises: the induction detector is arranged at an entrance lane of each lane of the intersection and is used for detecting passing vehicles; the signal lamp control device is used for calculating the traffic intensity of the intersection at intervals of a set statistical period according to the detection signals sent by the induction detectors; for each induction detector, calculating the time occupancy within a set time period at intervals of a set sampling period, and determining that the lane where the induction detector is located is in a congestion state when the time occupancy calculated for m continuous sampling periods is greater than a set occupancy threshold; if the signal lamp control device judges that the intersection traffic intensity calculated in the current statistical period exceeds a set traffic intensity threshold value and a traffic lane is in a congestion state, judging that the traffic condition of the intersection is a congestion condition of queuing overflow; and then, controlling the traffic lights at the intersection by adopting a traffic light control scheme corresponding to the congestion condition of the queue overflow.
The intersection traffic jam judging and controlling method and system based on the induction detector have the following advantages: calculating the traffic intensity of the intersection according to detection signals sent by an induction detector arranged at an entrance lane of each lane of the intersection, determining whether the lanes are congested or not, judging the traffic condition of the intersection according to the calculated traffic intensity of the intersection and whether the lanes are congested or not, and controlling the traffic lights of the intersection by adopting a traffic light control scheme corresponding to the traffic condition of the intersection; therefore, the detection of the intersection congestion state is realized with less investment cost and smaller road breaking area, and when the intersection has a traffic condition of queuing overflow, the vehicles of the lane with the congestion state are prevented from continuously entering the intersection, and the traffic congestion condition of the intersection is relieved; when a traffic accident occurs at the intersection, the method can relieve the blockage caused by the traffic accident from queuing at the intersection, and ensure the traffic operation of the vehicles at the intersection.
However, the intersection traffic jam determination and control method and system based on the induction detector also have the following disadvantages: the running conditions of vehicles at each intersection are not comprehensively considered, and the vehicles about to be converged at the intersection cannot be pre-judged; only the running condition of a single intersection is considered, the one-sidedness is achieved, and the condition that the congestion of adjacent intersections is caused by only ensuring the maximum traffic of the single intersection can be caused.
Therefore, a method and a system for pre-judging vehicles about to be merged into the intersection and comprehensively considering the running conditions of the vehicles at each intersection are needed.
Disclosure of Invention
In order to solve the problems that the vehicles about to enter the intersection can not be pre-judged and the operation condition of the intersection can not be considered one-sidedly, the application provides a public service traffic management method and system based on the Internet of things.
The application provides a public service traffic management method based on the Internet of things, which comprises the following steps:
step S1, collecting road surface information, collecting road surface image information, and identifying the running state and the position of a road vehicle;
step S2, analyzing road conditions, analyzing the smooth degree or congestion degree of traffic operation according to the running conditions of the road vehicles at each position, and analyzing the change conditions of the running conditions of the road vehicles at each position along with time and position;
and step S3, taking measures, and according to the traffic operation smooth degree or congestion degree analyzed and obtained in the step S2, making evaluation and taking corresponding measures.
The step S1 includes: s11, recognizing lane directions, namely recognizing the driving directions of all lanes on the road surface by the lane direction recognition module through the road surface image information collected by the road surface monitoring module; s12, traffic flow statistics, wherein the traffic flow statistics module identifies the number of vehicles in each lane through the road image information collected by the road monitoring module; s13, identifying the positions of the signal lamps, and identifying the positions of the signal lamps and the types of nearby buildings by the signal lamp position identification module in combination with the identification of the city map module; and S14, recognizing sudden accidents, recognizing whether the road surface is blocked due to accidents or not by the accident recognition module through the road surface image information provided by the road surface monitoring module, and recognizing the number of the blocked lanes.
The step S2 includes: s21, analyzing the ordinary road condition, and summarizing the vehicle running rule by analyzing the vehicle running conditions of different positions at different times through the time counting module and the position judging module; s22, analyzing the current intersection condition, and analyzing the unobstructed degree or congestion degree of the vehicle running at the current intersection according to the vehicle running condition provided by the information monitoring unit; s23, analyzing the conditions of the nearby intersections, and analyzing the vehicle operating conditions of each intersection nearby the current intersection through the vehicle operating conditions provided by the information monitoring unit, namely the quantity of vehicles entering the current intersection and the direction of entering a lane at other intersections; and S24, evaluating road conditions, namely, evaluating the traffic conditions of a single intersection and evaluating the related traffic conditions between each intersection by the road condition judging module according to the vehicle running conditions of the current intersection and the adjacent intersections.
