CN116363891B - Smart city off-network operation method and system based on Internet of vehicles - Google Patents
Smart city off-network operation method and system based on Internet of vehicles Download PDFInfo
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- G—PHYSICS
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- G08G1/00—Traffic control systems for road vehicles
- G08G1/09—Arrangements for giving variable traffic instructions
- G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
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- G08G1/096805—Systems involving transmission of navigation instructions to the vehicle where the transmitted instructions are used to compute a route
- G08G1/096827—Systems involving transmission of navigation instructions to the vehicle where the transmitted instructions are used to compute a route where the route is computed onboard
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/09—Arrangements for giving variable traffic instructions
- G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
- G08G1/0968—Systems involving transmission of navigation instructions to the vehicle
- G08G1/096833—Systems involving transmission of navigation instructions to the vehicle where different aspects are considered when computing the route
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Abstract
The invention discloses a smart city extranet operation method and system based on the Internet of vehicles, relates to the technical field of city extranet operation, and solves the technical problem that in the prior art, passing vehicles cannot be subjected to passing pre-operation, real-time operation and prediction operation in the passing process of city roads; the real-time traffic route is displayed by the vehicle-mounted terminal, the real-time traffic route is subjected to data acquisition and calculation in the passing process by the real-time operation end, the real-time traffic condition of the current traffic route is analyzed, when the traffic condition of the real-time traffic route is congested, the road section where the congested object is located is predicted by the prediction operation end, and the real-time traffic condition of the current road section is predicted by the data acquisition and calculation.
Description
Technical Field
The invention relates to the technical field of urban off-network operation, in particular to a smart urban off-network operation method and system based on the Internet of vehicles.
Background
The internet of vehicles is an interactive network formed by information such as vehicle position, speed, route and the like, the vehicles can complete the collection of self environment and state information through components such as GPS, RFID, sensors, cameras and the like, all vehicles can transmit and gather various information of the vehicles to a central processing unit through an internet technology, and the information of the vehicles can be analyzed and processed through a computer technology so as to calculate the optimal route of different vehicles, report road conditions in time, arrange signal lamp periods and the like;
however, in the prior art, the passing vehicles cannot be subjected to passing pre-operation, real-time operation and prediction operation in the passing process of the urban roads, so that the passing efficiency of the passing vehicles is low, the qualification of urban road planning is influenced, and the performance of data acquisition and calculation of the Internet of vehicles is reduced;
in view of the above technical drawbacks, a solution is now proposed.
Disclosure of Invention
The invention aims to solve the problems and provide a smart city extranet operation method and system based on the Internet of vehicles.
The aim of the invention can be achieved by the following technical scheme: the intelligent city off-network operation system based on the Internet of vehicles comprises an off-network operation center, wherein a pre-operation end, a real-time operation end and a prediction operation end are arranged in the off-network operation center;
marking an automobile covered by the Internet of vehicles as a covered object, setting a reference number i, wherein i is a natural number larger than 1, and dividing the covered object into an object to be travelled, a real-time passing object and a congestion object according to the real-time running state of the covered object;
the method comprises the steps that a pre-operation end analyzes a road route of an object to be travelled, determines an origin and a destination of the object to be travelled, intercepts an internet map according to the origin and the destination, marks the intercepted map as a route planning area, acquires a drivable route of the object to be travelled according to a traffic road in the route planning area, performs data acquisition and calculation on the drivable route, and determines a real-time traffic route through the data acquisition and calculation;
after the real-time traffic route is determined, the real-time traffic object carries out traffic according to the route displayed by the vehicle-mounted terminal, the real-time operation end carries out data acquisition and calculation on the real-time traffic route in the traffic process, analyzes the real-time vehicle condition of the current traffic route, and judges whether the current road section has congestion risk according to the real-time vehicle condition analysis;
when the traffic condition of the real-time traffic route is congested, the prediction operation end predicts the traffic condition of the road section where the congested object is located, predicts the real-time traffic condition of the current road section through data acquisition and calculation, and carries out traveling planning of the congested object according to the prediction result.
