CN110930691B - Network traffic flow double-layer control method in full-automatic driving environment - Google Patents

Network traffic flow double-layer control method in full-automatic driving environment Download PDF

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CN110930691B
CN110930691B CN201911011916.6A CN201911011916A CN110930691B CN 110930691 B CN110930691 B CN 110930691B CN 201911011916 A CN201911011916 A CN 201911011916A CN 110930691 B CN110930691 B CN 110930691B
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CN110930691A (en
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钱国敏
郭满
章立辉
王亦兵
王殿海
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Zhejiang University ZJU
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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
    • G08G1/0137—Measuring and analyzing of parameters relative to traffic conditions for specific applications
    • 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
    • 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

Abstract

The invention discloses a double-layer control method of network traffic flow in a full-automatic driving environment. The method constructs a set of linear programming model on the upper layer to minimize the maximum time required by travel among all origin-destination points in the road network as a target, so as to control the departure time, the travel path and the signal scheme of the intersection of the automatic driving vehicle, realize that the traffic flow on all road sections in the road network presents periodic characteristics under the full automatic driving environment, and fully utilize the space-time resources of the road network as far as possible. The lower layer controls the longitudinal speed of the automatic driving vehicle to realize that all vehicles on the road section can pass through the intersection without stopping, and deduces a calculation formula of the shortest path section length required by passing through the intersection without stopping through a geometric relationship. Finally, road network traffic operation presents a stable state in a full-automatic driving environment, traffic flow on all road sections presents periodic characteristics in the state, and vehicles can pass through all signal intersections without stopping.

Description

Network traffic flow double-layer control method in full-automatic driving environment
Technical Field
The invention relates to a network traffic flow double-layer control method in a full-automatic driving environment, which is used for carrying out combined optimization on the departure time, the travel path, the longitudinal track of a road section and an intersection signal scheme of an automatic driving vehicle in a road network and belongs to the technical field of intelligent traffic.
Background
Vehicles with full-automatic driving technology have been tested in a closed test field in a large number, and some of the automatic driving automobiles of enterprises are tested on open urban roads, and some of the automatic driving automobiles even start commercial test operation. The advent of vehicle road coordination technology has further made possible the large-scale application of autonomous vehicles. The autonomous vehicles with communication capability may not only provide real-time information for road traffic status estimation, but also may be used directly as actuators for various traffic control strategies to improve traffic flow operation. Under the background that the automatic driving technology is more mature, a network traffic flow control method which can fully utilize the automatic driving vehicle technology is urgently needed to reasonably distribute and utilize road space-time resources so as to relieve traffic congestion, improve travel efficiency and save travel time of residents.
Disclosure of Invention
The invention aims to provide a double-layer control method of network traffic flow in a full-automatic driving environment. The core idea of the double-layer method is that a set of linear programming model which aims at minimizing the maximum time required by travel among all origin-destination points in the road network is constructed at the upper layer to control the departure time, the travel path and the intersection of the automatic driving vehicle, so that the traffic flow on all road sections in the road network presents periodic characteristics in the full-automatic driving environment, and the space-time resources of the road network are fully utilized as far as possible. The model mainly comprises a departure time distribution module, a trip path distribution module, a signal optimization module and a path and signal phase matching module. The lower layer controls the longitudinal speed of the automatic driving vehicle to realize that all vehicles on the road section can pass through the intersection without stopping, and deduces a calculation formula of the shortest path section length required by passing through the intersection without stopping through a geometric relationship. Finally, road network traffic operation presents a stable state in a fully automatic driving environment, traffic flow on all road sections presents periodic characteristics based on signal periods in the state, and vehicles can pass through all signal intersections without stopping.
The technical scheme adopted by the invention is as follows:
a network traffic flow double-layer control method under a full-automatic driving environment comprises the following steps:
c1, constructing a set of linear programming model aiming at minimizing the maximum time required by finishing all origin-destination opposite traveling to obtain the departure time, the traveling path and the timing scheme of each signalized intersection of the automatic driving vehicle.
c2, controlling the longitudinal speed of the automatic driving vehicle on each road section at the lower layer, and realizing that all vehicles on the road network can pass through the intersection without stopping.
c3, under the full-automatic driving environment, all vehicles travel according to the travel route obtained in the step c1 and the distributed travel time, and the network traffic flow stable state can be realized by adopting the longitudinal speed of the step c2 for driving. In this steady state, traffic flow on all road segments exhibits a periodic characteristic, and vehicles may pass through without stopping at all signal intersections. The stable state means that in one signal period, all automatic vehicles entering the road section ij from the intersection i can drive out of the road section ij through the intersection j without stopping in a certain period through longitudinal speed control. And the system is extended to the road network, the traffic flow on all road sections presents periodic characteristics, and vehicles can pass through all signal intersections without stopping.