By adopting the technical scheme, the ordinary traffic road conditions can be analyzed, the rules can be summarized, the time factor and the position factor are combined, the signal lamp control can be carried out in the non-congestion state of the road surface according to the rules of the ordinary traffic road conditions, and the data processing time is greatly shortened.
In step S2, the method for evaluating the clear degree or the congestion degree of the vehicle running at a single intersection is shown in the following formula:
eta is expressed as a single congestion index of a lane corresponding to a certain phase at the intersection 0, namely the current intersection;
X0the number of vehicles of the corresponding lane of the phase at the intersection 0 is represented;
Y0the maximum number of vehicles allowed to stay in the corresponding lane of the phase at the intersection 0 is represented, and five meters in length is taken as the maximum length of a single vehicle;
X1the total number of vehicles which are converged into the lane in the direction of the No. 0 intersection in all lanes of the No. 1 intersection is represented;
Y1the maximum number of vehicles allowed to stay in the lane converged to the direction of the No. 0 intersection in all lanes of the No. 1 intersection is represented, and the length of five meters is taken as the maximum length of a single vehicle;
Xnthe total number of vehicles converging into lanes in the direction of the n-1 intersection in all lanes of the n-number intersection is represented;
Yn-1the maximum number of vehicles allowed to stay in lanes converging to the direction of the n-2 intersection is expressed in all lanes of the n-1 intersection, and the length of five meters is taken as the maximum length of a single vehicle;
wherein, n intersections are defined as intersections with a distance of one intersection from n-1 intersections, and 0 intersection is the current evaluation intersection;
the set threshold value of the single congestion index is 0.75.
By adopting the technical scheme, the single congestion index can intuitively reflect the running condition of road traffic, and the intuitive degree of judging the running condition of the road traffic is improved. The single congestion index is used for prejudging the vehicles to be merged at the intersection to be evaluated, so that the predictability of the road traffic running condition is improved, the data processing time is greatly reduced, and the traffic running management efficiency is improved.
In step S2, the method for evaluating the correlation between the traffic conditions of a single intersection and other intersections nearby includes:
ε represents the relevant congestion index;
Tnrepresenting the number of intersections with a single congestion index larger than a set threshold in all the n intersections;
the set threshold value of the related congestion index is 0.5.
By adopting the technical scheme, the relevance between the intersection to be evaluated and other intersections is evaluated by the relevant congestion index, the smooth degree of traffic operation can be improved by the coordination and coordination among the intersections, the operation conditions of the intersection to be evaluated and the adjacent intersections are comprehensively considered, and the comprehensive degree of grasp of the intersections on the overall road surface is improved.
The step S3 includes: s31, local signal lamp control; s32, information pushing;
in the step S31, when both the single congestion index and the related congestion index are lower than the set threshold, the signal lamp control module controls the proportion of the period duration of each phase of the signal lamp to be matched with the analyzed vehicle operation rule according to the vehicle operation rule analyzed in the step S21 and according to different positions at different times; when any one of the single congestion index or the related congestion index is higher than the set threshold, the signal lamp control module controls the proportion of the time length of each phase of the signal lamp in the period time according to the real-time traffic flow, so that the time length of each phase of the intersection is matched with the number of the vehicles on the corresponding lane of each phase, and the calculation method of the proportion of the time length of each phase in the period time refers to the following formula:
wherein, λ represents the proportion of the time length of a certain phase of the signal lamp to the period time length; etaiA single congestion index expressed as a phase;
in step S32, when the single congestion index at a certain intersection is higher than the set threshold, the congestion information is pushed to nearby vehicles by the information pushing module, and a detour suggestion is proposed; when the accident recognition module monitors that a traffic accident happens to a lane at a certain intersection, if the accident recognition module recognizes that the number of the traffic jam lanes caused by the accident is more than one half of the number of the total lanes, the information pushing module is used for pushing accident information to nearby vehicles to provide a detour suggestion, and if the accident recognition module recognizes that the number of the traffic jam lanes caused by the accident is less than one half of the number of the total lanes, the information pushing module is used for pushing accident information to nearby vehicles to provide a delay suggestion.
