CN112907986A - Dynamic time window crossing scheduling method based on digital twin scene and edge cloud - Google Patents
Dynamic time window crossing scheduling method based on digital twin scene and edge cloud Download PDFInfo
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- G—PHYSICS
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- G08G1/00—Traffic control systems for road vehicles
- G08G1/07—Controlling traffic signals
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- G08—SIGNALLING
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- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
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- G—PHYSICS
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- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
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- G08G1/0116—Measuring and analyzing of parameters relative to traffic conditions based on the source of data from roadside infrastructure, e.g. beacons
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0125—Traffic data processing
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- G—PHYSICS
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- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/04—Detecting movement of traffic to be counted or controlled using optical or ultrasonic detectors
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/07—Controlling traffic signals
- G08G1/08—Controlling traffic signals according to detected number or speed of vehicles
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Abstract
The invention discloses a dynamic time window crossing scheduling method based on a digital twin scene and edge clouds.
Description
Technical Field
The invention belongs to the technical field of traffic management, and particularly relates to a dynamic time window crossing scheduling method based on a digital twin scene.
Background
At present, traffic jam is a common problem in each big city in China. 28 days 2 and 28 months 2020, the national statistics bureau publishes a national economy and social development statistics bulletin of 2019, and by the end of 2019, the quantity of retained automobiles for the whole country is 26150 thousands (including three-wheeled automobiles and 762 thousands of low-speed trucks), and 2122 thousands are added compared with the last year, wherein the quantity of retained automobiles for the private countries is 22635 thousands and 1905 thousands are added. The quantity of the civilian cars is 14644 thousands, 1193 thousands are added, wherein the quantity of the private cars is 13701 thousands, and 1112 thousands are added. The automobile holding capacity of China is continuously increased, and the bearing capacity of the traffic roads of China can be further tested.
The problem of traffic jam brings much trouble to people in urban life, and greatly increases the time and cost of people going out. In Beijing, if the peak period is selected to travel for 1 hour, roughly half an hour of time may be spent in congestion waiting. The time cost of a commuter group lost due to traffic congestion every month is 808 yuan. And in other cities such as Hangzhou, Guangzhou, Jinnan, Dalian, Harbin, Shenzhen, Shanghai, Chongqing and Qingdao with the ten highest congestion rank, the travel time can be increased by 0.88-1.00 times due to traffic congestion, and the minimum extra cost loss is at least 551 yuan per person per month. Secondly, traffic jam increases energy consumption, greatly increases atmospheric pollution emission of urban traffic, and brings great threat to public health.
The intersection scene is a scene in which vehicles are intersected, such as a road intersection, a fast road on-off ramp and the like. The intersection region is connected with roads in different directions, becomes an important junction node of a road traffic network, and has great influence on traffic safety and traffic efficiency of the traffic network. Statistically, over 50% of serious traffic accidents occur at or near intersections in the united states each year. Unreasonable intersection design and unreasonable intersection scheduling rules directly affect the safety and the efficiency of intersection traffic, and further directly affect the overall operation condition of the whole traffic network.
In order to relieve the traffic pressure of cities, a single-number and double-number restriction system is issued by some major cities in China, and vehicle restriction measures are implemented according to the tail numbers of vehicles, so that the vehicles of the vehicles are greatly reduced, and the traffic pressure is reduced to a certain extent. However, the existing traffic control measures take the license plate number as the traffic control standard, so that the consideration of humanization is lacked, and in addition, the distribution condition of the vehicles is not considered from the time and space dimensions, so that the problem of urban traffic jam cannot be fundamentally solved. In addition, most of the existing intelligent signal lamps monitor the traffic flow of each intersection through sensing equipment such as a camera and an induction line, and adjust the signal lamps according to the traffic flow, the length of a waiting queue and the like, so that the intersection passing efficiency is improved, and the passing time is reduced. The method has high deployment cost, lacks information communication between the vehicle and the regulation and control system, has limited acquired information types, cannot adapt to complicated and variable traffic environments, and has limited promotion effect on traffic efficiency.