As a preferred embodiment of the present invention, the operation procedure of the pre-operation end is as follows:
the method comprises the steps of obtaining the number proportion of right-turn intersections in traffic lights in a drivable path and the frequency of the road sections in the drivable path needing to pass, and comparing the number proportion of right-turn intersections in the traffic lights in the drivable path and the frequency of the road sections in the drivable path needing to pass with a number proportion threshold and a road frequency threshold needing to be changed respectively:
if the number ratio of the right turn intersections in the traffic lights in the drivable path exceeds a number ratio threshold and the frequency of the road sections needing to pass in the drivable path does not exceed a road changing frequency threshold, marking the corresponding drivable path as a preferred path to be passed; otherwise, if the number ratio of the right turn intersections in the traffic lights in the drivable path does not exceed the number ratio threshold, or the frequency of the road sections needing to pass in the drivable path exceeds the road changing frequency threshold, marking the corresponding drivable path as an alternative route to be passed.
As a preferred implementation mode of the invention, real-time road condition analysis is carried out on the route to be passed first, the speed of the vehicle passing through the junction corresponding to the reduced span in the route to be passed first and the speed of the vehicle passing through the junction at the junction set by the traffic light of the route to be passed first are obtained, and the speed of the vehicle passing through the junction corresponding to the reduced span in the route to be passed first and the speed of the vehicle passing through the junction at the junction set by the traffic light of the route to be passed first are respectively compared with a speed reduction span threshold value and a speed reduction speed threshold value;
if the corresponding reduced span of the vehicle passing speed at the junction in the preferred route to be passed exceeds a speed reduced span threshold value or the reduced speed of the lane change passing speed at the junction set by the traffic light of the preferred route to be passed exceeds a speed reduced speed threshold value, the corresponding preferred route to be passed is not used as a real-time passing route; if the corresponding reduced span of the vehicle passing speed at the junction in the preferred route to be passed does not exceed the speed reduced span threshold and the reduced speed of the lane change passing speed at the junction set by the traffic light of the preferred route to be passed does not exceed the speed reduced speed threshold, the corresponding preferred route to be passed is used as a real-time passing route, and the real-time passing route is sent to the vehicle-mounted terminal of the object to be passed through the Internet of vehicles.
As a preferred embodiment of the present invention, the operation process of the real-time operation end is as follows:
monitoring a traffic road section of a current real-time traffic object, acquiring the average traffic speed of each area of the traffic road section, marking the corresponding area as a congestion risk area when the average traffic speed is reduced, acquiring the duration of speed reduction of the congestion risk area in the traffic road section corresponding to the real-time traffic object and the buffer duration of synchronous speed reduction of the area where the real-time traffic object is positioned in the process of speed reduction in the congestion risk area, and marking the duration of speed reduction of the congestion risk area corresponding to the real-time traffic object and the buffer duration of synchronous speed reduction of the area where the real-time traffic object is positioned in the process of speed reduction in the congestion risk area as VJC and HCS respectively; acquiring the quantity increment of vehicles in a corresponding area of the current area of the real-time passing object far from the congestion risk area, and marking the quantity increment of vehicles in the corresponding area of the current area of the real-time passing object far from the congestion risk area as ZJL;
and acquiring a real-time vehicle condition analysis coefficient H of the road section of the real-time passing object through a formula, and comparing the real-time vehicle condition analysis coefficient H of the road section of the real-time passing object with a real-time vehicle condition analysis coefficient threshold value.
As a preferred embodiment of the present invention,wherein, f1, f2 and f3 are preset proportionality coefficients, and f1 > f2 > f3 > 0.
As a preferred embodiment of the present invention, if the real-time vehicle condition analysis coefficient H of the road section of the real-time traffic object exceeds the real-time vehicle condition analysis coefficient threshold, determining that there is a congestion risk in real-time vehicle condition analysis of the road section of the real-time traffic object, generating a congestion high risk signal and transmitting the congestion high risk signal to the vehicle-mounted terminal of the real-time traffic object, and after acquiring the congestion high risk signal, the vehicle-mounted terminal re-programs the road corresponding to the real-time communication object; if the real-time vehicle condition analysis coefficient H of the road section of the real-time passing object does not exceed the real-time vehicle condition analysis coefficient threshold value, judging that the real-time vehicle condition analysis of the road section of the real-time passing object does not have the congestion risk, generating a congestion low-risk signal and sending the congestion low-risk signal to the vehicle-mounted terminal of the real-time passing object.