Further, in step c1, the linear programming model aiming at minimizing the maximum time required for completing all origin-destination trips comprises a departure time allocation module for controlling a departure time of the vehicle, a trip path allocation module for controlling a trip path of the vehicle, a signal optimization module for optimizing signal timing, a path and signal phase pairing module for establishing a corresponding relationship between the trip path and an intersection signal phase, and an objective function module for minimizing the maximum time required for completing all origin-destination trips.
Further, the departure time distribution module controls the departure time of the automatic driving vehicle through the following constraint, and the situation that the vehicle travels intensively in time to cause congestion is avoided.
Figure BDA0002244450570000021
Figure BDA0002244450570000022
Figure BDA0002244450570000023
Figure BDA0002244450570000024
Figure BDA0002244450570000025
Figure BDA0002244450570000026
Figure BDA0002244450570000027
In the formula:
w represents a beginning-to-end set;
Ωwa set of paths representing origin-destination w;
i represents a certain intersection;
k represents the intersection phase number;
w represents a certain alignment, W belongs to W;
r denotes a path set ΩwIn one path, r ∈ Ωw；
Figure BDA0002244450570000031
Representing the number of vehicles going out by the origin-destination w per period selected path r;
Figure BDA0002244450570000032
is a binary variable and is used for judging whether the r path of the origin-destination pair w passes through the k phase of the intersection i,
Figure BDA0002244450570000033
the r path representing the origin-destination w passes through the k phase of the intersection i, otherwise, the r path does not pass through the intersection i;
Figure BDA0002244450570000034
indicates the number of vehicles passing through the phase k at the intersection i per cycle on the r path of the origin-destination pair w,
Figure BDA0002244450570000035
when in use
Figure BDA0002244450570000036
Then
Figure BDA0002244450570000037
Otherwise
Figure BDA0002244450570000038
M is a large natural number which ensures that the number of vehicles which pass through the phase k at the intersection i in each period on the r path of the origin-destination point w does not exceed the number of vehicles which depart from the path in each period
Figure BDA0002244450570000039
nwRepresenting the number of vehicles departing per cycle of origin-destination w;
Figure BDA00022444505700000310
representing the number of lanes channelized to the k phase at the intersection i;
Figure BDA00022444505700000311
green time representing the phase k at the intersection i;
hsindicating a saturated headway.
Constraints (1) - (5) indicate that the number of vehicles arriving at the phase k of the intersection i per cycle does not exceed the allowable traffic capacity; constraint (6) indicates that the number of vehicles departing from each period of origin-destination w is equal to the sum of the number of vehicles departing from all paths, the vehicles depart at equal intervals in each period, and the interval is equal to the period duration/the number of vehicles departing from each period; the constraint (7) is an integer constraint.
Further, the travel path distribution module controls the travel path of the automatic driving vehicle through the following constraint, and the situation that the vehicles are distributed too intensively on the space to cause congestion is avoided.
Figure BDA00022444505700000312
Figure BDA00022444505700000313
Figure BDA00022444505700000314
Figure BDA00022444505700000315
Figure BDA0002244450570000041
Figure BDA0002244450570000042
Figure BDA0002244450570000043
Figure BDA0002244450570000044
Figure BDA0002244450570000045
In the formula:
n represents a road network node set, which comprises an origin-destination point set I' and an intersection set I, subscripts u and v are different nodes of a road network, and u, v belong to N and u is not equal to v;
Figure BDA0002244450570000046
indicates the order of the node v on the path r when
Figure BDA0002244450570000047
Indicating that node v is not on path r, where
Figure BDA0002244450570000048
Indicating the order of origin (o), (w) of origin (w);
Figure BDA0002244450570000049
is a binary variable which indicates whether the path r passes through the section vu or not when
Figure BDA00022444505700000410
Representing that the path r passes through the section vu, otherwise it does not pass;
Figure BDA00022444505700000411
is a binary parameter, which indicates whether the node v is the starting point of the origin-destination path r, when
Figure BDA00022444505700000412
Indicating that the node v is the starting point of the path r, otherwise, not;
Figure BDA00022444505700000413
is a binary parameter, which indicates whether the node v is the end point of the origin-destination path r, when
Figure BDA00022444505700000414
Indicating that the node v is the end point of the path r, otherwise, not;
a is a road segment set in a road network;
lvuthe length of the section vu belongs to A;
Figure BDA00022444505700000415
represents the shortest distance of origin-destination w;
beta is a length control parameter of the origin-destination path r. The beta value is too large and is easily distributed to unreasonable paths; the beta value is too small, the solution space of the model is influenced, and the reasonable range is recommended to be (1,2) through repeatedly solving the travel path distribution module.
