CN116704788A - Vehicle-road cooperation method and system based on edge calculation - Google Patents
Vehicle-road cooperation method and system based on edge calculation Download PDFInfo
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Abstract
The invention provides a vehicle-road cooperation method based on edge calculation, which comprises the following steps: acquiring an urban traffic network map, and acquiring road section information through a sensor; calculating the road combination coefficient of each intersection through an edge calculation node according to the road section information; calculating the road junction road combination weight according to the road junction road combination coefficients of all the road junctions; the system used by the method comprises a road section information acquisition module, a road combination coefficient calculation module, a road combination weight control module and a control module, the traffic flow change condition can be accurately mastered in real time by the method and the system, and the time of the traffic lamp is controlled according to the road combination coefficient and the road combination weight, so that the traffic lamp is more suitable for actual traffic demands, and the traffic running efficiency and safety are improved; the main power supply circuit and the standby power supply are connected with the traffic light, so that the power supply stability of the traffic light can be effectively ensured, the power waste is reduced, and the energy utilization rate is improved.
Description
Technical Field
The invention relates to the technical field of vehicle-road cooperation, in particular to a vehicle-road cooperation method and system based on edge calculation.
Background
With the development of wireless communication, unmanned vehicles are capable of achieving communication connection and information interaction between vehicles, vehicles and infrastructure, etc. using Dedicated Short Range Communication (DSRC) technology. The unmanned vehicles connected with each other through wireless communication can reduce most collision accidents of a traffic system, reduce traffic delay, greatly improve traffic management efficiency and provide functions of information entertainment, remote information processing and the like. Interconnected unmanned vehicles are therefore of great potential for improving traffic system management and their advantages make them one of the current research hotspots in the field of internet of vehicles. The traditional traffic light dispatching method for managing the traffic intersections at present is realized in such a way that part of the intersections are opened at fixed time intervals to allow vehicles to pass through, and vehicles at other intersections are stopped and waited. The traditional traffic light dispatching method can adjust the traffic flow of the crossing to a certain extent, but has the following defects: the traffic flow cannot be flexibly and intelligently adapted; lack of a communication cooperative function with the unmanned vehicle; the problem of traffic jam and safety caused by the increase of the traffic flow cannot be solved; it is difficult to improve throughput and traffic management efficiency of the entire traffic system, and at the same time, control of traffic lights cannot be accurately provided when a sudden power system failure occurs.
Disclosure of Invention
The invention provides a vehicle-road cooperation method based on edge calculation, which is used for solving the problems of traffic jam and safety caused by the increase of vehicle flow, improving the passing efficiency and ensuring normal peer when a sudden power system fails.
The invention provides a vehicle-road cooperation method based on edge calculation, which comprises the following steps:
s1, acquiring urban traffic network information through a map, acquiring road information through the urban traffic network information, and classifying roads according to areas; installing acquisition equipment at an intersection according to traffic network information, and acquiring road section traffic information through the acquisition equipment;
s2, transmitting the road section traffic information acquired by the acquisition equipment to an edge calculation node, dividing each traffic intersection according to the driving directions, and calculating road combination coefficients of different driving directions of each intersection through the edge calculation node;
s3, calculating the road combination weight of the intersections according to the road combination coefficients of the intersections in different driving directions and the road information;
s4, controlling traffic lights according to the road combination weight of the intersection, and selecting and starting a standby power supply system under the abnormal power failure condition; the abnormal power failure includes line damage and line overhaul.
Further, a method for fusion perception based on vehicle-road cooperation comprises the following steps:
s11, acquiring urban traffic network information through a map, acquiring road information through the traffic information, and classifying roads according to areas; the road information comprises lane widths and lane numbers of all directions of the traffic intersection; the area may be a power plant power coverage area, administrative area;
s12, arranging traffic lights and acquisition equipment at a traffic intersection; the traffic light and the acquisition equipment are connected with a main power supply line and a standby power supply;
s13, collecting road section traffic information through collecting equipment; the road section traffic information comprises the number of vehicles passing through the traffic intersection, the speed of the vehicles, the number of pedestrians and the time for collecting information by the collecting equipment; the acquisition equipment comprises a road side sensor and a vehicle end sensor.