As a preferred embodiment of the present invention, the operation procedure of the prediction operation end is as follows:
acquiring a congestion area of a road section where a congestion object is located, analyzing the corresponding congestion area, acquiring an increase of the area occupation ratio of a passable area in the congestion area of the road section where the congestion object is located and an increase span of the vehicle passing speed of the passable area in the congestion area, and comparing the increase of the area occupation ratio of the passable area in the road section where the congestion object is located and the increase span of the vehicle passing speed of the passable area in the congestion area with an area occupation ratio increase threshold and a speed increase span threshold respectively;
if the increase of the area ratio of the passable area in the road section congestion area where the congestion object is located exceeds the area ratio increase threshold, or the increase span of the vehicle passing speed of the passable area in the congestion area exceeds the speed increase span threshold, judging that the road section where the congestion object is currently located is subjected to congestion prediction and relief, generating a congestion relief signal and transmitting the congestion relief signal to the vehicle-mounted terminal of the congestion object;
if the increase of the area ratio of the passable area in the road section congestion area where the congestion object is located does not exceed the area ratio increase threshold, and the increase span of the vehicle passing speed in the passable area in the congestion area does not exceed the speed increase span threshold, judging that the current road section congestion prediction where the congestion object is located is aggravated, generating a congestion aggravation signal and sending the congestion aggravation signal to the vehicle-mounted terminal of the congestion object, and after receiving the congestion aggravation signal, re-planning a route for the current congestion object and guiding the next nearest exit to the lane.
The intelligent city off-network operation method based on the Internet of vehicles comprises the following specific steps:
the method comprises the steps of firstly, pre-computing, analyzing a road route of an object to be travelled, monitoring the road condition of the urban road by data acquisition and calculation in the urban road passing process, and planning the route according to the monitoring result of the road condition;
step two, real-time operation is carried out, after route planning is completed, a real-time passing object passes according to a route displayed by the vehicle-mounted terminal, data acquisition calculation is carried out on the real-time passing route in the passing process, real-time vehicle conditions of the current passing route are analyzed, vehicle condition monitoring is carried out on the real-time passing route through the data acquisition calculation, and whether the real-time passing route has congestion risk is judged;
and thirdly, predicting the vehicle condition of the road section where the congestion object is located when the vehicle condition of the real-time traffic route is congested, and predicting the real-time vehicle condition of the current road section through data acquisition and calculation.
Compared with the prior art, the invention has the beneficial effects that:
according to the invention, the pre-operation end analyzes the road route of the object to be traveled, monitors the road condition of the urban road through data acquisition and calculation in the urban road passing process, and performs route planning according to the vehicle condition monitoring result, so that the high efficiency of automobile traveling is improved, the urban road can be reasonably planned while the traveling congestion is avoided, and the overall passing quality of the urban road is improved.
According to the invention, after route planning is completed, a real-time passing object passes through the route displayed by the vehicle-mounted terminal, the real-time operation end performs data acquisition calculation on the real-time passing route in the passing process, the real-time vehicle condition of the current passing route is analyzed, the real-time passing route is monitored through the data acquisition calculation, whether the real-time passing route has a congestion risk is judged, the passing rationality of vehicles is improved through route congestion monitoring, meanwhile, the passing efficiency of roads in an area can be ensured, urban road traffic congestion caused by unreasonable urban road management and control is avoided, and the operation efficiency of the internet of vehicles is reduced.
In the invention, when the traffic condition of the real-time traffic route is congested, the prediction operation end predicts the traffic condition of the road section where the congested object is located, predicts the real-time traffic condition of the current road section by data acquisition and calculation, ensures that the congested object can reasonably match with the road route, prevents the congestion of the road from relieving after the congested object leaves the current route, and thus influences the real-time traffic efficiency of the traffic vehicles.
Drawings
The present invention is further described below with reference to the accompanying drawings for the convenience of understanding by those skilled in the art.