Disclosure of Invention
In view of the above, the invention provides a dynamic time window crossing scheduling method based on a digital twin scene and an edge cloud, which is characterized in that the method is used for scheduling and controlling crossing passing vehicles based on a dynamic time window algorithm by establishing the digital twin scene in a crossing region and predefining the running track and potential conflict points of automatically-driven vehicles at the crossing, thereby effectively improving the crossing passing rate and greatly reducing the average waiting time of the vehicles at the crossing.
The technical scheme of the invention is as follows:
the invention firstly provides a dynamic time window crossing scheduling method based on a digital twin scene and an edge cloud, which comprises the following steps:
establishing a digital twin body of a scene based on real-time information data transmitted by a three-dimensional point cloud map, a scene high-precision map, roadside sensing equipment and an intelligent driving vehicle;
monitoring traffic operation in the area, monitoring physical state information of a scene, and updating high-precision map and three-dimensional point cloud map data;
maintaining a time window sequence based on standard UTC time for each intersection conflict point, monitoring the traffic state of an intersection area in real time, adding the conflict point time window sequences of all passable vehicles into an intersection conflict point time window set, enabling all occupied time windows of the same conflict point to be mutually non-intersected on the basis of an intersection scheduling strategy of a dynamic time window, and providing a planned path and track data carrying timestamp information for all vehicles to guide the running of a single vehicle; and updating the intersection conflict point time window sequence set along with time, and scheduling vehicles to pass through the intersection.
According to the priority scheme of the invention, the digital twin body consists of a basic information layer, a physical characteristic layer, a semantic information layer and a real-time mapping layer;
the basic information layer stores a three-dimensional point cloud map and scene high-precision map information of the intersection area;
the physical characteristic layer records the subordination relation between roads and lanes, the geometric information of the lanes, the geometric information of intersection areas and the positions of intersection stop lines;
the semantic information layer records lane speed limit, lane weight, road junction topological relation and conflict point) geometric information;
the real-time mapping layer maintains the information of a vehicle total set, a vehicle waiting queue on a Lane Lane and an intersection passing queue, and updates the state of the vehicle in real time according to the information transmitted by the vehicle.
According to a preferred embodiment of the invention, a set of time windows is maintained for each conflict point, all time windows being composed of two parts, each occupying a start time T for a time windowstartAnd the sum time window occupies the end time Tend，TstartAnd TendUTC time, precision in milliseconds, all of which are standard, is denoted as [ T ]start,Tend](ii) a The time window is indicated at the slave TstartTo TendDuring the time, the collision point will be occupied by a certain vehicle, and thus become unavailable.
According to the priority scheme of the invention, the current time of the target vehicle is set to be TbowThe current speed of the vehicle is VcurrentAcceleration of vehicle is a, crossing traffic speed is set as Vcross；
The collision area is a circular space area, and if the specific time T when the vehicle just reaches the conflict point is assumed, and the time elapsed from the edge of the collision area to the conflict point is Δ T, then:
Tstart＝T-ΔT
Tend＝T+ΔT
Vehiclelengthvehicle length, Vehicle, set for passing vehicles at the crossingwidthThe vehicle width is set for passing the vehicle according to the intersection.
In order to solve for the specific time T at which the vehicle reaches the conflict point, the time at which the vehicle takes to travel from the current position to the conflict point under dispatch control needs to be solved,
T＝Tnow+Δt
the vehicle state information including the position, speed and acceleration of the vehicle is synchronized in real time, the distance L from the current vehicle to the conflict point is obtained, and the condition that the vehicle needs to pass through the vehicle acceleration state and the vehicle speed stable state from the current position to the conflict point position is set, namely, in the vehicle acceleration state, the vehicle speed is from the initial speed VcurrentIncreasing to crossing traffic speed V with constant acceleration across(ii) a In the vehicle speed stable state, the vehicle speed is kept at VcrossAnd the vehicle runs to the conflict point at a constant speed, so that a time window occupied by the vehicle in the conflict point area is obtained.
According to the priority scheme of the invention, the time when the vehicles at the current intersection arrive at each conflict point according to the driving track of the vehicles and the time window sequence of each conflict point occupied by each vehicle are obtained and compared with the existing intersection conflict point time window sequence set; when detecting that a time window sequence of a certain conflict point occupied by a certain vehicle in the existing state conflicts with the existing conflict point time window sequence set, decelerating the vehicle, stopping in an intersection waiting area for waiting, calculating the time of reaching each conflict point for the vehicle again, when detecting that the time sequence does not conflict, namely the vehicle can pass through, sending an intersection passing schedule to the vehicle, updating the time window of the vehicle at the conflict point, and tracking the running of the vehicle until the vehicle exits the intersection.