By adopting the technical scheme, the traffic regulation and control strategy is adjusted according to the congestion index, the control capacity of the system on the road condition in the traffic congestion period is improved, the data calculation time and the operation cost in the idle traffic period are reduced, and the flexibility of the system operation and the management efficiency of the traffic operation are integrally improved.
The evaluation frequency of the single congestion index and the related congestion index changes according to time and position, the peak time evaluation frequency is once evaluated for fifteen minutes, the ordinary evaluation frequency is once evaluated for thirty minutes, and the peak time and the ordinary time interval of the position to be evaluated are obtained from the vehicle running rule obtained by analyzing the ordinary road condition in the step S21.
By adopting the technical scheme, the evaluation frequency of the congestion index is adjusted according to the running condition of the road surface, so that the condition that the feedback on the traffic congestion state cannot be made due to the fact that the evaluation frequency is too slow in the traffic congestion period or the waste of the system running cost is caused by the fact that the evaluation frequency is too fast in the idle traffic period is prevented. The adaptability to traffic operation conditions in different time periods is enhanced, and the flexibility of system operation is improved.
A public service traffic management system based on the Internet of things comprises: the system comprises a public service platform, an information monitoring unit, a road condition analysis unit and a traffic regulation and control unit;
the public service platform is respectively connected with the information monitoring unit, the road condition analysis unit and the traffic regulation and control unit through the Internet of things; the public service platform comprises: the road surface monitoring module is used for acquiring road surface image information; the city map module is used for importing a city map model and matching road surface image information; the data storage module is used for receiving and storing data;
the information monitoring unit is used for identifying the running conditions of the vehicles on the road surface of each point of the city by combining the city map module according to the road surface image information provided by the road surface monitoring module;
the road condition analysis unit is used for analyzing the traffic running smoothness or congestion degree according to the running conditions of the road vehicles at each place identified by the information monitoring unit and analyzing the change condition of the running conditions of the road vehicles at each place along with time and position;
the traffic control unit is used for taking corresponding measures according to the result obtained by the road condition analysis unit so as to control road traffic; the traffic control unit includes: the signal lamp control module is used for receiving the result obtained by the road condition analysis unit and adjusting the time of each phase of the signal lamp; and the information pushing module is used for pushing the road condition information and the burst information to nearby vehicles and judging the route planning in advance.
The information monitoring unit includes: the lane direction identification module is used for identifying the driving direction of each lane on the road surface according to the road surface image information provided by the road surface monitoring module; the traffic flow counting module is used for identifying the number of the vehicles in each lane according to the road surface image information provided by the road surface monitoring module; the signal lamp position identification module is used for identifying the position of each signal lamp and the type of a nearby building by combining the city map module; and the accident identification module is used for identifying whether the road surface is blocked due to the accident or not and the number of the blocked lanes according to the road surface image information provided by the road surface monitoring module.
The traffic condition analysis unit includes: the time counting module is used for matching the vehicle running conditions of the road surface at different times with the time; the position judging module is used for analyzing the vehicle running conditions of all positions at different time in a combined manner according to the types of the buildings at the positions; and the road surface condition judging module is used for judging the smooth degree or the congestion degree of road surface traffic operation so as to send a control instruction to the traffic control unit.
To sum up, the application comprises the following beneficial technical effects:
1. the traffic regulation and control strategy is adjusted according to the congestion index, signal lamp control can be carried out according to the rule of common traffic road conditions in a road non-congestion state, and the proportion of the signal lamp time length occupying the period time length is controlled in real time to be matched with the traffic flow in the road congestion state, so that the flexibility degree of system operation and the management efficiency of traffic operation are integrally improved;
2. the single congestion index is introduced, the running condition of road traffic can be visually reflected, vehicles about to be converged at the evaluation intersection are pre-judged, and the predictability of the running condition of the road traffic is improved;
3. the related congestion index is introduced, the running conditions of the intersection to be evaluated and the adjacent intersections are comprehensively considered, and the comprehensive degree of grasp of the intersections on the road surface is improved;
4. the evaluation frequency of the congestion index is adjusted according to the running condition of the road surface, the adaptability to the traffic running conditions in different time periods is enhanced, and the flexibility of the system running is improved.