FIG. 1 is a schematic block diagram of a system of the present invention;
fig. 2 is a schematic flow chart of the method of the present invention.
Detailed Description
In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the invention. The appearances of such phrases in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those of skill in the art will explicitly and implicitly appreciate that the embodiments described herein may be combined with other embodiments.
Referring to fig. 1, an off-network computing system of a smart city based on the internet of vehicles comprises an off-network computing center, wherein the off-network computing center is internally provided with a pre-computing end, a real-time computing end and a prediction computing end, and in the process of urban road traffic, the off-network computing center performs real-time data acquisition and calculation on roads and performs operation analysis on urban roads where the internet of vehicles cover objects in different time periods;
marking an automobile covered by the Internet of vehicles as a covered object, setting a reference number i, wherein i is a natural number larger than 1, and dividing the covered object into an object to be travelled, a real-time passing object and a congestion object according to the real-time running state of the covered object;
the pre-operation end analyzes the road route of the object to be travelled, monitors the road condition of the urban road route through data acquisition and calculation in the urban road passing process, and performs route planning according to the monitoring result of the road condition, so that the travelling efficiency of the automobile is improved, the travelling congestion is avoided, the urban road can be reasonably planned, and the overall passing quality of the urban road is improved;
determining an origin and a destination of an object to be travelled, intercepting an internet map according to the origin and the destination, marking the intercepted map as a route planning area, acquiring a drivable route of the object to be travelled according to a road passing through the route planning area, performing data acquisition and calculation on the drivable route, and setting a drivable route as a natural number larger than 1;
the method comprises the steps of obtaining the number proportion of right-turn intersections in traffic lights in a drivable path and the frequency of the road sections in the drivable path needing to pass, and comparing the number proportion of right-turn intersections in the traffic lights in the drivable path and the frequency of the road sections in the drivable path needing to pass with a number proportion threshold and a road frequency threshold needing to be changed respectively:
if the number ratio of the right turn intersections in the traffic lights in the drivable path exceeds a number ratio threshold and the frequency of the road sections needing to pass in the drivable path does not exceed a road changing frequency threshold, marking the corresponding drivable path as a preferred path to be passed; otherwise, if the number ratio of the right turn intersections in the traffic lights in the drivable path does not exceed the number ratio threshold, or the frequency of the road needing to be changed for each road section in the drivable path exceeds the road needing to be changed frequency threshold, marking the corresponding drivable path as an alternative route to be driven;
carrying out real-time road condition analysis on the route to be passed first, obtaining the corresponding reduction span of the vehicle passing speed of the junction in the route to be passed first and the reduction speed of the lane changing passing speed at the junction set by the traffic light of the route to be passed first, and comparing the corresponding reduction span of the vehicle passing speed of the junction in the route to be passed first and the reduction speed of the lane changing passing speed at the junction set by the traffic light of the route to be passed first with a speed reduction span threshold value and a speed reduction speed threshold value respectively:
if the corresponding reduced span of the vehicle passing speed at the junction in the preferred route to be passed exceeds a speed reduced span threshold value or the reduced speed of the lane change passing speed at the junction set by the traffic light of the preferred route to be passed exceeds a speed reduced speed threshold value, the corresponding preferred route to be passed is not used as a real-time passing route; if the corresponding reduced span of the vehicle passing speed at the junction in the preferred route to be passed does not exceed the speed reduced span threshold and the reduced speed of the lane change passing speed at the junction set by the traffic light of the preferred route to be passed does not exceed the speed reduced speed threshold, taking the corresponding preferred route to be passed as a real-time passing route, and sending the real-time passing route to the vehicle-mounted terminal of the object to be passed through the vehicle network;
after the route planning is completed, the real-time traffic object carries out traffic according to the route displayed by the vehicle-mounted terminal, the real-time operation end carries out data acquisition calculation on the real-time traffic route in the traffic process, the real-time vehicle condition of the current traffic route is analyzed, the real-time traffic route is monitored through the data acquisition calculation, whether the real-time traffic route has a congestion risk is judged, the traffic rationality of vehicles is improved through the route congestion monitoring, meanwhile, the traffic efficiency of roads in an area can be ensured, the urban road traffic congestion caused by unreasonable urban road management is avoided, and the operation efficiency of the internet of vehicles is reduced;