The invention also provides a dynamic time window crossing scheduling system based on the digital twin scene and the edge cloud, which comprises the following steps: the intelligent driving system comprises an edge cloud platform, roadside sensing equipment and an intelligent driving vehicle;
the edge cloud platform establishes a digital twin body of a scene based on real-time information transmitted by a three-dimensional point cloud map, a scene high-precision map, roadside sensing equipment and an intelligent driving vehicle; the edge cloud platform maintains a time window sequence based on standard UTC time for each intersection conflict point, provides path planning service for all intelligent driving vehicles in the region in real time based on scene digital twin, schedules multiple vehicles in the conflict region, and maintains the safety and order of multiple vehicle driving in the region; the edge cloud platform guides the running of the single vehicle by transferring the driving right and the track data with the timestamp information, and the transferred track data comprises spatial position information and specified time for reaching the point; the edge cloud platform is directly connected with the road side sensing equipment, actively monitors traffic operation in the responsible area, monitors the physical state information of a scene, and updates high-precision map and three-dimensional point cloud map data in time;
the roadside sensing equipment comprises a camera, a laser radar and a millimeter wave radar; the system comprises an edge cloud platform, a road information acquisition module and a road information transmission module, wherein the edge cloud platform is used for acquiring road information and transmitting the road information to the edge cloud platform;
the intelligent driving vehicle transmits vehicle information to the edge cloud platform in real time and passes through the intersection according to the track data provided by the edge cloud platform and carrying the timestamp information.
Compared with the prior art, the invention provides a dynamic time window crossing scheduling method based on a digital twin scene and edge clouds, which is characterized in that the method is used for scheduling and controlling crossing passing vehicles based on a dynamic time window algorithm by establishing the digital twin scene in a crossing region and predefining the running track and potential conflict points of automatically-driven vehicles at the crossing, thereby effectively improving the crossing traffic rate and greatly reducing the average waiting time of the vehicles at the crossing.
Drawings
FIG. 1 is a layered structure of a digital twin;
FIG. 2 is a digital twin at a road intersection;
FIG. 3 is a schematic diagram of dynamic time window calculation;
fig. 4 is a schematic diagram of a dynamic time window crossing scheduling method based on a digital twin scene and an edge cloud according to the present invention, wherein a-D respectively illustrate four different times.
Detailed Description
In order to more specifically describe the present invention, the following detailed description is provided for the technical solution of the present invention with reference to the accompanying drawings and the specific embodiments.
Dynamic time window crossing scheduling system based on digit twin scene and marginal cloud, its characterized in that includes: the intelligent driving system comprises an edge cloud platform, roadside sensing equipment and an intelligent driving vehicle;
the edge cloud platform establishes a digital twin body of a scene based on real-time information transmitted by a three-dimensional point cloud map, a scene high-precision map, roadside sensing equipment and an intelligent driving vehicle; the edge cloud platform maintains a time window sequence based on standard UTC time for each intersection conflict point, provides path planning service for all intelligent driving vehicles in the region in real time based on scene digital twin, schedules multiple vehicles in the conflict region, and maintains the safety and order of multiple vehicle driving in the region; the edge cloud platform guides the running of the single vehicle by transferring the driving right and the track data with the timestamp information, and the transferred track data comprises spatial position information and specified time for reaching the point; the edge cloud platform is directly connected with the road side sensing equipment, actively monitors traffic operation in the responsible area, monitors the physical state information of a scene, and updates high-precision map and three-dimensional point cloud map data in time;
the roadside sensing equipment comprises a camera, a laser radar and a millimeter wave radar; the system comprises an edge cloud platform, a road information acquisition module and a road information transmission module, wherein the edge cloud platform is used for acquiring road information and transmitting the road information to the edge cloud platform;
the intelligent driving vehicle transmits vehicle information to the edge cloud platform in real time and passes through the intersection according to the track data provided by the edge cloud platform and carrying the timestamp information.