Further, a method for fusion perception based on vehicle-road cooperation comprises the following steps:
setting an edge computing node; processing the traffic intersection information by using an edge computing node; comprising the following steps:
according to a preset time period, calculating the number of vehicles, the speed of the vehicles and the number of pedestrians in the same direction at the same intersection;
calculating road combination coefficient lambda of the same direction in the preset time period of the same intersection rk 。
Further, a method for fusion perception based on vehicle-road cooperation, which calculates the same intersection according to a preset time period,
the number of vehicles, the speed of the vehicles and the number of pedestrians in the same direction; wherein:
the number of sampling times in preset time is n, the number of passing vehicles at each sampling point of green light in the same direction of the same road at each intersection is Cij, and the number of passing pedestrians is Pij; vehicle average speed is Vij; time Jj when no pedestrian or vehicle is passing; i=1, 2,3 … n.
The road combination coefficient of the same intersection in the same direction in the preset time period is calculated, and the road combination coefficient is specifically as follows:
λ 1k ,λ 2k …λ xk the traffic coefficients are r traffic coefficients in different directions at the same intersection; g, the total green light duration in the preset time,n is the sampling times in a preset time; j=1, 2,3 … m, m being the number of days of one statistical period; preferably 30 days; alpha is a dynamic adjustment factor;
when 80% of Cmin is less than or equal to C ij+1 Alpha=1 when 1.2×cmax is not more than; c (C) ij+1 The current traffic flow of the intersection in the direction; cmax is the maximum traffic flow in the same time period before the same direction of the intersection in a statistical period; cmin is the minimum traffic flow in the same time period before the same time period of this direction of the intersection;
when C ij+1 >1.2 XCmax or C ij+1 <At the time of 80% x Cmin,
further, a method for fusion perception based on vehicle-road cooperation comprises the following steps:
determining the road combination weight of each driving direction of the traffic intersection according to the road combination coefficient;
lane width W and number Nw of lanes in each direction of the traffic intersection; ln is the natural logarithm of the base e;
determining the total road combination weight of the intersection according to the weight settings of different directions of the same intersection;
Z k ＝max(Z 1k ,Z 1k …Z rk )+avg(Z 1k ,Z 1k …Z rk )。
further, a method for fusion perception based on vehicle-road cooperation comprises the following steps:
z in the region k Ordering from high to low; calculating the average avg (Z) k )；
If Z k >avg(Z k ) The method comprises the steps of carrying out a first treatment on the surface of the The green light of the intersection is in the time period of the traffic light T in the direction A and the direction opposite to the direction A k ＝(1+10％×avg(Z 1k ,Z 1k …Z rk )/max(Z 11 ,Z 12 ))×T；
If Z k <avg(Z k ) The method comprises the steps of carrying out a first treatment on the surface of the The green light time length T of the green light of the intersection in the direction A and the green light time length T of the green light in the direction opposite to the direction A k ＝(1-10％×avg(Z 1k ,Z 1k …Z rk )/max(Z 11 ,Z 12 ))×T；Z 11 ,Z 12 Weights in the direction A and the direction opposite to the direction A;
wherein; the green light calibration time length is T each time;
at least Z when abnormal power failure of area is encountered k >(1+10％)avg(Z k ) Is powered by the intersection-enabled backup power supply.
The invention provides a system for fusion perception based on vehicle-road cooperation, which comprises:
the road section information acquisition module: acquiring urban traffic network information through a map, acquiring road information through the urban traffic network information, and classifying roads according to areas; installing acquisition equipment at an intersection according to traffic network information, and acquiring road section traffic information through the acquisition equipment;
and a road combination coefficient calculation module: transmitting the road section traffic information acquired by the acquisition equipment to an edge computing node, dividing each traffic intersection according to the driving directions, and computing road combination coefficients of different driving directions of each intersection through the edge computing node;
and the road combination weight control module is used for: calculating road combination weight of the intersections according to road combination coefficients of the intersections in different driving directions and the road information;
and the control module is used for: controlling traffic lights according to the road combination weight of the intersection, and selecting to start a standby power supply system under the abnormal power failure condition; the abnormal power failure includes line damage and line overhaul.