monitoring a traffic road section of a current real-time traffic object, acquiring the average traffic speed of each area of the traffic road section, marking the corresponding area as a congestion risk area when the average traffic speed is reduced, acquiring the duration of speed reduction of the congestion risk area in the traffic road section corresponding to the real-time traffic object and the buffer duration of synchronous speed reduction of the area where the real-time traffic object is positioned in the process of speed reduction in the congestion risk area, and marking the duration of speed reduction of the congestion risk area corresponding to the real-time traffic object and the buffer duration of synchronous speed reduction of the area where the real-time traffic object is positioned in the process of speed reduction in the congestion risk area as VJC and HCS respectively; acquiring the quantity increment of vehicles in a corresponding area of the current area of the real-time passing object far from the congestion risk area, and marking the quantity increment of vehicles in the corresponding area of the current area of the real-time passing object far from the congestion risk area as ZJL;
by the formulaAcquiring a real-time traffic condition analysis coefficient H of a road section where a real-time passing object is located, wherein f1, f2 and f3 are preset proportional coefficients, and f1 is more than f2 and more than f3 is more than 0;
comparing a real-time traffic condition analysis coefficient H of a road section where a real-time passing object is located with a real-time traffic condition analysis coefficient threshold value:
if the real-time vehicle condition analysis coefficient H of the road section of the real-time passing object exceeds the real-time vehicle condition analysis coefficient threshold, judging that the real-time vehicle condition analysis of the road section of the real-time passing object has a congestion risk, generating a congestion high risk signal, sending the congestion high risk signal to a vehicle-mounted terminal of the real-time passing object, and re-planning a road corresponding to the real-time communication object after the vehicle-mounted terminal acquires the congestion high risk signal;
if the real-time vehicle condition analysis coefficient H of the road section of the real-time passing object does not exceed the real-time vehicle condition analysis coefficient threshold value, judging that the real-time vehicle condition analysis of the road section of the real-time passing object does not have a congestion risk, generating a congestion low-risk signal and sending the congestion low-risk signal to the vehicle-mounted terminal of the real-time passing object;
when the traffic condition of the real-time traffic route is congested, the prediction operation end predicts the traffic condition of the road section where the congested object is located, predicts the real-time traffic condition of the current road section through data acquisition and calculation, ensures that the congested object can reasonably match with the road route, prevents the congestion of the road from relieving after the congested object leaves the current route, and thus influences the real-time traffic efficiency of the traffic vehicles;
the method comprises the steps of obtaining a congestion area of a road section where a congestion object is located, analyzing a corresponding congestion area, obtaining an increase of the area occupation ratio of a passable area in the congestion area of the road section where the congestion object is located and an increase span of the vehicle passing speed of the passable area in the congestion area, and comparing the increase of the area occupation ratio of the passable area in the road section where the congestion object is located and the increase span of the vehicle passing speed of the passable area in the congestion area with an area occupation ratio increase threshold and a speed increase span threshold respectively:
if the increase of the area ratio of the passable area in the road section congestion area where the congestion object is located exceeds the area ratio increase threshold, or the increase span of the vehicle passing speed of the passable area in the congestion area exceeds the speed increase span threshold, judging that the road section where the congestion object is currently located is subjected to congestion prediction and relief, generating a congestion relief signal and transmitting the congestion relief signal to the vehicle-mounted terminal of the congestion object;
if the increase of the area ratio of the passable area in the road section congestion area where the congestion object is located does not exceed the area ratio increase threshold, and the increase span of the vehicle passing speed in the passable area in the congestion area does not exceed the speed increase span threshold, judging that the current road section congestion prediction where the congestion object is located is aggravated, generating a congestion aggravation signal and sending the congestion aggravation signal to the vehicle-mounted terminal of the congestion object, and after receiving the congestion aggravation signal, re-planning a route for the current congestion object and guiding the next nearest exit to the lane.