The invention discloses a dynamic time window crossing scheduling method based on a digital twin scene and an edge cloud, which comprises the following steps:
establishing a digital twin body of a scene based on real-time information data transmitted by a three-dimensional point cloud map, a scene high-precision map, roadside sensing equipment and an intelligent driving vehicle;
monitoring traffic operation in the area, monitoring physical state information of a scene, and updating high-precision map and three-dimensional point cloud map data;
maintaining a time window sequence based on standard UTC time for each intersection conflict point, monitoring the traffic state of an intersection area in real time, adding the conflict point time window sequences of all passable vehicles into an intersection conflict point time window set, enabling all occupied time windows of the same conflict point to be mutually non-intersected on the basis of an intersection scheduling strategy of a dynamic time window, and providing a planned path and track data carrying timestamp information for all vehicles to guide the running of a single vehicle; and updating the intersection conflict point time window sequence set along with time, and scheduling vehicles to pass through the intersection.
As shown in fig. 1, the element scene digital twin is a layered structure, and the mapping from the real scene to the virtual scene is realized from four dimensions. The edge cloud platform realizes perception and control of a real scene based on four-dimensional information provided by the scene digital twin.
The basic information layer stores point cloud maps and high-precision map information of intersection areas. The point cloud map is key information for realizing self-vehicle positioning of the vehicle, the high-precision map is used as an important perception container for assisting vehicle positioning and path track extraction, and map data of a vehicle end is updated by means of high bandwidth characteristics of short-range direct communication of an intersection area.
In the physical characteristic layer, the dependency relationship between Road and Lane Lane, the geometric information such as the width and orientation of Lane Lane, the geometric information of intersection area, the position of intersection stop line and the like are recorded.
In the semantic information layer, information such as lane speed limit, lane weight, intersection road connection topological relation, conflict point (shown as a track line intersection in an intersection area in fig. 2) geometry and the like is recorded, wherein the lane weight is an important reference of an intersection scheduling strategy.
And maintaining information such as a vehicle total set, a vehicle waiting queue on a Lane Lane, an intersection passing queue and the like on a real-time mapping layer, and updating the state of the vehicle in real time according to the information transmitted by the vehicle.
Taking a bidirectional six-lane crossroad as an example, a digital twin body of a crossing scene is established, and as shown in fig. 2, a visual display of the crossing model is shown.
The edge cloud platform is located at the bottommost layer of all the cloud platforms, is the cloud platform closest to the vehicle end and the road end in all the cloud platforms, is communicated with the regional cloud upwards, and is connected with the intelligent networking automobile downwards. The real-time performance is the biggest characteristic of the edge cloud platform, and the edge cloud platform is usually arranged near a responsible scene, especially in a scene with high conflict performance such as an intersection. The main services provided by the edge cloud platform include:
(1) scene digital twinning
The edge cloud platform establishes a digital twin body of a scene based on data such as a scene high-precision map, road side sensing equipment and real-time information transmitted by an intelligent driving vehicle, and is a basis for the edge cloud platform to realize all functions related to intelligent driving.
(2) Planning and scheduling
The edge cloud platform provides path planning service for all intelligent driving vehicles in the region in real time based on the element scene digital twin body, and dispatches multiple vehicles in a conflict region by means of putting down driving rights, so that safety and order of running of the multiple vehicles in the region are maintained.
(3) Driving guide
The edge cloud platform guides the running of the single vehicle by transferring the right of exercise and the track data with the timestamp information, and the issued track point comprises the spatial position information and the specified time for reaching the point.
(4) Active monitoring
The edge cloud platform is directly connected with the road side infrastructure and comprises a camera, a laser radar, a millimeter wave radar and other sensors, the sensors actively monitor traffic operation in the area in charge and monitor the physical state information of a scene, so that high-precision map and three-dimensional point cloud data can be updated timely.