Drawings
Fig. 1 is a step diagram of a public service traffic management method based on the internet of things according to an embodiment of the present application.
Fig. 2 is a structural diagram of a public service traffic management system based on the internet of things according to an embodiment of the present application.
Description of reference numerals:
the system comprises a public service platform 1, a road surface monitoring module 11, an urban map module 12, a data storage module 13,
An information monitoring unit 2, a lane direction recognition module 21, a traffic flow statistic module 22, a signal lamp position recognition module 23, an accident recognition module 24,
Road condition analysis unit 3, time statistic module 31, position determination module 32, road surface condition determination module 33,
The traffic control unit 4, the signal lamp control module 41 and the information pushing module 42.
Detailed Description
The following description of the embodiments with reference to the drawings is provided to describe the embodiments, and the embodiments of the present application, such as the shapes and configurations of the components, the mutual positions and connection relationships of the components, the functions and working principles of the components, the manufacturing processes and the operation and use methods, etc., will be further described in detail to help those skilled in the art to more fully, accurately and deeply understand the inventive concepts and technical solutions of the present invention. For convenience of description, the directions mentioned in the present application shall be those shown in the drawings.
Referring to fig. 1-2, a public service traffic management method based on the internet of things includes the following steps:
step S1, collecting road surface information, collecting road surface image information, and identifying the running state and the position of a road vehicle;
step S2, analyzing road conditions, analyzing the smooth degree or congestion degree of traffic operation according to the running conditions of the road vehicles at each position, and analyzing the change conditions of the running conditions of the road vehicles at each position along with time and position;
and step S3, taking measures, and according to the traffic operation smooth degree or congestion degree analyzed and obtained in the step S2, making evaluation and taking corresponding measures.
The step S1 includes: s11, recognizing lane directions, namely recognizing the driving directions of all lanes on the road surface by the lane direction recognition module 21 through the road surface image information collected by the road surface monitoring module 11; s12, traffic flow statistics, wherein the traffic flow statistics module 22 identifies the number of vehicles in each lane through the road image information collected by the road monitoring module 11; s13, identifying the positions of the signal lamps, and identifying the positions of the signal lamps and the types of the nearby buildings by the signal lamp position identification module 23 in combination with the identification of the city map module 12; s14, accident recognition, road surface image information provided by the road surface monitoring module 11, recognition of whether the road surface is blocked by accident by the accident recognition module 24, and the number of lanes to be blocked.
The step S2 includes: s21, analyzing the ordinary road condition, and summarizing the vehicle running rule by analyzing the vehicle running conditions of different positions at different times through the time counting module 31 and the position judging module 32; s22, analyzing the current intersection condition, and analyzing the unobstructed degree or congestion degree of the vehicle running at the current intersection according to the vehicle running condition provided by the information monitoring unit 2; s23, analyzing the conditions of the nearby intersections, and analyzing the vehicle operating conditions of each intersection nearby the current intersection through the vehicle operating conditions provided by the information monitoring unit 2, namely the quantity of vehicles entering the current intersection and the direction of entering a lane at other intersections; s24, evaluating road conditions, wherein the road condition judging module 33 evaluates the traffic conditions of a single intersection and the related traffic conditions between each intersection according to the vehicle running conditions of the current intersection and the adjacent intersections.