Referring to fig. 2, the method for calculating the smart city outside network based on the internet of vehicles specifically comprises the following steps:
the method comprises the steps of firstly, pre-computing, analyzing a road route of an object to be travelled, monitoring the road condition of the urban road by data acquisition and calculation in the urban road passing process, and planning the route according to the monitoring result of the road condition;
step two, real-time operation is carried out, after route planning is completed, a real-time passing object passes according to a route displayed by the vehicle-mounted terminal, data acquisition calculation is carried out on the real-time passing route in the passing process, real-time vehicle conditions of the current passing route are analyzed, vehicle condition monitoring is carried out on the real-time passing route through the data acquisition calculation, and whether the real-time passing route has congestion risk is judged;
and thirdly, predicting the vehicle condition of the road section where the congestion object is located when the vehicle condition of the real-time traffic route is congested, and predicting the real-time vehicle condition of the current road section through data acquisition and calculation.
When the method is used, a pre-operation end analyzes a road route of an object to be travelled, determines an origin and a destination of the object to be travelled, intercepts an internet map according to the origin and the destination, marks the intercepted map as a route planning area, acquires a drivable route of the object to be travelled according to a traffic road in the route planning area, performs data acquisition and calculation on the drivable route, and determines a real-time traffic route through the data acquisition and calculation; after the real-time traffic route is determined, the real-time traffic object carries out traffic according to the route displayed by the vehicle-mounted terminal, the real-time operation end carries out data acquisition and calculation on the real-time traffic route in the traffic process, analyzes the real-time vehicle condition of the current traffic route, and judges whether the current road section has congestion risk according to the real-time vehicle condition analysis; when the traffic condition of the real-time traffic route is congested, the prediction operation end predicts the traffic condition of the road section where the congested object is located, predicts the real-time traffic condition of the current road section through data acquisition and calculation, and carries out traveling planning of the congested object according to a prediction structure.
The formulas are all formulas obtained by collecting a large amount of data for software simulation and selecting a formula close to a true value, and coefficients in the formulas are set by a person skilled in the art according to actual conditions; the preferred embodiments of the invention disclosed above are intended only to assist in the explanation of the invention. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise form disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best understand and utilize the invention. The invention is limited only by the claims and the full scope and equivalents thereof.
Claims (5)
1. The intelligent city off-network operation system based on the Internet of vehicles is characterized by comprising an off-network operation center, wherein a pre-operation end, a real-time operation end and a prediction operation end are arranged in the off-network operation center;
marking an automobile covered by the Internet of vehicles as a covered object, setting a reference number i, wherein i is a natural number larger than 1, and dividing the covered object into an object to be travelled, a real-time passing object and a congestion object according to the real-time running state of the covered object;
the method comprises the steps that a pre-operation end analyzes a road route of an object to be travelled, determines an origin and a destination of the object to be travelled, intercepts an internet map according to the origin and the destination, marks the intercepted map as a route planning area, acquires a drivable route of the object to be travelled according to a traffic road in the route planning area, performs data acquisition and calculation on the drivable route, and determines a real-time traffic route through the data acquisition and calculation;
after the real-time traffic route is determined, the real-time traffic object carries out traffic according to the route displayed by the vehicle-mounted terminal, the real-time operation end carries out data acquisition and calculation on the real-time traffic route in the traffic process, analyzes the real-time vehicle condition of the current traffic route, and judges whether the current road section has congestion risk according to the real-time vehicle condition analysis;
when the traffic condition of the real-time traffic route is congested, the prediction operation end predicts the traffic condition of the road section where the congested object is located, predicts the real-time traffic condition of the current road section through data acquisition and calculation, and carries out traveling planning of the congested object according to the prediction result;
the operation process of the real-time operation end is as follows:
monitoring a traffic road section of a current real-time traffic object, acquiring the average traffic speed of each area of the traffic road section, marking the corresponding area as a congestion risk area when the average traffic speed is reduced, acquiring the duration of speed reduction of the congestion risk area in the traffic road section corresponding to the real-time traffic object and the buffer duration of synchronous speed reduction of the area where the real-time traffic object is positioned in the process of speed reduction in the congestion risk area, and marking the duration of speed reduction of the congestion risk area corresponding to the real-time traffic object and the buffer duration of synchronous speed reduction of the area where the real-time traffic object is positioned in the process of speed reduction in the congestion risk area as VJC and HCS respectively; acquiring the quantity increment of vehicles in a corresponding area of the current area of the real-time passing object far from the congestion risk area, and marking the quantity increment of vehicles in the corresponding area of the current area of the real-time passing object far from the congestion risk area as ZJL;
by the formulaAcquiring a real-time vehicle condition analysis coefficient H of a road section where a real-time passing object is located, wherein f1, f2 and f3 are preset proportionality coefficients, and f1 > f2 > f3 > 0 compares the real-time vehicle condition analysis coefficient H of the road section where the real-time passing object is located with a real-time vehicle condition analysis coefficient threshold value:
if the real-time vehicle condition analysis coefficient H of the road section of the real-time passing object exceeds the real-time vehicle condition analysis coefficient threshold, judging that the real-time vehicle condition analysis of the road section of the real-time passing object has a congestion risk, generating a congestion high risk signal, sending the congestion high risk signal to a vehicle-mounted terminal of the real-time passing object, and re-planning a road corresponding to the real-time communication object after the vehicle-mounted terminal acquires the congestion high risk signal; if the real-time vehicle condition analysis coefficient H of the road section of the real-time passing object does not exceed the real-time vehicle condition analysis coefficient threshold value, judging that the real-time vehicle condition analysis of the road section of the real-time passing object does not have the congestion risk, generating a congestion low-risk signal and sending the congestion low-risk signal to the vehicle-mounted terminal of the real-time passing object.
2. The intelligent city extranet operation system based on the internet of vehicles according to claim 1, wherein the operation process of the pre-operation end is as follows:
the method comprises the steps of obtaining the number ratio of right-turn intersections in traffic lights in a drivable path and the frequency of the road sections in the drivable path needing to pass, and comparing the number ratio of the right-turn intersections in the traffic lights in the drivable path and the frequency of the road sections in the drivable path needing to pass with a number ratio threshold and a road frequency threshold needing to be changed respectively;
if the number ratio of the right turn intersections in the traffic lights in the drivable path exceeds a number ratio threshold and the frequency of the road sections needing to pass in the drivable path does not exceed a road changing frequency threshold, marking the corresponding drivable path as a preferred path to be passed; otherwise, if the number ratio of the right turn intersections in the traffic lights in the drivable path does not exceed the number ratio threshold, or the frequency of the road sections needing to pass in the drivable path exceeds the road changing frequency threshold, marking the corresponding drivable path as an alternative route to be passed.
3. The internet-of-vehicles-based intelligent urban off-network computing system according to claim 2, wherein real-time road condition analysis is performed on the route to be travelled first, the corresponding reduced span of the traffic speed of the junction in the route to be travelled first and the reduced speed of the lane change traffic speed at the junction set by the traffic light of the route to be travelled first are obtained, and the corresponding reduced span of the traffic speed of the junction in the route to be travelled first and the reduced speed of the lane change traffic speed at the junction set by the traffic light of the route to be travelled first are compared with a speed reduced span threshold and a speed reduced speed threshold respectively;
if the corresponding reduced span of the vehicle passing speed at the junction in the preferred route to be passed exceeds a speed reduced span threshold value or the reduced speed of the lane change passing speed at the junction set by the traffic light of the preferred route to be passed exceeds a speed reduced speed threshold value, the corresponding preferred route to be passed is not used as a real-time passing route; if the corresponding reduced span of the vehicle passing speed at the junction in the preferred route to be passed does not exceed the speed reduced span threshold and the reduced speed of the lane change passing speed at the junction set by the traffic light of the preferred route to be passed does not exceed the speed reduced speed threshold, the corresponding preferred route to be passed is used as a real-time passing route, and the real-time passing route is sent to the vehicle-mounted terminal of the object to be passed through the Internet of vehicles.