Because the driving track of the vehicle at the intersection is fixed, and the vehicle is completely controlled by the dispatching instruction of the edge cloud in the intersection area, the vehicles on the same track line can not generate conflict, and therefore all potential conflicts at the intersection can come from the vehicles in different directions and occur at the fixed conflict point position. The crossing scheduling strategy based on the dynamic time window takes the conflict problem of the conflict points as a starting point, a time window sequence based on standard UTC time is maintained for each conflict point, all occupied time windows of the same conflict point are not intersected, and therefore the problem that the same conflict point is simultaneously occupied by a plurality of vehicles at a certain moment to cause vehicle collision is avoided.
a. Conflict point and conflict time window definitions
A conflict point is the intersection of multiple pass lines, essentially a single dot. However, since the vehicles have length and width dimensions in space, the vehicles and the conflict points cannot be easily handled as particles.
As shown in FIG. 3, for simplicity of the algorithm description, it is assumed that the vehicles have the same length VehiclelengthAnd width of VehiclewidthThe center point of the vehicle is located at the geometric center of the vehicle. For a certain conflict point, in order to enable two vehicles with potential conflict relation to safely pass through the conflict point, a circle with the radius of R is established by taking the actual coordinate of the point as the center of the circle.
In the limit, as shown in fig. 3, vehicle Car3 is leaving the conflict point area, and vehicle Car4 is entering the conflict point area, and the two vehicles can just avoid the collision. The radius of the conflict area can be obtained according to the geometrical relationship as follows:
the area with the radius of R is a conflict area, and at most one vehicle can be located in the conflict area at a certain moment. The time window occupied by the conflict point is a sequence pair consisting of the time when the vehicle enters the conflict area and the time when the vehicle exits the conflict area.
b. Computation of conflict time windows
A conflict-free intersection scheduling system based on dynamic time windows maintains a time window sequence set for each conflict point, and all the time windows consist of two parts which respectively occupy a starting time T for the time windowsstartAnd the sum time window occupies the end time Tend，TstartAnd TendUTC time, precision in milliseconds, all of which are standard, is denoted as [ T ]start,Tend]. The time window is indicated at the slave TstartTo TendDuring the time, the collision point will be occupied by a certain vehicle, and thus become unavailable.
The current time is TnowThe current speed of the vehicle is VcurrentAcceleration of vehicle is a, crossing traffic speed is set as Vcross. Because the vehicle can actively decelerate before entering the intersection to ensure safety, and in the intersection passing stage, the edge cloud platform ensures the driving safety of the intersection in a software-defined mode, the vehicle can pass through the intersection at a higher speed so as to improve the passing time of the vehicle at the intersection and further improve the passing rate of the intersection, and therefore V is realizedcurrent<Vcorss。
The collision area is a circular space area, and if the specific time T when the vehicle just reaches the conflict point is assumed, and the time elapsed from the edge of the collision area to the conflict point is Δ T, then:
Tstart＝T-ΔT (2)
Tend＝T+ΔT (3)
by the formula (1, 2, 3) and the crossing traffic speed VcrossThe following can be obtained:
in order to solve the specific time T when the vehicle reaches the conflict point, we need to solve the time Δ T consumed by the vehicle to travel to the conflict point from the current position under the scheduling control of the cloud platform,
T＝Tnow+Δt (5)
after the vehicle is registered to the edge cloud platform, the state information of the vehicle, such as position, speed, acceleration and the like, is synchronized to the edge cloud platform in real time, so that the distance L from the conflict point of the current vehicle can be acquired in real time.
The vehicle runs to the position of the collision point from the current position in the current state and needs to pass through the vehicle acceleration state and the vehicle speed stable state.
(1) Acceleration state of vehicle
In this state, the vehicle speed is from the initial speed VcurrentIncreasing to crossing traffic speed V with constant acceleration across。
Assume that the distance traveled in this state is L1Duration of time Δt1Then:
a*Δt1＝Vcross-Vcurrent (6)
the following equations (6, 7) can be obtained:
(2) vehicle speed steady state
In this state, the vehicle speed is kept at VcrossAnd the vehicle runs to the conflict point at a constant speed.
Assume that the distance traveled in this state is L2Duration of Δt2Then:
L2＝Vcross*Δt2 (10)
because of the fact that
L＝L1+L2 (11)
Combining formulas (9) and (11) gives:
combining equations (10) and (12) yields:
the formula is combined to obtain:
the specific time of the vehicle center point road intersection conflict point is as follows:
thus, it is possible to obtain:
in the actual implementation process, a certain time or space margin is required to compensate for control errors caused by vehicle actuators, network delays and the like. In a practical implementation we use a time margin of η seconds.