Constraint (8) indicates the starting sequence number of each origin to w
Figure BDA00022444505700000416
Is set to 1; constraints (9) and (10) select the road segment through which the path r passes, the constraint (9) representing a path node number
Figure BDA00022444505700000417
Sequentially increasing by 1, the constraint (10) numbering nodes not on path r sequentially
Figure BDA00022444505700000418
Set to 0; constraints (11) and (12) prevent loops from occurring; constraints (13) and constraints (14) ensure connectivity of the paths; constraints (15) ensure the reasonability of the paths, preventing the length of the allocated paths from being much greater than the length of the shortest path; constraint (16) limiting
Figure BDA0002244450570000051
Is a binary variable.
Further, the signal optimization module performs signal timing optimization by the following constraints:
Figure BDA0002244450570000052
Figure BDA0002244450570000053
Figure BDA0002244450570000054
Figure BDA0002244450570000055
Figure BDA0002244450570000056
Cmin≤C≤Cmax (22)
Figure BDA0002244450570000057
Figure BDA0002244450570000058
in the formula:
Figure BDA0002244450570000059
respectively the green time of each phase at the intersection i, and the phases are numbered according to the NEMA phase structure;
c represents the signal period duration;
Cmin,Cmaxrespectively representing the minimum and maximum values of the signal period;
gmin,gmaxrespectively representing the minimum and maximum values of the phase duration.
Constraints (17) - (20) indicate that the green light durations of the paired phases are equal; constraint (21) means that the sum of the phase green duration of the same phase ring equals the signal period; constraints (22) and (23) limit cycle C and phase duration
Figure BDA00022444505700000510
The value range of (a); constraining (24) phase duration
Figure BDA00022444505700000511
Is an integer variable.
Further, the path and signal phase pairing module establishes a corresponding relationship between the travel path and the intersection signal phase through the following constraints.
Figure BDA00022444505700000512
Figure BDA00022444505700000513
Figure BDA0002244450570000061
Figure BDA0002244450570000062
In the formula:
a-(i, k) an entry leg representing a k phase at intersection i;
a+(i, k) represents the exit link for the k phase at i intersection.
When a certain path r of the origin-destination pair w passes through an inlet-outlet road section corresponding to the k phase of the intersection i at the same time, the vehicle which selects the path r to travel passes through the intersection i at the k phase, namely
Figure BDA0002244450570000063
Then
Figure BDA0002244450570000064
Otherwise, the path r does not pass through the k phase at the i intersection, i.e.
Figure BDA0002244450570000065
Further, the objective function module minimizes the maximum time required to complete all origin-destination trips by the following constraints:
maxrm
Figure BDA0002244450570000066
Figure BDA0002244450570000067
in the formula:
rm represents the minimum value of the reciprocal of the number of cycles required for completing the travel demand at all the origin-destination pairs;
rmwrepresenting the reciprocal of the number of cycles required for origin-destination pair w to complete its fixed travel demand;
Nwrepresenting a fixed travel demand of origin-destination w;
the objective function maxrm maximizes the minimum value of the reciprocal of the number of cycles required for all the origin-destination pairs to complete the travel demand, and is equivalent to minimizing the maximum time required for all the origin-destination pairs to complete the travel demand, the constraint (29) represents the reciprocal of the number of cycles required for the origin-destination pair w to complete the travel demand, and the constraint (30) represents the minimum value of the reciprocal of the number of cycles.
