CN113012450B - No-signal-lamp intersection intelligent vehicle passing decision method based on constraint tree - Google Patents
No-signal-lamp intersection intelligent vehicle passing decision method based on constraint tree Download PDFInfo
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- G08G1/00—Traffic control systems for road vehicles
- G08G1/07—Controlling traffic signals
- G08G1/081—Plural intersections under common control
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- G08G1/20—Monitoring the location of vehicles belonging to a group, e.g. fleet of vehicles, countable or determined number of vehicles
- G08G1/207—Monitoring the location of vehicles belonging to a group, e.g. fleet of vehicles, countable or determined number of vehicles with respect to certain areas, e.g. forbidden or allowed areas with possible alerting when inside or outside boundaries
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Abstract
The invention provides a constraint tree-based network systemA signal lamp intersection intelligent vehicle passing decision making method comprises the steps of 1, receiving vehicle information through a vehicle infrastructure interconnection system (V2I), and when an intelligent internet vehicle drives into a communication area, establishing connection between a roadside intelligent body arranged at an intersection accessory and a vehicle so as to receive motion state information of the vehicle when the vehicle enters the communication area, wherein the motion state information comprises a position x of the roadside intelligent bodyi(t), velocity vi(t); step 2, determining the passing sequence of all N vehicles in the communication area; step 3, determining a target equation of each vehicle; and 4, step 4: and (3) combining the node distribution obtained in the step (2) with the target equation obtained in the step (3) to form a constraint tree of the traffic decision result of the intersection without the signal lamp. The signal lamp-free intersection intelligent vehicle communication decision method based on the constraint tree can adapt to a time-varying traffic flow scene, avoids a complex optimization solving method and ensures the high efficiency of the decision process.
Description
Technical Field
The invention relates to a passing method of intelligent vehicles, in particular to a no-signal-lamp intersection intelligent vehicle passing decision method based on a constraint tree.
Background
The signal lamp-free intersection represented by the intersection of the roads in the villages and towns is a section where traffic accidents are easy to occur, and the difficulty is how to realize safe passing by enabling vehicles to cooperate with one another. With the development and landing of the intelligent internet technology, the intelligent vehicle can utilize the vehicle-vehicle and vehicle infrastructure interconnection system communication technology carried by the intelligent vehicle, and the possibility is provided for realizing multi-vehicle cooperation at the intersection without the signal lamp.
The traffic decision is a main problem of multi-vehicle cooperation at the intersection without the signal lamp, and the purpose of the traffic decision is to obtain a control target for subsequent vehicle control. The existing research can be mainly divided into two types, one is that all vehicles driving to an intersection are regarded as a same virtual queue, and the obtained decision result is a uniform expected vehicle distance, and the method is not suitable for traffic flow change scenes, for example, when the initial distance between the vehicles is too large, the uniform expected vehicle distance is set, so that the following vehicles generate unnecessary pursuit; and secondly, conflict-free optimization adjustment is carried out on the expected arrival time of all vehicles, so that the overlapping of time of the vehicles occupying conflict areas is avoided.
Disclosure of Invention
The invention solves the traffic decision problem of the intelligent vehicle at the intersection without the signal lamp, gives the sequence and the traffic mode of the vehicle driving to the intersection, and gives the sequence and the traffic mode as decision results.
In order to achieve the purpose, the invention adopts the following technical scheme: a no-signal-lamp intersection intelligent vehicle passing decision method based on a constraint tree is characterized by comprising the following steps:
step 3.1, determining the front vehicle of the sequence of each vehicle;
3.2, calculating the distance between the ith vehicle and the vehicle before the sequence;
3.3, judging the constraint type according to the initial inter-vehicle distance between the ith vehicle and the vehicle before the sequence;
3.4, generating a specific target equation according to the constraint type;
and 4, step 4: and (3) combining the node distribution obtained in the step (2) with the target equation obtained in the step (3) to form a constraint tree of the traffic decision result of the intersection without the signal lamp.
The invention has the beneficial effects that:
1. the signal lamp-free intersection intelligent vehicle communication decision method based on the constraint tree can adapt to a time-varying traffic flow scene, avoids a complex optimization solving method and ensures the high efficiency of a decision process.
2. The invention creatively expresses the passing sequence and the passing mode decision result of the complex scene in the form of the constraint tree, and provides a new idea for the decision analysis of the intersection without the signal lamp;
3. according to the invention, corresponding passing modes and target equations thereof are set according to the difference of the initial inter-vehicle distances of the vehicles, so that the reasonability of vehicle passing decisions in a scene of traffic flow change is improved, unnecessary pursuit of distant vehicles is avoided on one hand, and the driving economy of the vehicles is improved, and queue driving in a local area is realized on the other hand, so that the safety and the passing efficiency of the intersection are improved.
Drawings
FIG. 1 is a schematic view of a road driving at an intersection without signal lamps;
FIG. 2 is a schematic diagram of a conflict relationship;
FIG. 3 is a general flow chart of a method;
FIG. 4 is a flow chart of a method of determining a target equation;
FIG. 5 is a constraint tree diagram;
detailed description of the preferred embodiments
The technical scheme of the invention is explained in detail in the following with reference to the attached figures 2-4.