In step S2, the method for evaluating the clear degree or the congestion degree of the vehicle running at a single intersection is shown in the following formula:
eta is expressed as a single congestion index of a lane corresponding to a certain phase at the intersection 0, namely the current intersection;
X0the number of vehicles of the corresponding lane of the phase at the intersection 0 is represented;
Y0the maximum number of vehicles allowed to stay in the corresponding lane of the phase at the intersection 0 is represented, and five meters in length is taken as the maximum length of a single vehicle;
X1the total number of vehicles which are converged into the lane in the direction of the No. 0 intersection in all lanes of the No. 1 intersection is represented;
Y1the maximum number of vehicles allowed to stay in the lane converged to the direction of the No. 0 intersection in all lanes of the No. 1 intersection is represented, and the length of five meters is taken as the maximum length of a single vehicle;
Xnthe total number of vehicles converging into lanes in the direction of the n-1 intersection in all lanes of the n-number intersection is represented;
Yn-1the maximum number of vehicles allowed to stay in lanes converging to the direction of the n-2 intersection is expressed in all lanes of the n-1 intersection, and the length of five meters is taken as the maximum length of a single vehicle;
wherein, n intersections are defined as intersections with a distance of one intersection from n-1 intersections, and 0 intersection is the current evaluation intersection;
the set threshold value of the single congestion index is 0.75.
In step S2, the method for evaluating the correlation between the traffic conditions of a single intersection and other intersections nearby includes:
ε represents the relevant congestion index;
Tnrepresenting the number of intersections with a single congestion index larger than a set threshold in all the n intersections;
the set threshold value of the related congestion index is 0.5.
The step S3 includes: s31, local signal lamp control; s32, information pushing;
in the step S31, when both the single congestion index and the related congestion index are lower than the set threshold, the signal lamp control module 41 controls the ratio of the time duration of each phase of the signal lamp occupying the period to match the analyzed vehicle operation rule according to the vehicle operation rule analyzed in the step S21 and according to different positions at different times; when any one of the single congestion index and the related congestion index is higher than the set threshold, the signal lamp control module 41 controls the proportion of the time length of each phase of the signal lamp in the period time according to the real-time traffic flow, so that the time length of each phase of the intersection is matched with the number of the vehicles in the lane corresponding to each phase, and the calculation method of the proportion of the time length of each phase in the period time refers to the following formula:
wherein, λ represents the proportion of the time length of a certain phase of the signal lamp to the period time length; etaiA single congestion index expressed as a phase;
in step S32, when the single congestion index at a certain intersection is higher than the set threshold, the congestion information is pushed to nearby vehicles by the information pushing module 42, and a detour suggestion is proposed; when the accident recognition module 24 monitors that a traffic accident occurs in a lane at a certain intersection, if the accident recognition module 24 recognizes that the number of the traffic lane blocked by the accident is greater than one half of the total number of the traffic lane, the information push module 42 pushes accident information to nearby vehicles to provide a detour suggestion, and if the accident recognition module 24 recognizes that the number of the traffic lane blocked by the accident is less than one half of the total number of the traffic lane, the information push module 42 pushes accident information to nearby vehicles to provide a delay suggestion.
The evaluation frequency of the single congestion index and the related congestion index changes according to time and position, the peak time evaluation frequency is once evaluated for fifteen minutes, the ordinary evaluation frequency is once evaluated for thirty minutes, and the peak time and the ordinary time interval of the position to be evaluated are obtained from the vehicle running rule obtained by analyzing the ordinary road condition in the step S21.
A public service traffic management system based on the Internet of things comprises: the system comprises a public service platform 1, an information monitoring unit 2, a road condition analysis unit 3 and a traffic regulation and control unit 4;
the public service platform 1 is respectively connected with the information monitoring unit 2, the road condition analysis unit 3 and the traffic regulation and control unit 4 through the Internet of things; the common service platform 1 comprises: the road surface monitoring module 11 is used for acquiring road surface image information; the city map module 12 is used for importing a city map model and matching road surface image information; a data storage module 13 for receiving and storing data;
the information monitoring unit 2 is used for identifying the running conditions of the vehicles on the road surface of each point of the city by combining the city map module 12 according to the road surface image information provided by the road surface monitoring module 11;
the road condition analysis unit 3 is used for analyzing the traffic smooth degree or congestion degree according to the running conditions of the road vehicles at each place identified by the information monitoring unit 2, and analyzing the change conditions of the running conditions of the road vehicles at each place along with time and position;
the traffic control unit 4 is used for taking corresponding measures according to the result obtained by the road condition analysis unit 3 so as to control road traffic; the traffic control unit 4 includes: the signal lamp control module 41 is used for receiving the result obtained by the road condition analysis unit 3 and adjusting the time of each phase of the signal lamp; and the information pushing module 42 is used for pushing the road condition information and the burst information to nearby vehicles and judging route planning in advance.