Further, in the step c2, a calculation formula of the shortest path length required for realizing the non-stop passing through the intersection through the longitudinal speed control is given, and on the section meeting the minimum path length, a reasonable speed is selected to ensure that the automatic driving vehicle on the section can pass through the intersection without stopping, and the calculation formula of the shortest path length is as follows:
Figure BDA0002244450570000068
in the formula:
Figure BDA0002244450570000071
representing the length of the shortest path segment required by controlling the longitudinal speed so as to pass through the intersection without stopping;
Vmin,Vmaxrespectively representing the minimum and maximum speeds allowed for the section vu.
The invention has the beneficial effects that:
the invention provides a network traffic flow double-layer control method in a full-automatic driving environment, which is characterized in that a set of linear programming model aiming at minimizing the maximum time required by finishing all origin-destination opposite traveling is constructed for the first time to obtain a signal scheme of a departure time, a traveling path and an intersection of an automatic driving vehicle, and the longitudinal speed of the automatic driving vehicle on each road section is controlled at the same time, so that all vehicles on a network can pass through the intersection without stopping, the network traffic flow periodically presents a stable state without stopping and passing at the intersection, and the method fully utilizes road space-time resources, minimizes the total time of all origin-destination opposite traveling, relieves traffic congestion, improves traveling efficiency and saves traveling time of residents.
Drawings
FIG. 1 traffic signal NEMA phase structure;
FIG. 2 is a sample vehicle trajectory;
FIG. 3 is a road network topology.
Detailed Description
The invention provides a network traffic flow double-layer control method in a full-automatic driving environment, which specifically comprises the following steps:
c1, constructing a set of linear programming model aiming at minimizing the maximum time required by finishing all origin-destination opposite traveling to obtain the departure time, the traveling path and the timing scheme of each signalized intersection of the automatic driving vehicle.
c2, controlling the longitudinal speed of the automatic driving vehicle on each road section at the lower layer, and realizing that all vehicles on the road network can pass through the intersection without stopping.
c3, under the full-automatic driving environment, all vehicles travel according to the travel route obtained in the step c1 and the distributed travel time, and the network traffic flow stable state can be realized by adopting the longitudinal speed of the step c2 for driving. In this steady state, traffic flow on all road segments exhibits a periodic characteristic, and vehicles may pass through without stopping at all signal intersections.
As a preferred scheme, the linear programming model includes a departure time allocation module for controlling a departure time of the vehicle, a travel path allocation module for controlling a travel path of the vehicle, a signal optimization module for signal timing optimization, a path and signal phase pairing module for establishing a corresponding relationship between the travel path and a signal phase at an intersection, and an objective function module for minimizing a maximum time required for completing all origin-destination trips.
In addition, a calculation formula for the shortest path length required by realizing the non-stop passing of the intersection through longitudinal speed control is given, and on the section meeting the minimum path length, the reasonable speed is selected to ensure that the automatic driving vehicle on the section can pass through the intersection without stopping:
suppose that a distance ij defines an allowable speed range (V)min,Vmax) In which V isminIs greater than 0. When the road section length is long enough and the number of arriving vehicles does not exceed the traffic capacity of the intersection, the vehicle passes through the position (V)min,Vmax) The proper longitudinal speed is selected to ensure that an automatic vehicle entering the section ij in the same signal cycle can drive out of the section ij through the intersection j without stopping, as shown in fig. 2.
FIG. 2 shows a diagram of the trajectories of automatic vehicles on a section ij passing through an intersection j without stopping, these automatic vehicles having different longitudinal speeds, entering the section ij from the intersection i
Figure BDA0002244450570000081
The phase is driven off the road section ij through the intersection j, wherein it is assumed
Figure BDA0002244450570000082
In order to turn the phase to the left,
Figure BDA0002244450570000083
is a straight line phase. If the first vehicle turns left in each cycle at speed vfIn that
Figure BDA0002244450570000084
After the starting moment, the vehicle leaves the intersection j, and the last left-turn automatic vehicle is driven at the speed vlIn that
Figure BDA0002244450570000085
Drive off intersection j at a time before the end, and Vf,Vl∈(Vmin,Vmax) Then all left-turn vehicles that enter section ij at the same cycle on section ij can be assigned the appropriate speed to pass through without stoppingAn intersection j; similarly, for a straight-ahead vehicle on a section ij, if it can be (V)min,Vmax) And the proper speed is also found in the range, so that the first and the last straight-going automatic vehicles entering in the same period can drive out of the road section ij without stopping to pass through the intersection j, and all the straight-going automatic vehicles entering in the same period can be distributed to proper longitudinal speed to drive out of the road section ij without stopping.