Finally, the time window occupied by the vehicle in the conflict point area can be obtained as follows:
in a first vehicle V1Before entering the intersection, the edge cloud platform calculates the time of the vehicle reaching each conflict point and the length of the time occupied on the conflict point according to the state of the vehicle. E.g. Tstart1，Tend2Respectively represent a first vehicle V1Entry and exit conflict point P1Together, they form a conflict point P1Occupied time window [ T ]start1,Tend2]. Suppose there is another second vehicle V at this time2When the vehicle is about to enter the intersection, the edge cloud platform can calculate a second vehicle V2The time to reach each conflict point, and the time window sequence occupying each conflict point, are compared with the existing intersection conflict point time window sequence set. It is now detected that the second vehicle V is in the existing state2Will occupy the conflict point P1[ T ] ofstart3,Tend4]Time window, and the time window and the first vehicle V1At the conflict point P1Time window of [ T ]start1,Tend2]Producing a conflict, the conflict is [ T ]start3,Tend2]Wherein T isstart1<Tstart3<Tend2。
To avoid potential collision problems, in the present round of scheduling, the second vehicle V2Will not be allowed to pass through the intersection and thus the second vehicle V2Will slow down and stop waiting in the intersection waiting area.
The edge cloud platform monitors the traffic state of the intersection area in real time and updates the intersection conflict point time window sequence set along with time. As time passes, vehicles in traffic at the intersection will gradually exit the intersection and cause a change in the set of intersection conflict point time windows. The dispatcher detects the vehicle at a high frequency according to the above calculation procedure, and when the second vehicle V is detected2When passing, the vehicle can go to the second vehicle V in real time2Sending the intersection passage scheduling execution to update the second vehicle V2At the conflict point P1And tracking the second vehicle V2Until the second vehicle V2And (5) exiting the intersection.
When more vehicles are added, the dispatching strategy can sequentially calculate the maximum number of the vehicles which can pass through each Lane Lane, select the Lane Lane which can pass through the most vehicles, add the conflict point time window sequences of all the vehicles which can pass through into the intersection conflict point time window set, and dispatch the vehicles to pass through the intersection.
An embodiment of the present invention will be described in detail with reference to fig. 4.
As shown in FIG. 4(A), the conflict-free intersection scheduling system based on dynamic time windows maintains a time window sequence set for each conflict point (note: a time window display in which only a part of conflict points are listed here), and all time windows are composed of two parts, and respectively occupy a start time T for the time windowstartAnd the sum time window occupies the end time Tend， TstartAnd TendUTC time, precision in milliseconds, all of which are standard, is denoted as [ T ]start,Tend]. The time window is indicated at the slave TstartTo TendDuring the time, the collision point will be occupied by a certain vehicle, and thus become unavailable.
The following description will take the example of calculating the time window occupied by Car1 at the conflict point with id 15.
As shown at FIG. 4(A), Car1 comes from lane landidLane land for 1-roadidThe L1 road passes through the conflict points 8-15-14-5 in sequence during the intersection traffic. Before the vehicle enters the intersection, the edge cloud platform calculates the time of the vehicle reaching each conflict point and the length of the time occupied at the conflict point according to the state of the vehicle, as shown in fig. 4 (B). t is t1，t2Respectively representing the time when Car1 enters and leaves the conflict point area with id 15, which together form a time window t occupied by the conflict point1,t2]。
Suppose that another vehicle will be present at that timeTo enter the intersection, as shown at fig. 4(B), Car2 is entering the intersection, and the trajectory line traveled by Car2 is from lane land id4 to lane landidL4, the overshoot point passed is 10-16-15-7. At this time, the edge cloud platform calculates the time for Car2 to reach each conflict point and the time window sequence occupying each conflict point, and compares with the existing intersection conflict point time window sequence set, as shown in fig. 4 (B). Now it is detected that in the present state, Car2 will occupy [ t ] of conflict point 153,t4]A time window which will be compared with the time window t existing at the conflict point 151,t2]Producing a collision with a collision projection of [ t ]3,t2]As shown in fig. 4(B) at the intersection of the dash point time window No. 15.