The information monitoring unit 2 includes: a lane direction recognition module 21, configured to recognize a driving direction of each lane on the road surface according to the road surface image information provided by the road surface monitoring module 11; the traffic flow counting module 22 is configured to identify the number of vehicles in each lane according to the road image information provided by the road monitoring module 11; the signal lamp position identification module 23 is used for identifying the position of each signal lamp and the type of a nearby building by combining the city map module 12; and the accident identification module 24 is used for identifying whether road surface blockage caused by an accident occurs on the road surface and the number of blocked lanes according to the road surface image information provided by the road surface monitoring module 11.
The road condition analysis unit 3 includes: the time counting module 31 is used for matching the vehicle running conditions of the road surface at different times with the time; the position judging module 32 is used for analyzing the vehicle running conditions of all positions at different time in a combined manner according to the types of the buildings at the positions; and the road condition determining module 33 is configured to determine the smoothness or congestion degree of road traffic operation, so as to send a control instruction to the traffic control unit 4.
In the embodiment of the application, the working principle of the public service traffic management method and system based on the Internet of things is as follows: and adjusting a traffic regulation and control strategy according to the congestion index, performing signal lamp control according to the rule of common traffic road conditions in a road non-congestion state, and controlling the proportion of the signal lamp time length occupying the period time length to be matched with the traffic flow in real time in the road congestion state, so that the flexibility of system operation and the management efficiency of traffic operation are integrally improved. A single congestion index is introduced to pre-judge vehicles to be converged at an evaluation intersection, so that the predictability of the traffic running condition of the road surface is improved; and introducing a related congestion index, and performing relevance evaluation on each intersection. The running condition of the road traffic can be visually reflected by combining the two congestion indexes, the visual degree of judging the running condition of the road traffic is improved, the running conditions of the intersection to be evaluated and the adjacent intersections are comprehensively considered, the comprehensive degree of grasping all the intersections on the whole road is improved, vehicles about to be converged at the intersection to be evaluated are pre-judged, the predictability of the running condition of the road traffic is improved, the data processing time is greatly reduced, and the traffic running management efficiency is improved.
In the embodiment of the application, the ordinary traffic road conditions can be analyzed, the rules can be summarized, the time factor and the position factor are combined, signal lamp control can be carried out on the road surface in the non-congestion state according to the rules of the ordinary traffic road conditions, and the data processing time is greatly shortened.
The evaluation frequency of the congestion index is adjusted according to the running condition of the road surface, and the situation that the feedback of the traffic congestion state cannot be made due to the fact that the evaluation frequency is too slow in the traffic congestion period or the waste of the running cost of the system due to the fact that the evaluation frequency is too fast in the idle traffic period is avoided. The adaptability to traffic operation conditions in different time periods is enhanced, and the flexibility of system operation is improved.
The traffic regulation and control strategy is adjusted according to the congestion index, the control capacity of the system on the road conditions in the traffic congestion period is improved, the data calculation time and the operation cost in the traffic idle period are reduced, and the flexibility of the system operation and the management efficiency of the traffic operation are integrally improved.
The road condition information and the burst information are pushed to nearby vehicles, a vehicle owner can judge the route planning in advance, the situation that vehicles are gathered in a congested road section and increased to cause vehicle congestion and vehicle congestion is further serious is prevented, and the possibility that vehicles drive in an accident road section to cause secondary accidents is reduced.
The present invention and its embodiments have been described above in an illustrative manner, and the description is not intended to be limiting, and the drawings are only one embodiment of the present invention, and the actual structure is not limited thereto. Therefore, if the person skilled in the art receives the teaching, the technical scheme and the embodiments similar to the technical scheme are not creatively designed without departing from the spirit of the invention, and the invention shall fall into the protection scope of the invention.
Claims (10)
1. A public service traffic management method based on the Internet of things is characterized by comprising the following steps:
step S1, collecting road surface information, collecting road surface image information, and identifying the running state and the position of a road vehicle;
step S2, analyzing road conditions, analyzing the smooth degree or congestion degree of traffic operation according to the running conditions of the road vehicles at each position, and analyzing the change conditions of the running conditions of the road vehicles at each position along with time and position;
and step S3, taking measures, and according to the traffic operation smooth degree or congestion degree analyzed and obtained in the step S2, making evaluation and taking corresponding measures.