Make the automotive vehicle can guarantee through longitudinal speed control that it passes through the downstream intersection not to stop, need satisfy: firstly, the number of vehicles arriving at an intersection per period cannot exceed the traffic capacity of the vehicles; ② the section should have enough length. The condition (i) can be satisfied by controlling the departure time, the trip path and the signal scheme through an upper layer, and a shortest path calculation formula which needs to be satisfied is given as the following condition (ii):
Figure BDA0002244450570000086
calculating the allowable speed range (V) according to the shortest path length calculation formulamin,Vmax) The shortest path length in between. When the length of the path is larger than
Figure BDA0002244450570000087
In time, an appropriate speed V (V) can be assigned according to the time when each automatic vehicle enters the section vumin≤V≤Vmax) Thereby ensuring that all automatic vehicles can drive away from the road section vu without stopping.
Taking a 4 × 4 road network as an example, as shown in fig. 3, the road network has 32 nodes, 16 intersections, 40 road segments, and 32 alignment points. The implementation steps are as follows:
step 1: solving the linear programming model to obtain the departure time, the travel path and the signal timing scheme of each intersection of each automatic vehicle, and the method comprises the following specific steps:
step 1.1: constructing a road network topology and a network traffic flow set, wherein the road network topology and the network traffic flow set comprise an intersection set I, a road network node set N, a road section set A, an origin-destination set W and a phase in-out road section matching set AP, and examples are shown in table 1:
table 1 road network topology and network traffic flow set examples
Collection name Aggregated content
Intersection set I {1,2,3,4,…,14,15,16}
Road network node set N {1,2,3,…,30,31,32}
Road section set A {(1,2),(2,1),(1,5),(5,1)…}
Origin-destination set W {17→25,25→17,19→27,27→19…}
Phase access road section matching set AP g1Phase { (10,1,4), (11,2,5) … } …
Step 1.2: investigating to obtain various model parameters including road length laOrigin-destination fixed traffic demand NwMinimum and maximum values of the period duration Cmin,CmaxMinimum and maximum phase duration gmin,gmaxNumber of channelized lanes per intersection phase k
Figure BDA0002244450570000091
Saturation vehicleHead time interval hs。
Step 1.3: calculating the shortest path length between each pair of origin-destination pairs by using Dijkstra algorithm
Figure BDA0002244450570000092
The number of paths r and the path length control parameter beta between each pair of origin-destination pairs are determined. For example, in the example, two paths are allocated to the origin-destination pair 17 → 25, the shortest path length is 4155m, the path length control parameter β is set to 1.5, and the shortest path lengths of the other OD are shown in table 2:
TABLE 2 shortest Path Length of each OD of road network
OD pair 17→25 18→26 19→27 20→28 21→29 22→30 23→31 24→32
Shortest Path Length (m) 4155 3255 3075 4215 4605 3660 3435 4155
OD pair 25→17 26→18 27→19 28→20 29→21 30→22 31→23 32→24
Shortest Path Length (m) 4155 3255 3075 4215 4605 3660 3435 4155
OD pair 17→29 18→30 19→31 20→32 25→21 26→22 27→23 28→24
Shortest Path Length (m) 3240 2790 2760 3150 3015 2715 2220 2790
OD pair 21→17 22→18 23→19 24→20 29→25 30→26 31→27 32→28
Shortest Path Length (m) 3120 2880 2745 3015 3210 3090 2325 2850
Step 1.4: and solving the linear programming model to obtain a timing scheme of each signalized intersection in the network, the number of the departure vehicles in each period and the number of the departure vehicles in each period of each path. For example, the two paths of origin-destination 19 → 27 are {19,3,2,6,5,9,13,14,27} and {19,3,2,1,5,9,10,14,27} respectively, and 24 and 4 vehicles are respectively started per cycle, and 28 vehicles are always started, and other paths and flow and intersection signal schemes are as shown in tables 3 and 4:
TABLE 3 Path and traffic distribution results
Figure BDA0002244450570000101
Figure BDA0002244450570000111
TABLE 4 intersection Signaling scheme
Figure BDA0002244450570000112
Step 1.5: all vehicles are randomly sequenced, departure time is distributed at equal intervals according to the number of departure vehicles in each period, and departure paths of the vehicles are distributed at equal intervals according to the proportion of the number of departure vehicles in each period of each path.