The invention has the beneficial effects that: the vehicle-road collaborative fusion perception method based on edge calculation can accurately grasp traffic flow change conditions in real time by acquiring urban traffic network maps and road section information by sensors, and control the time of traffic lights according to road combination coefficients and road combination weights so as to be more suitable for actual traffic demands, thereby improving traffic running efficiency and safety; by acquiring the road section information in real time, traffic signals can be timely adjusted according to the change condition of traffic flow, traffic capacity of the intersection is optimized, and congestion is reduced; by calculating the road combination coefficient and the road combination weight, the time of the traffic light can be adjusted according to actual conditions, the traffic efficiency of the road is improved, and the travel time of the traffic is shortened; by controlling the time of the traffic light, traffic accidents can be reduced, and the safety of traffic operation is improved; in general, the scheme can control the time of the traffic light by acquiring the road section information and calculating the road junction road combination coefficient in real time, so that the traffic light is more suitable for actual traffic demands, and the efficiency and the safety of traffic operation are improved.
Drawings
FIG. 1 is a schematic diagram of a vehicle-road collaborative fusion perception method based on edge calculation according to the present invention;
fig. 2 is a schematic diagram of a vehicle-road collaborative fusion perception system based on edge calculation.
Detailed Description
The preferred embodiments of the present invention will be described below with reference to the accompanying drawings, it being understood that the preferred embodiments described herein are for illustration and explanation of the present invention only, and are not intended to limit the present invention.
The embodiment relates to a vehicle-road cooperation method based on edge calculation, which comprises the following steps:
s1, acquiring urban traffic network information through a map, acquiring road information through the urban traffic network information, and classifying roads according to areas; installing acquisition equipment at an intersection according to traffic network information, and acquiring road section traffic information through the acquisition equipment;
s2, transmitting the road section traffic information acquired by the acquisition equipment to an edge calculation node, dividing each traffic intersection according to the driving directions, and calculating road combination coefficients of different driving directions of each intersection through the edge calculation node;
s3, calculating the road combination weight of the intersections according to the road combination coefficients of the intersections in different driving directions and the road information;
s4, controlling traffic lights according to the road combination weight of the intersection, and selecting and starting a standby power supply system under the abnormal power failure condition; the abnormal power failure includes line damage and line overhaul.
The working principle and the effect of the technical scheme are as follows: the road section information is acquired by acquiring the urban traffic network map and the sensor, so that the traffic flow change condition can be accurately mastered in real time, and the time of the traffic light is controlled according to the road combination coefficient and the road combination weight, so that the traffic light is more suitable for actual traffic demands, and the traffic running efficiency and safety are improved; by acquiring the road section information in real time, traffic signals can be timely adjusted according to the change condition of traffic flow, traffic capacity of the intersection is optimized, and congestion is reduced; by calculating the road combination coefficient and the road combination weight, the time of the traffic light can be adjusted according to actual conditions, the traffic efficiency of the road is improved, and the travel time of the traffic is shortened; by controlling the time of the traffic light, traffic accidents can be reduced, and the safety of traffic operation is improved; in general, the scheme can control the time of the traffic light by acquiring the road section information and calculating the road junction road combination coefficient in real time, so that the traffic light is more suitable for actual traffic demands, and the efficiency and the safety of traffic operation are improved.
The method for fusion perception based on vehicle-road cooperation comprises the following steps:
s11, acquiring urban traffic network information through a map, acquiring road information through the traffic information, and classifying roads according to areas; the road information comprises lane widths and lane numbers of all directions of the traffic intersection; the area may be a power plant power coverage area, administrative area;
s12, arranging traffic lights and acquisition equipment at a traffic intersection; the traffic light and the acquisition equipment are connected with a main power supply line and a standby power supply;
s13, collecting road section traffic information through collecting equipment; the road section traffic information comprises the number of vehicles passing through the traffic intersection, the speed of the vehicles, the number of pedestrians and the time for collecting information by the collecting equipment; the acquisition equipment comprises a road side sensor and a vehicle end sensor.
The working principle and the effect of the technical scheme are as follows: the urban traffic network map is obtained, roads are classified according to areas, traffic conditions of each area can be mastered better, traffic lights are distributed more accurately, traffic intersection information is collected through the collecting equipment, traffic conditions can be mastered in real time, and the time length and the interval time of traffic signals can be adjusted according to actual conditions, so that the urban traffic network map is more suitable for actual traffic demands, and therefore traffic running efficiency and traffic running safety are improved. Traffic can be effectively coordinated with traffic flow and pedestrian flow by arranging traffic lights, traffic pressure is relieved, and traffic efficiency of intersections is improved. The traffic intersection information is collected in real time, and the time length and the interval time of traffic signals are adjusted according to actual conditions, so that traffic accidents can be reduced, and the safety of traffic operation is improved; the main power supply circuit and the standby power supply are connected with the traffic light, so that the power supply stability of the traffic light can be effectively ensured, the power waste is reduced, and the energy utilization rate is improved.