2. The internet of things-based public service traffic management method according to claim 1, wherein:
the step S1 includes: s11, recognizing lane directions, namely recognizing the driving directions of all lanes on the road surface by a lane direction recognition module (21) through road surface image information collected by a road surface monitoring module (11); s12, traffic flow statistics, wherein the traffic flow statistics module (22) identifies the number of vehicles in each lane through the road image information collected by the road monitoring module (11); s13, identifying the positions of the signal lamps, combining with the identification of the city map module (12), and identifying the positions of the signal lamps and the types of the nearby buildings by the signal lamp position identification module (23); s14, recognizing sudden accidents, recognizing whether the road surface is blocked due to accidents or not by the accident recognition module (24) through the road surface image information provided by the road surface monitoring module (11), and recognizing the number of the blocked lanes.
3. The internet of things-based public service traffic management method according to claim 2, wherein:
the step S2 includes: s21, analyzing the ordinary road condition, and summarizing the vehicle running rule by analyzing the vehicle running conditions of different positions at different times through the time statistic module (31) and the position judgment module (32); s22, analyzing the current intersection condition, and analyzing the unobstructed degree or the congestion degree of the vehicle running at the current intersection according to the vehicle running condition provided by the information monitoring unit (2); s23, analyzing the conditions of the nearby intersections, namely analyzing the vehicle operating conditions of each intersection nearby the current intersection, namely the quantity of vehicles entering the current intersection and the direction of entering a lane at other intersections, according to the vehicle operating conditions provided by the information monitoring unit (2); and S24, evaluating road conditions, namely, evaluating the traffic conditions of a single intersection and evaluating the related traffic conditions between each intersection according to the vehicle running conditions of the current intersection and the adjacent intersections by a road condition judging module (33).
4. The internet of things-based public service traffic management method according to claim 3, wherein:
in step S2, the method for evaluating the clear degree or the congestion degree of the vehicle running at a single intersection is shown in the following formula:
eta is expressed as a single congestion index of a lane corresponding to a certain phase at the intersection 0, namely the current intersection;
X0the number of vehicles of the corresponding lane of the phase at the intersection 0 is represented;
Y0the maximum number of vehicles allowed to stay in the corresponding lane of the phase at the intersection 0 is represented, and five meters in length is taken as the maximum length of a single vehicle;
X1the total number of vehicles which are converged into the lane in the direction of the No. 0 intersection in all lanes of the No. 1 intersection is represented;
Y1the maximum number of vehicles allowed to stay in the lane converged to the direction of the No. 0 intersection in all lanes of the No. 1 intersection is represented, and the length of five meters is taken as the maximum length of a single vehicle;
Xnthe total number of vehicles converging into lanes in the direction of the n-1 intersection in all lanes of the n-number intersection is represented;
Yn-1the maximum number of vehicles allowed to stay in lanes converging to the direction of the n-2 intersection is expressed in all lanes of the n-1 intersection, and the length of five meters is taken as the maximum length of a single vehicle;
wherein, n intersections are defined as intersections with a distance of one intersection from n-1 intersections, and 0 intersection is the current evaluation intersection;
the set threshold value of the single congestion index is 0.75.
5. The internet of things-based public service traffic management method according to claim 4, wherein:
in step S2, the method for evaluating the correlation between the traffic conditions of a single intersection and other intersections nearby includes:
ε represents the relevant congestion index;
Tnrepresenting the number of intersections with a single congestion index larger than a set threshold in all the n intersections;
the set threshold value of the related congestion index is 0.5.