For example, the departure interval of origin-destination pair 19 → 27 is the period duration/number of vehicles departing per period, i.e. 120/28 equals 4.3s, the first vehicle departs at the beginning of the period, the second vehicle departs at the 4.3s of the period, the third vehicle departs at the 8.6s of the period, and so on, the departure time of each vehicle is obtained. And one of every 7 vehicles is assigned to the second path, and assuming that the first vehicle and the remaining six vehicles are assigned to the second path, the first vehicle of the next 7 vehicles is still assigned to the second path.
Step 2: according to the sequence of each vehicle entering the road section in the same-flow traffic flow, the cycle time of the road section which is driven away at the earliest at the downstream intersection is determined, and the conflict is prevented. For example, a 5 th vehicle turning left at the intersection 7 may initially leave the intersection at the 5 th s time of the left turn phase, otherwise a collision with the preceding vehicle may occur.
And step 3: selecting a suitable speed range (V) for each road section according to the length of the road sectionmin,Vmax) Determining the periodic time of each vehicle actually driving off the road section and assigning a sumThe proper longitudinal speed ensures that the vehicle leaves the intersection without stopping.
For example, a 5 th vehicle turning left at the intersection 7 can initially leave the intersection at the 5 th s of the left-turn phase, but the assigned speed V > VmaxNot meeting the speed requirement, and only at this time, the speed V ismaxDriving off the intersection at a certain moment after 5s at the earliest; and if the 5 th left-turn vehicle can leave the intersection at the 5 th s moment of the left-turn phase, the speed of the road section is distributed according to the time so as to ensure that the vehicle passes through without stopping.
The invention is not the best known technology.
The above embodiments are merely illustrative of the technical ideas and features of the present invention, and the purpose thereof is to enable those skilled in the art to understand the contents of the present invention and implement the present invention, and not to limit the protection scope of the present invention. All equivalent changes and modifications made according to the spirit of the present invention should be covered within the protection scope of the present invention.

Claims (8)

1. A network traffic flow double-layer control method in a full-automatic driving environment is characterized by comprising the following steps:
c1, constructing a set of linear programming model aiming at minimizing the maximum time required by finishing all origin-destination opposite traveling to obtain the departure time, the traveling path and the timing scheme of each signalized intersection of the automatic driving vehicle at the upper layer; the method specifically comprises the following substeps:
c1.1, constructing a road network topology and a network traffic flow set, wherein the road network topology and the network traffic flow set comprise an intersection set I, a road network node set N, a road section set A, an origin-destination set W and a phase in-out road section matching set AP;
c1.2, investigating to obtain various model parameters including the road section length laOrigin-destination fixed traffic demand NwMinimum and maximum values of the period duration Cmin,CmaxMinimum and maximum phase duration gmin,gmaxNumber of channelized lanes per intersection phase k
Figure FDA0002811825420000011
Saturated headway hs；
c1.3, calculating the shortest path length between each pair of origin-destination pairs by utilizing Dijkstra algorithm
Figure FDA0002811825420000012
Determining the path number r and the path length control parameter beta between each pair of origin-destination pairs;
c1.4, solving the linear programming model to obtain a timing scheme of each signalized intersection in the network;
c1.5, randomly sequencing all vehicles, distributing departure time at equal intervals according to the number of departure vehicles in each period, and distributing departure paths of the vehicles at equal intervals according to the proportion of the number of departure vehicles in each period of each path;
c2, controlling the longitudinal speed of the automatic driving vehicle on each road section at the lower layer, and realizing that all vehicles on the road network can pass through the intersection without stopping;
c3, in a full-automatic driving environment, all vehicles travel according to the travel route obtained in the step c1 and the distributed travel time, and the stable state of the network traffic flow can be realized by adopting the longitudinal speed of the step c2 for driving; in this steady state, traffic flow on all road segments exhibits a periodic characteristic, and vehicles may pass through without stopping at all signal intersections.
2. The network traffic flow double-layer control method in the full-automatic driving environment according to claim 1, characterized in that: in step c1, the linear programming model aiming at minimizing the maximum time required for completing all origin-destination trips comprises a departure time distribution module for controlling a departure time of the vehicle, a trip path distribution module for controlling a trip path of the vehicle, a signal optimization module for optimizing signal timing, a path-signal phase pairing module for establishing a corresponding relationship between the trip path and an intersection signal phase, and an objective function module for minimizing the maximum time required for completing all origin-destination trips.