In general, the scheme is used for acquiring the urban traffic network map, classifying according to the region, distributing traffic lights, and collecting traffic intersection information in real time through the collecting equipment to control the time and interval of traffic signals, so that the traffic signals are more suitable for actual traffic demands, and the traffic running efficiency and safety are improved.
The method for fusion perception based on vehicle-road cooperation comprises the following steps:
setting an edge computing node; processing the traffic intersection information by using an edge computing node; comprising the following steps:
according to a preset time period, calculating the number of vehicles, the speed of the vehicles and the number of pedestrians in the same direction at the same intersection; the preset time period is from 7 to 9 points in the morning of rush hours, is from 5 to 7 points in the afternoon every 10 minutes, is from a preset time period every ten minutes, and is from a preset time period every half hour in the rest time;
calculating road combination coefficient lambda of the same direction in the preset time period of the same intersection rk 。
The working principle and the effect of the technical scheme are as follows: the traffic intersection information is processed by setting the edge computing nodes, and the number of vehicles, the speed of the vehicles and the number of pedestrians are computed according to the preset time period, so that the traffic condition can be mastered more accurately, because the intersection possibly has rush hours of going up and going down, the traffic flow of different time periods is different, different time periods are set, and the time periods are divided more finely in the rush hours, so that the sampling result is more accurate; therefore, the optimal control of traffic signals is realized in the vehicle-road coordination, and the efficiency and the safety of traffic operation are improved. By calculating the number of vehicles, the speed of the vehicles and the number of pedestrians at the same intersection and in the same direction and calculating the road combination coefficient, the traffic condition can be mastered more accurately, so that the traffic signals are optimally controlled in the cooperation of the vehicles and the roads, and the traffic running efficiency is improved; by monitoring traffic conditions in real time and optimally controlling traffic signals, traffic accidents can be reduced, and traffic operation safety is improved; in general, the scheme processes traffic intersection information by setting the edge computing nodes, calculates the number of vehicles, the speed of the vehicles, the number of pedestrians and the road combination coefficient, can more accurately grasp traffic conditions, and realizes the optimal control of traffic signals in the cooperation of the vehicles and the roads, thereby improving the efficiency and the safety of traffic operation.
According to the fusion perception method based on the vehicle-road cooperation, the number of vehicles, the speed of the vehicles and the number of pedestrians in the same direction at the same intersection are calculated according to a preset time period; wherein:
the number of sampling times in preset time is n, the number of passing vehicles at each sampling point of green light in the same direction of the same road at each intersection is Cij, and the number of passing pedestrians is Pij; vehicle average speed is Vij; time Jj when no pedestrian or vehicle is passing; i=1, 2,3 … n.
Calculating road combination coefficient lambda of the same direction in the preset time period of the same intersection rk The method specifically comprises the following steps:
λ 1k ,λ 2k …λ rk for the traffic coefficients of r different directions at the same intersection, for example, if one intersection is an intersection, there are four driving directions r=4; g, the total green light duration in the preset time, n is the sampling times in a preset time; j=1, 2,3 … m, m being the number of days of one statistical period; preferably 30 days; alpha is a dynamic adjustment factor;
when 80% of Cmin is less than or equal to C ij+1 Alpha=1 when 1.2×cmax is not more than; c (C) ij+1 The current traffic flow of the intersection in the direction; cmax is the maximum traffic flow in the same time period before the same direction of the intersection in a statistical period; cmin is the minimum traffic flow in the same time period before the same time period of this direction of the intersection;
when C ij+1 >1.2 XCmax or C ij+1 <At the time of 80% x Cmin,
the working principle of the technical scheme is as follows: the traffic flow in the same direction and the same time period at the same intersection is used, the average speed of the traffic flow and the vehicle is the average value of the time when no pedestrian or vehicle passes through, a statistical period is set, the traffic information in the same time period at the same intersection is monitored, and the road combination coefficient lambda in the same direction at the same intersection is calculated through a formula rk The road combination coefficient of the road is one of very important indexes in traffic planning, design and management, and reflects the characteristics of traffic flow and the traffic capacity of road sections; the formula adopts the parameters of passing vehicle number, passing pedestrian number, average speed of vehicles and the like to calculate, and the ratio of time without pedestrians and vehicles to green light time, and dynamically adjusts alpha factors according to actual conditions, so that the influence of traffic flow change on road combination coefficients is reflected more accurately, and the accuracy and efficiency of traffic planning are improved; by sampling and counting the same intersection in the same direction and combining a plurality of factors such as traffic flow, pedestrian quantity, average speed of vehicles, green time and the like, a relatively accurate road combination coefficient can be obtained, real-time change of traffic conditions is reflected, and the situation of the current intersection can be better reflected by considering sudden conditions of the intersection, such as road repair, for example, the increase of traffic flow of special activities, the comparison of the traffic flow with the highest and lowest traffic flows in the previous statistical period, judging whether the special situation exists or not, if not, the dynamic adjustment factor is 1, and if so, the ratio of the current traffic flow to the average value in the previous statistical period is used as the dynamic adjustment factor; the formula comprehensively considers various factors such as the passing number of vehicles, the passing number of pedestrians, the speed of vehicles and the like, and can accurately reflect the traffic flow condition. The formula can be used for statistical analysis of actual data and simulation calculation in traffic planning.