6. The internet of things-based public service traffic management method according to claim 5, wherein:
the step S3 includes: s31, local signal lamp control; s32, information pushing;
in the step S31, when both the single congestion index and the related congestion index are lower than the set threshold, the signal lamp control module (41) controls the ratio of the time length of each phase of the signal lamp occupying the period to match the analyzed vehicle operation rule according to the vehicle operation rule analyzed in the step S21 and according to different time and different positions; when any one of the single congestion index or the related congestion index is higher than a set threshold, the signal lamp control module (41) controls the proportion of the time length of each phase of the signal lamp in the period time according to the real-time traffic flow so that the time length of each phase of the intersection is matched with the number of vehicles in the corresponding lane of each phase, and the calculation method of the proportion of the time length of each phase in the period time refers to the following formula:
wherein, λ represents the proportion of the time length of a certain phase of the signal lamp to the period time length; etaiA single congestion index expressed as a phase;
in the step S32, when the single congestion index at a certain intersection is higher than the set threshold, the congestion information is pushed to nearby vehicles by the information pushing module (42), and a detour suggestion is proposed; when the accident recognition module (24) monitors that a traffic accident happens to a lane at a certain intersection, if the accident recognition module (24) recognizes that the number of the traffic jam lanes caused by the accident is higher than one half of the total number of the lanes, the information pushing module (42) pushes accident information to nearby vehicles to provide a detour suggestion, and if the accident recognition module (24) recognizes that the number of the traffic jam lanes caused by the accident is lower than one half of the total number of the lanes, the information pushing module (42) pushes the accident information to nearby vehicles to provide a slow-moving suggestion.
7. The internet of things-based public service traffic management method according to claim 5, wherein:
the evaluation frequency of the single congestion index and the related congestion index changes according to time and position, the peak time evaluation frequency is once evaluated for fifteen minutes, the ordinary evaluation frequency is once evaluated for thirty minutes, and the peak time and the ordinary time interval of the position to be evaluated are obtained from the vehicle running rule obtained by analyzing the ordinary road condition in the step S21.
8. An internet-of-things-based public service traffic management system, characterized in that the internet-of-things-based public service traffic management method of any one of claims 1 to 7 is applied:
the public service traffic management system based on the Internet of things comprises: the system comprises a public service platform (1), an information monitoring unit (2), a road condition analysis unit (3) and a traffic regulation and control unit (4);
the public service platform (1) is respectively connected with the information monitoring unit (2), the road condition analysis unit (3) and the traffic regulation and control unit (4) through the Internet of things; the common service platform (1) comprises: the road surface monitoring module (11) is used for acquiring road surface image information; the urban map module (12) is used for importing an urban map model and matching road surface image information; a data storage module (13) for receiving and storing data;
the information monitoring unit (2) is used for identifying the running conditions of vehicles on the road surface of each place in the city by combining the city map module (12) according to the road surface image information provided by the road surface monitoring module (11);
the road condition analysis unit (3) is used for analyzing the traffic smooth degree or congestion degree according to the running condition of the road vehicles at each place identified by the information monitoring unit (2), and analyzing the change condition of the running condition of the road vehicles at each place along with time and position;
the traffic control unit (4) is used for taking corresponding measures according to the result obtained by the road condition analysis unit (3) so as to control road traffic; the traffic control unit (4) comprises: the signal lamp control module (41) is used for receiving the result obtained by the road condition analysis unit (3) and adjusting the time of each phase of the signal lamp; and the information pushing module (42) is used for pushing the road condition information and the burst information to nearby vehicles and judging the route planning in advance.
9. The internet of things-based public service traffic management system according to claim 8, wherein:
the information monitoring unit (2) comprises: the lane direction recognition module (21) is used for recognizing the driving direction of each lane on the road surface according to the road surface image information provided by the road surface monitoring module (11); the traffic flow counting module (22) is used for identifying the driving quantity of each lane according to the road surface image information provided by the road surface monitoring module (11); the signal lamp position identification module (23) is used for identifying the position of each signal lamp and the type of a nearby building in combination with the city map module (12); and the accident identification module (24) is used for identifying whether road surface blockage is caused by accidents on the road surface and the number of blocked lanes according to the road surface image information provided by the road surface monitoring module (11).
10. The internet of things-based public service traffic management system according to claim 8, wherein:
the road condition analysis unit (3) includes: the time counting module (31) is used for matching the vehicle running conditions of the road surface at different times with the time; the position judging module (32) is used for analyzing the vehicle running conditions of all positions at different time in a combined manner according to the types of the buildings at the positions; and the road surface condition judging module (33) is used for judging the smooth degree or the congestion degree of road surface traffic operation so as to send a control instruction to the traffic control unit (4).
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