3. The network traffic flow double-layer control method in the full-automatic driving environment according to claim 2, characterized in that: the departure time allocation module controls the departure time of the autonomous vehicle by the following constraints:
Figure FDA0002811825420000021
Figure FDA0002811825420000022
Figure FDA0002811825420000023
Figure FDA0002811825420000024
Figure FDA0002811825420000025
Figure FDA0002811825420000026
Figure FDA0002811825420000027
in the formula:
w represents a beginning-to-end set;
Ωwa set of paths representing origin-destination w;
i represents a certain intersection;
k represents the intersection phase number;
w represents a certain alignment, W belongs to W;
r denotes a path set ΩwIn one path, r ∈ Ωw；
Figure FDA0002811825420000028
Representing the number of vehicles going out by the origin-destination w per period selected path r;
Figure FDA0002811825420000029
is a binary variable and is used for judging whether the r path of the origin-destination pair w passes through the k phase of the intersection i,
Figure FDA00028118254200000210
the r path representing the origin-destination w passes through the k phase of the intersection i, otherwise, the r path does not pass through the intersection i;
Figure FDA00028118254200000211
indicates the number of vehicles passing through the phase k at the intersection i per cycle on the r path of the origin-destination pair w,
Figure FDA00028118254200000212
when in use
Figure FDA00028118254200000213
Then
Figure FDA00028118254200000214
Otherwise
Figure FDA00028118254200000215
M is a large natural number which ensures that the number of vehicles which pass through the phase k at the intersection i in each period on the r path of the origin-destination point w does not exceed the number of vehicles which depart from the path in each period
Figure FDA00028118254200000216
nwRepresenting the number of vehicles departing per cycle of origin-destination w;
Figure FDA00028118254200000217
representing the number of lanes channelized to the k phase at the intersection i;
Figure FDA0002811825420000031
green time representing the phase k at the intersection i;
hsrepresenting a saturated headway;
constraints (1) - (5) indicate that the number of vehicles arriving at the phase k of the intersection i per cycle does not exceed the allowable traffic capacity; constraint (6) means that the number of vehicles departing from origin-destination point w per period is equal to the sum of the number of vehicles departing from all paths, and the vehicles depart at equal intervals per period; the constraint (7) is an integer constraint.
4. The network traffic flow double-layer control method in the full-automatic driving environment according to claim 2, characterized in that: the travel path distribution module controls the travel path of the automatic driving vehicle through the following constraints:
Figure FDA0002811825420000032
Figure FDA0002811825420000033
Figure FDA0002811825420000034
Figure FDA0002811825420000035
Figure FDA0002811825420000036
Figure FDA0002811825420000037
Figure FDA0002811825420000038
Figure FDA0002811825420000039
Figure FDA00028118254200000310
in the formula:
n represents a road network node set, which comprises an origin-destination point set I' and an intersection set I, subscripts u and v are different nodes of a road network, and u, v belong to N and u is not equal to v;
Figure FDA00028118254200000311
indicates the order of the node v on the path r when
Figure FDA00028118254200000312
Indicating that node v is not on path r, where
Figure FDA00028118254200000313
Indicating the order of origin (o), (w) of origin (w);
Figure FDA00028118254200000314
is a binary variable which indicates whether the path r passes through the section vu or not when
Figure FDA00028118254200000315
Representing that the path r passes through the section vu, otherwise it does not pass;
Figure FDA0002811825420000041
is a binary parameter, which indicates whether the node v is the starting point of the origin-destination path r, when
Figure FDA0002811825420000042
Indicating that the node v is the starting point of the path r, otherwise, not;
Figure FDA0002811825420000043
is a binary parameter, which indicates whether the node v is the end point of the origin-destination path r, when
Figure FDA0002811825420000044
Indicating that the node v is the end point of the path r, otherwise, not;
a is a road segment set in a road network;
lvuthe length of the section vu belongs to A;
Figure FDA0002811825420000045
represents the shortest distance of origin-destination w;
beta is a length control parameter of the origin-destination path r, and a reasonable range is recommended to be (1, 2);
constraint (8) indicates the starting sequence number of each origin to w
Figure FDA0002811825420000046
Is set to 1; constraints (9) and (10) select the road segment through which the path r passes, the constraint (9) representing a path node number
Figure FDA0002811825420000047
Sequentially increasing by 1, the constraint (10) numbering nodes not on path r sequentially
Figure FDA0002811825420000048
Set to 0; constraints (11) and (12) prevent loops from occurring; constraints (13) and constraints (14) ensure connectivity of the paths; constraints (15) ensure the reasonability of the paths, preventing the length of the allocated paths from being much greater than the length of the shortest path; constraint (16) limiting
Figure FDA0002811825420000049
Is a binary variable.