The method for fusion perception based on vehicle-road cooperation comprises the following steps:
determining the road combination weight of each driving direction of the traffic intersection according to the road combination coefficient;
each of traffic intersectionsLane width W and number of lanes Nw in each direction; ln is the natural logarithm of the base e;
determining the total road combination weight of the intersection according to the weight settings of different directions of the same intersection;
Z k ＝max(Z 1k ,Z 1k …Z rk )+avg(Z 1k ,Z 1k …Z rk )。
the working principle and the effect of the technical scheme are as follows: the road combination weights of all the driving directions are determined by counting the lane widths, the lane numbers and the like of the traffic crossing in different driving directions and combining with comprehensive evaluation of the road combination coefficients, so that the traffic jam conditions of the different directions are reflected more accurately, and the situation that the weight setting is too subjective or unreasonable can be avoided. The total road combination weight of the intersection, such as an intersection, has a main road and a minor road, is obtained by carrying out the combined calculation of the maximum value and the average value on the road combination weights in different directions, if only the average value is considered, the weight in the main road direction is unbalanced, and if only the maximum value is considered, the weight in the minor road direction is lower, and no method is considered, so the combined calculation of the maximum value and the average value is selected, the traffic condition of the intersection is more comprehensively mastered, and the traffic control purely according to the weight in a certain direction is avoided, so that the other directions are blocked. By defining the road combination weight and the total road combination weight of each driving direction of the intersection, the control strategy of the signal lamp can be set more accurately, so that traffic jam is reduced, and traffic efficiency and safety are improved. The weight distribution is carried out according to the actual situation by the formula, the traffic condition is comprehensively considered, the traffic signal control is optimized, the traffic condition of the intersection can be reflected more accurately, and the efficiency and the safety of traffic operation are fundamentally improved.
The method for fusion perception based on vehicle-road cooperation comprises the following steps:
z in the region k Ordering from high to low; calculating the average avg (Z) k )；
If Z k >avg(Z k ) The method comprises the steps of carrying out a first treatment on the surface of the Then this wayTraffic lights T in direction A and opposite to direction A during this period k ＝(1+10％×avg(Z 1k ,Z 1k …Z rk )/max(Z 11 ,Z 12 ))×T；
If Z k <avg(Z k ) The method comprises the steps of carrying out a first treatment on the surface of the The green light time length T of the green light of the intersection in the direction A and the green light time length T of the green light in the direction opposite to the direction A k ＝(1-10％×avg(Z 1k ,Z 1k …Z rk )/max(Z 11 ,Z 12 ))×T；Z 11 ,Z 12 Weights in the direction A and the direction opposite to the direction A;
wherein; the green light calibration time length is T each time;
at least Z when abnormal power failure of area is encountered k >(1+10％)avg(Z k ) The emergency power supply started at the crossing is used for supplying power, and the abnormal power failure comprises line faults and line overhauls.
The working principle and the effect of the technical scheme are as follows: the weight and the average weight of each traffic intersection in the area are calculated in real time, and the green light duration is dynamically adjusted according to the current traffic condition, so that the traffic condition can be reflected more accurately, the traffic jam is reduced, and the traffic efficiency is improved; through fine green light duration adjustment, green light duration can be fully utilized, the situation that congestion occurs in other directions due to long waiting in a certain direction is avoided, and accordingly traffic smoothness and safety are improved.