To avoid potential conflict problems, in the present round of scheduling, Car2 will not be allowed to pass through the intersection, and thus Car2 will slow down and stop waiting within the intersection waiting area.
The edge cloud platform monitors the traffic state of the intersection area in real time and updates the intersection conflict point time window sequence set along with time. As time passes, vehicles in traffic at the intersection will gradually exit the intersection and cause a change in the set of intersection conflict point time windows. The dispatcher detects at a high frequency according to the calculation flow, and when detecting that Car2 can pass through, the dispatcher sends intersection passing schedule execution to Car2 in real time, updates an intersection conflict point time window, and tracks the operation of Car2 until Car2 exits the intersection.
As shown in fig. 4(C), (D), by controlling the driving state of Car2 so that Car2 is behind the time window of expected occupancy of conflict points 10-16-15-7, when all conflict points will not exist, Car1 and Car2 can pass normally.
The embodiments described above are presented to enable a person having ordinary skill in the art to make and use the invention. It will be readily apparent to those skilled in the art that various modifications to the above-described embodiments may be made, and the generic principles defined herein may be applied to other embodiments without the use of inventive faculty. Therefore, the present invention is not limited to the above embodiments, and those skilled in the art should make improvements and modifications to the present invention based on the disclosure of the present invention within the protection scope of the present invention.
Claims (9)
1. A dynamic time window crossing scheduling method based on a digital twin scene and an edge cloud is characterized by comprising the following steps:
establishing a digital twin body of a scene based on real-time information data transmitted by a three-dimensional point cloud map, a scene high-precision map, roadside sensing equipment and an intelligent driving vehicle;
monitoring traffic operation in the area, monitoring physical state information of a scene, and updating high-precision map and three-dimensional point cloud map data;
maintaining a time window sequence based on standard UTC time for each intersection conflict point, monitoring the traffic state of an intersection area in real time, adding the conflict point time window sequences of all passable vehicles into an intersection conflict point time window set, enabling all occupied time windows of the same conflict point to be mutually non-intersected on the basis of an intersection scheduling strategy of a dynamic time window, and providing a planned path and track data carrying timestamp information for all vehicles to guide the running of a single vehicle; and updating the intersection conflict point time window sequence set along with time, and scheduling vehicles to pass through the intersection.
2. The dynamic time window crossing scheduling method based on the digital twin scene and the edge cloud as claimed in claim 1, wherein the digital twin is composed of a basic information layer, a physical characteristic layer, a semantic information layer and a real-time mapping layer;
the basic information layer stores a three-dimensional point cloud map and scene high-precision map information of the intersection area;
the physical characteristic layer records the subordination relation between roads and lanes, the geometric information of the lanes, the geometric information of intersection areas and the positions of intersection stop lines;
the semantic information layer records lane speed limit, lane weight, road connection topological relation of intersections and geometric information of conflict points;
the real-time mapping layer maintains the information of a vehicle total set, a vehicle waiting queue on a Lane Lane and an intersection passing queue, and updates the state of the vehicle in real time according to the information transmitted by the vehicle.
3. The dynamic time window intersection scheduling method based on the digital twin scene and the edge cloud as claimed in claim 1, wherein the intersection conflict point is an intersection point on at least two vehicle driving trajectory lines in the intersection.
4. The dynamic time window crossing scheduling method based on digital twin scene and edge cloud as claimed in claim 1 or 3, wherein the crossing conflict point is set to a circle with radius R,
Vehiclelengthvehicle length, Vehicle, set for passing vehicles at the crossingwidthThe vehicle width is set for passing the vehicle according to the intersection.
5. The dynamic time window crossing scheduling method based on digital twin scenes and edge clouds according to claim 1, wherein a time window sequence set is maintained for each conflict point, all time windows are composed of two parts, and the time windows respectively occupy a start time TstartAnd the sum time window occupies the end time Tend，TstartAnd TendUTC time, precision in milliseconds, all of which are standard, is denoted as [ T ]start，Tend](ii) a The time window is indicated at the slave TstartTo TendDuring the time, the collision point will be occupied by a certain vehicle, and thus become unavailable.