5. The network traffic flow double-layer control method in the full-automatic driving environment according to claim 2, characterized in that: the signal optimization module performs signal timing optimization through the following constraints:
Figure FDA00028118254200000410
Figure FDA00028118254200000411
Figure FDA00028118254200000412
Figure FDA00028118254200000413
Figure FDA00028118254200000414
Cmin≤C≤Cmax (22)
Figure FDA00028118254200000415
Figure FDA00028118254200000416
in the formula:
Figure FDA0002811825420000051
respectively the green time of each phase at the intersection i, and the phases are numbered according to the NEMA phase structure;
c represents the signal period duration;
Cmin,Cmaxrespectively representing the minimum and maximum values of the signal period;
gmin,gmaxrespectively representing the minimum and maximum values of the phase duration;
constraints (17) - (20) indicate that the green light durations of the paired phases are equal; constraint (21) means that the sum of the phase green duration of the same phase ring equals the signal period; constraints (22) and (23) limit cycle C and phase duration
Figure FDA0002811825420000052
The value range of (a); constraining (24) phase duration
Figure FDA0002811825420000053
Is an integer variable.
6. The network traffic flow double-layer control method in the full-automatic driving environment according to claim 2, characterized in that: the path and signal phase pairing module establishes a corresponding relation between a travel path and an intersection signal phase through the following constraints;
Figure FDA0002811825420000054
Figure FDA0002811825420000055
Figure FDA0002811825420000056
Figure FDA0002811825420000057
in the formula:
a-(i, k) an entry leg representing a k phase at intersection i;
a+(i, k) an exit road segment representing a k phase at i intersection;
when a certain path r of the origin-destination pair w passes through an inlet-outlet road section corresponding to the k phase of the intersection i at the same time, the vehicle which selects the path r to travel passes through the intersection i at the k phase, namely
Figure FDA0002811825420000058
Then
Figure FDA0002811825420000059
Otherwise, the path r does not pass through the k phase at the i intersection, i.e.
Figure FDA00028118254200000510
7. The network traffic flow double-layer control method in the full-automatic driving environment according to claim 2, characterized in that: the objective function module achieves the minimum maximum time required for completing all origin-destination opposite trips through the following constraints:
max rm
Figure FDA00028118254200000511
Figure FDA0002811825420000061
in the formula:
rm represents the minimum value of the reciprocal of the number of cycles required for completing the travel demand at all the origin-destination pairs;
rmwrepresenting the reciprocal of the number of cycles required for origin-destination pair w to complete its fixed travel demand;
Nwrepresenting a fixed travel demand of origin-destination w;
the objective function maxrm maximizes the minimum value of the reciprocal of the number of cycles required for all the origin-destination pairs to complete the travel demand, and is equivalent to minimizing the maximum time required for all the origin-destination pairs to complete the travel demand, the constraint (29) represents the reciprocal of the number of cycles required for the origin-destination pair w to complete the travel demand, and the constraint (30) represents the minimum value of the reciprocal of the number of cycles.
8. The network traffic flow double-layer control method in the full-automatic driving environment according to claim 1, characterized in that: in the step c2, a calculation formula of the shortest path length required for realizing the non-stop passing through the intersection through the longitudinal speed control is given, and on the section meeting the shortest path length, the reasonable speed is selected to ensure that the automatic driving vehicle on the section can pass through the intersection without stopping, and the calculation formula of the shortest path length is as follows:
Figure FDA0002811825420000062
in the formula:
Figure FDA0002811825420000063
representing the length of the shortest path segment required by controlling the longitudinal speed so as to pass through the intersection without stopping;
Vmin,Vmaxrespectively representing the minimum and maximum speeds allowed for the section vu.
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