Under the condition of meeting regional power failure, the standby power supply is started to supply power according to the weight of the intersection, so that normal operation of the intersection with high weight can be at least ensured, and traffic accidents are reduced. The embodiment dynamically adjusts the green light time, fully utilizes the green light time and ensures the normal operation of the intersection.
The embodiment relates to a system for fusion perception based on vehicle-road cooperation, which comprises:
the road section information acquisition module: acquiring urban traffic network information through a map, acquiring road information through the urban traffic network information, and classifying roads according to areas; installing acquisition equipment at an intersection according to traffic network information, and acquiring road section traffic information through the acquisition equipment;
and a road combination coefficient calculation module: transmitting the road section traffic information acquired by the acquisition equipment to an edge computing node, dividing each traffic intersection according to the driving directions, and computing road combination coefficients of different driving directions of each intersection through the edge computing node;
and the road combination weight control module is used for: calculating road combination weight of the intersections according to road combination coefficients of the intersections in different driving directions and the road information;
and the control module is used for: controlling traffic lights according to the road combination weight of the intersection, and selecting to start a standby power supply system under the abnormal power failure condition; the abnormal power failure includes line damage and line overhaul.
The working principle and the effect of the technical scheme are as follows: the urban traffic network map is obtained, roads are classified according to areas, traffic conditions of each area can be mastered better, traffic lights are distributed more accurately, traffic intersection information is collected through the collecting equipment, traffic conditions can be mastered in real time, and the time length and the interval time of traffic signals can be adjusted according to actual conditions, so that the urban traffic network map is more suitable for actual traffic demands, and therefore traffic running efficiency and traffic running safety are improved. Traffic can be effectively coordinated with traffic flow and pedestrian flow by arranging traffic lights, traffic pressure is relieved, and traffic efficiency of intersections is improved. The traffic intersection information is collected in real time, and the time length and the interval time of traffic signals are adjusted according to actual conditions, so that traffic accidents can be reduced, and the safety of traffic operation is improved; the main power supply circuit and the standby power supply are connected with the traffic light, so that the power supply stability of the traffic light can be effectively ensured, the power waste is reduced, and the energy utilization rate is improved.
In general, the scheme is used for acquiring the urban traffic network map, classifying according to the region, distributing traffic lights, and collecting traffic intersection information in real time through the collecting equipment to control the time and interval of traffic signals, so that the traffic signals are more suitable for actual traffic demands, and the traffic running efficiency and safety are improved.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (9)
1. A vehicle-road collaboration method based on edge computation, the method comprising:
s1, acquiring urban traffic network information through a map, acquiring road information through the urban traffic network information, and classifying roads according to areas; installing acquisition equipment at an intersection according to traffic network information, and acquiring road section traffic information through the acquisition equipment;
s2, transmitting the road section traffic information acquired by the acquisition equipment to an edge calculation node, dividing each traffic intersection according to the driving directions, and calculating road combination coefficients of different driving directions of each intersection through the edge calculation node;
s3, calculating the road combination weight of the intersections according to the road combination coefficients of the intersections in different driving directions and the road information;
s4, controlling traffic lights according to the road combination weight of the intersection, and selecting and starting a standby power supply system under the abnormal power failure condition; the abnormal power failure includes line damage and line overhaul.
2. The method for vehicle-road collaboration-based fusion awareness according to claim 1, comprising:
s11, acquiring urban traffic network information through a map, acquiring road information through the traffic information, and classifying roads according to areas; the road information comprises lane widths and lane numbers of all directions of the traffic intersection;
s12, arranging traffic lights and acquisition equipment at a traffic intersection; the traffic light and the acquisition equipment are connected with a main power supply line and a standby power supply;
s13, collecting road section traffic information through collecting equipment; the road section traffic information comprises the number of vehicles passing through the traffic intersection, the speed of the vehicles, the number of pedestrians and the time for collecting information by the collecting equipment; the acquisition equipment comprises a road side sensor and a vehicle end sensor.