4. The intelligent urban off-network computing system based on the internet of vehicles according to claim 1, wherein the operation process of the prediction computing terminal is as follows:
acquiring a congestion area of a road section where a congestion object is located, analyzing the corresponding congestion area, acquiring an increase of the area occupation ratio of a passable area in the congestion area of the road section where the congestion object is located and an increase span of the vehicle passing speed of the passable area in the congestion area, and comparing the increase of the area occupation ratio of the passable area in the road section where the congestion object is located and the increase span of the vehicle passing speed of the passable area in the congestion area with an area occupation ratio increase threshold and a speed increase span threshold respectively;
if the increase of the area ratio of the passable area in the road section congestion area where the congestion object is located exceeds the area ratio increase threshold, or the increase span of the vehicle passing speed of the passable area in the congestion area exceeds the speed increase span threshold, judging that the road section where the congestion object is currently located is subjected to congestion prediction and relief, generating a congestion relief signal and transmitting the congestion relief signal to the vehicle-mounted terminal of the congestion object;
if the increase of the area ratio of the passable area in the road section congestion area where the congestion object is located does not exceed the area ratio increase threshold, and the increase span of the vehicle passing speed in the passable area in the congestion area does not exceed the speed increase span threshold, judging that the current road section congestion prediction where the congestion object is located is aggravated, generating a congestion aggravation signal and sending the congestion aggravation signal to the vehicle-mounted terminal of the congestion object, and after receiving the congestion aggravation signal, re-planning a route for the current congestion object and guiding the next nearest exit to the lane.
5. The intelligent city off-network operation method based on the Internet of vehicles is characterized by comprising the following specific steps of:
the method comprises the steps of firstly, pre-computing, analyzing a road route of an object to be travelled, monitoring the road condition of the urban road by data acquisition and calculation in the urban road passing process, and planning the route according to the monitoring result of the road condition;
step two, real-time operation is carried out, after route planning is completed, a real-time passing object passes according to a route displayed by the vehicle-mounted terminal, data acquisition calculation is carried out on the real-time passing route in the passing process, real-time vehicle conditions of the current passing route are analyzed, vehicle condition monitoring is carried out on the real-time passing route through the data acquisition calculation, and whether the real-time passing route has congestion risk is judged;
monitoring a traffic road section of a current real-time traffic object, acquiring the average traffic speed of each area of the traffic road section, marking the corresponding area as a congestion risk area when the average traffic speed is reduced, acquiring the duration of speed reduction of the congestion risk area in the traffic road section corresponding to the real-time traffic object and the buffer duration of synchronous speed reduction of the area where the real-time traffic object is positioned in the process of speed reduction in the congestion risk area, and marking the duration of speed reduction of the congestion risk area corresponding to the real-time traffic object and the buffer duration of synchronous speed reduction of the area where the real-time traffic object is positioned in the process of speed reduction in the congestion risk area as VJC and HCS respectively; acquiring the quantity increment of vehicles in a corresponding area of the current area of the real-time passing object far from the congestion risk area, and marking the quantity increment of vehicles in the corresponding area of the current area of the real-time passing object far from the congestion risk area as ZJL;
by the formulaAcquiring a real-time traffic condition analysis coefficient H of a road section where a real-time passing object is located, wherein f1, f2 and f3 are preset proportional coefficients, and f1 is more than f2 and more than f3 is more than 0;
comparing a real-time traffic condition analysis coefficient H of a road section where a real-time passing object is located with a real-time traffic condition analysis coefficient threshold value:
if the real-time vehicle condition analysis coefficient H of the road section of the real-time passing object exceeds the real-time vehicle condition analysis coefficient threshold, judging that the real-time vehicle condition analysis of the road section of the real-time passing object has a congestion risk, generating a congestion high risk signal, sending the congestion high risk signal to a vehicle-mounted terminal of the real-time passing object, and re-planning a road corresponding to the real-time communication object after the vehicle-mounted terminal acquires the congestion high risk signal;
if the real-time vehicle condition analysis coefficient H of the road section of the real-time passing object does not exceed the real-time vehicle condition analysis coefficient threshold value, judging that the real-time vehicle condition analysis of the road section of the real-time passing object does not have a congestion risk, generating a congestion low-risk signal and sending the congestion low-risk signal to the vehicle-mounted terminal of the real-time passing object;
and thirdly, predicting the vehicle condition of the road section where the congestion object is located when the vehicle condition of the real-time traffic route is congested, and predicting the real-time vehicle condition of the current road section through data acquisition and calculation.
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