6. The dynamic time window intersection scheduling method based on digital twin scenes and edge clouds according to claim 5,
setting the current time of the target vehicle as TnowVehicleCurrent speed is VcurrentAcceleration of vehicle is a, crossing traffic speed is set as Vcross；
The collision area is a circular space area, and if the specific time T when the vehicle just reaches the conflict point is assumed, and the time elapsed from the edge of the collision area to the conflict point is Δ T, then:
Tstart＝T-ΔT
Tend＝T+ΔT
Vehiclelengthvehicle length, Vehicle, set for passing vehicles at the crossingwidthThe vehicle width is set for passing the vehicle according to the intersection.
In order to solve for the specific time T at which the vehicle reaches the conflict point, the time at which the vehicle takes to travel from the current position to the conflict point under dispatch control needs to be solved,
T＝Tnow+Δt
the vehicle state information including the position, speed and acceleration of the vehicle is synchronized in real time, the distance L from the current vehicle to the conflict point is obtained, and the condition that the vehicle needs to pass through the vehicle acceleration state and the vehicle speed stable state from the current position to the conflict point position is set, namely, in the vehicle acceleration state, the vehicle speed is from the initial speed VcurrentIncreasing to crossing traffic speed V with constant acceleration across(ii) a In the vehicle speed stable state, the vehicle speed is kept at VcrossAnd the vehicle runs to the conflict point at a constant speed, so that a time window occupied by the vehicle in the conflict point area is obtained.
7. The dynamic time window crossing scheduling method based on digital twin scenes and edge clouds according to claim 1,
acquiring the time when the vehicles at the current intersection reach each conflict point according to the running track of the vehicles and the time window sequence of each conflict point occupied by each vehicle, and comparing the time window sequence with the existing intersection conflict point time window sequence set; when detecting that a time window sequence of a certain conflict point occupied by a certain vehicle in the existing state conflicts with the existing conflict point time window sequence set, decelerating the vehicle, stopping in an intersection waiting area for waiting, calculating the time of reaching each conflict point for the vehicle again, when detecting that the time sequence does not conflict, namely the vehicle can pass through, sending an intersection passing schedule to the vehicle, updating the time window of the vehicle at the conflict point, and tracking the running of the vehicle until the vehicle exits the intersection.
8. The dynamic time window crossing scheduling method based on digital twin scenes and edge clouds according to claim 1,
when the vehicles to be passed are ready to drive into the intersection, the maximum number of the vehicles which can pass through each Lane Lane at present is calculated in sequence, the Lane Lane which meets the vehicle passing requirement and can pass through the most vehicles is selected from the number of the vehicles to be passed, the vehicles to be passed pass through the Lane Lane are provided for the vehicles to pass through, the conflict point time window sequence of the vehicles is added into the conflict point time window set of the intersection, and the vehicles are scheduled to pass through the intersection.
9. A dynamic time window crossing scheduling system based on digital twin scenes and edge clouds is characterized by comprising: the intelligent driving system comprises an edge cloud platform, roadside sensing equipment and an intelligent driving vehicle;
the edge cloud platform establishes a digital twin body of a scene based on real-time information transmitted by a three-dimensional point cloud map, a scene high-precision map, roadside sensing equipment and an intelligent driving vehicle; the edge cloud platform maintains a time window sequence based on standard UTC time for each intersection conflict point, provides path planning service for all intelligent driving vehicles in the region in real time based on scene digital twin, schedules multiple vehicles in the conflict region, and maintains the safety and order of multiple vehicle driving in the region; the edge cloud platform guides the running of the single vehicle by transferring the driving right and the track data with the timestamp information, and the transferred track data comprises spatial position information and specified time for reaching the point; the edge cloud platform is directly connected with the road side sensing equipment, actively monitors traffic operation in the responsible area, monitors the physical state information of a scene, and updates high-precision map and three-dimensional point cloud map data in time;
the roadside sensing equipment comprises a camera, a laser radar and a millimeter wave radar; the system comprises an edge cloud platform, a road information acquisition module and a road information transmission module, wherein the edge cloud platform is used for acquiring road information and transmitting the road information to the edge cloud platform;
the intelligent driving vehicle transmits vehicle information to the edge cloud platform in real time and passes through the intersection according to the track data provided by the edge cloud platform and carrying the timestamp information.
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