3. The method for vehicle-road collaboration-based fusion awareness according to claim 1, comprising:
setting an edge computing node; processing the traffic intersection information by using an edge computing node to obtain a road combination coefficient; comprising the following steps:
according to a preset time period, calculating the number of vehicles, the speed of the vehicles and the number of pedestrians in the same direction at the same intersection;
calculating road combination coefficient lambda of the same direction in the preset time period of the same intersection rk 。
4. The method for fusion perception based on vehicle-road coordination according to claim 3, wherein the number of vehicles, the speed of vehicles and the number of pedestrians in the same direction at the same intersection are calculated according to a preset time period; comprising the following steps:
the number of sampling times in preset time is n, the number of passing vehicles at each sampling point of green light in the same direction of the same road at each intersection is Cij, and the number of passing pedestrians is Pij; vehicle average speed is Vij; time Jj when no pedestrian or vehicle is passing; i=1, 2,3 … n.
5. The method for fusion perception based on vehicle-road coordination according to claim 3, wherein the calculating of the road combination coefficient of the same intersection in the same direction within the preset time period specifically comprises the following steps:
λ 1k ,θ 2k …λ rk the traffic coefficients are r traffic coefficients in different directions at the same intersection; g, the total green light duration in the preset time,n is the sampling times in a preset time; j=1, 2,3 … m, m being the number of days of one statistical periodThe method comprises the steps of carrying out a first treatment on the surface of the Alpha is a dynamic adjustment factor.
6. The method for vehicle-road collaboration-based fusion awareness according to claim 5, comprising:
when 80% of Cmin is less than or equal to C ij+1 Alpha=1 when 1.2×cmax is not more than; c (C) ij+1 The current traffic flow of the intersection in the direction; cmax is the maximum traffic flow in the same time period before the same direction of the intersection in a statistical period; cmin is the minimum traffic flow in the same time period before the same time period of this direction of the intersection;
when C ij+1 > 1.2 XCmax or C ij+1 When the concentration is less than 80 percent multiplied by Cmin,
7. the method for vehicle-road collaboration-based fusion awareness according to claim 6, comprising:
determining the road combination weight of each driving direction of the traffic intersection according to the road combination coefficient;
lane width W and number Nw of lanes in each direction of the traffic intersection; ln is the natural logarithm of the base e;
determining the total road combination weight of the intersection according to the weight settings of different directions of the same intersection;
Z k ＝max(Z 1k ，Z 1k …Z rk )+avg(Z 1k ，Z 1k …Z rk )。
8. the method for vehicle-road collaboration-based fusion awareness according to claim 7, comprising:
z in the region k Ordering from high to low; calculating the average avg (Z) of all the road combination weights of the traffic intersections in the area k )；
If Z k ＞avg(Z k ) The method comprises the steps of carrying out a first treatment on the surface of the Then the intersection is greenThe lamp is in the time period and the traffic light T in the direction A and the direction opposite to the direction A k ＝(1+10％×avg(Z 1k ，Z 1k …Z rk )/max(Z 11 ，Z 12 ))×T；
If Z k ＜avg(Z k ) The method comprises the steps of carrying out a first treatment on the surface of the The green light time length T of the green light of the intersection in the direction A and the green light time length T of the green light in the direction opposite to the direction A k ＝(1-10％×avg(Z 1k ，Z 1k …Z rk )/max(Z 11 ，Z 12 ))×T；Z 11 ，Z 12 Weights in the direction A and the direction opposite to the direction A;
wherein; the green light calibration time length is T each time;
at least Z when abnormal power failure of area is encountered k ＞(1+10％)avg(Z k ) Is powered by the intersection-enabled backup power supply.
9. A system for fusion awareness based on vehicle-road collaboration, the system comprising:
the road section information acquisition module: acquiring urban traffic network information through a map, acquiring road information through the urban traffic network information, and classifying roads according to areas; installing acquisition equipment at an intersection according to traffic network information, and acquiring road section traffic information through the acquisition equipment;
and a road combination coefficient calculation module: transmitting the road section traffic information acquired by the acquisition equipment to an edge computing node, dividing each traffic intersection according to the driving directions, and computing road combination coefficients of different driving directions of each intersection through the edge computing node;
and the road combination weight control module is used for: calculating road combination weight of the intersections according to road combination coefficients of the intersections in different driving directions and the road information;
and the control module is used for: controlling traffic lights according to the road combination weight of the intersection, and selecting to start a standby power supply system under the abnormal power failure condition; the abnormal power failure includes line damage and line overhaul.
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