As shown in fig. 2-4, the embodiment provides a no-signal intersection intelligent vehicle passing decision method based on a constraint tree, which includes two levels, wherein the upper level is a passing sequence level, and a no-conflict passing sequence is obtained; the lower layer is a passing mode layer, and a passing mode expected by the vehicle is obtained, wherein the passing mode comprises an expected inter-vehicle distance type and an expected speed type. In the embodiment, the decision result is represented in a form of a constraint tree, namely, the node distribution of the constraint tree represents the traffic sequence of the vehicle, and the target equation of the constraint tree represents the traffic mode of the vehicle. The method specifically comprises the following steps:
FIG. 1 illustrates a typical turn-signal-free intersection scenario, where vehicle position x at time ti(t) is defined as: distance of vehicle from communication zone boundaryWhen not entering the communication zone xi(t) is negative, x at the border of the communication zonei(t) is 0, once entering the communication area, until x is reached after the communication area is exited againi(t) is a positive number; where the subscript i represents the ith vehicle, the embodiment describes the decision result in the form of a constraint tree, where the nodes represent each vehicle, the distribution of the nodes represent the traffic order, and the objective equation represents the expected traffic pattern.
step 2.1, defining the ith vehicle as the ith node, and determining the passing sequence of each vehicle from 1 to N for i;
2.2, if the 1 st vehicle passes through the 1 st communication area, placing the node 1 in the first layer of the constraint tree;
step 2.3, when a 2 nd vehicle enters the communication area, if the 2 nd vehicle and the 1 st vehicle do not have cross conflict, confluence conflict or diversion conflict, the 2 nd vehicle and the 1 st vehicle can simultaneously pass through the intersection communication area, and the node 2 is placed on the first layer of the constraint tree; if the 2 nd vehicle and the 1 st vehicle have cross collision, confluence collision or diversion collision, the 2 nd vehicle passes through the communication area after the 1 st vehicle, and then passes through the communication area, and at the moment, the node 2 is placed on the second layer of the constraint tree. As shown in particular in fig. 2.
Step 2.4, when the ith vehicle enters the communication area, the previous i-1 vehicle forms a constraint tree with k layers of nodes; if the ith vehicle and all vehicles on the kth layer can simultaneously pass through the intersection communication area, the node i is placed on the kth layer of the constraint tree, and if the node i cannot pass through the intersection communication area, the node i is placed on the (k + 1) th layer of the constraint tree.
wherein the relevant parameters of the ith vehicle are denoted by the subscript i (e.g., x)i(t)), the relevant parameter for the vehicle preceding the sequence of the ith vehicle is denoted by the subscript p (e.g., x)p(t)). The specific process is as follows:
step 3.1, each vehicle determines the vehicle before the sequence, namely: the 1 st vehicle does not have a vehicle before the sequence, and the vehicle before the sequence of the 2 nd vehicle is the 1 st vehicle; when the ith vehicle is not the vehicle which is arrived earliest in the layer, the vehicle before the ith vehicle is the vehicle which is arrived earliest in the layer, and when the ith vehicle is the vehicle which is arrived earliest in the layer, the vehicle before the ith vehicle is the i-1 st vehicle. And by analogy, obtaining the front vehicles of all the N vehicles in sequence.
Step 3.2, calculating the distance between the ith vehicle and the vehicle before the ith vehicle in the sequence
According to the vehicle position x in step 1iAs can be seen from the definition of (t), even if the vehicles are on lanes in different directions, such as i-vehicle traveling from west to east and p-vehicle traveling from north to south in FIG. 1, the inter-vehicle distance between the two vehicles can be calculated according to the following formula
Si(t)＝xp(t)-xi(t)-Lp
Wherein: si(t) represents the inter-vehicle distance of the ith vehicle from the vehicle preceding its sequence at time t, xp(t) represents the position at time t of the preceding train in the sequence, LpRepresenting the body length, x, of the preceding vehicle in the sequencei(t) represents the position of the ith vehicle at time t. When two vehicles run on the same lane, the inter-vehicle distance between the ith vehicle and the vehicle before the sequence is the actual inter-vehicle distance, and when the two vehicles run on different lanes, the inter-vehicle distance is the virtual inter-vehicle distance.
Step 3.3, judging the constraint type according to the initial inter-vehicle distance of the ith vehicle
If S isi(t0) If the distance is more than 30m, the constraint is time type;
if S isi(t0) If the distance is less than or equal to 30m, the constraint is a space type;
wherein t is0Representing the instant at which the ith vehicle enters the communication zone, Si(t0) Represents t0The location of the ith vehicle at time instant.
Step 3.4, generating a specific target equation according to the constraint type, wherein the specific target equation is as follows:
determining constraint equations of all N vehicles in the communication area, wherein the constraint equations correspond to the ith vehicle, and the constraint equations are as follows:
if i is 1, the vehicle is the first vehicle passing through the intersection, and no constraint is required to be established;
if i is more than or equal to 2 and less than or equal to N, if the ith vehicle belongs to the space type constraint, the target equation of the vehicle I is
fi(x，v，t)：xp(t)-xi(t)-Lp＝δi
Wherein f isi(x, v, t) represents this equation, δiRepresenting a desired vehicle spacing; d is a constant.
If the ith vehicle belongs to the time type constraint, recording the flow velocity as a constant VMIf the ith vehicle initial speed vi，0Satisfy the requirement of
vi，0≥VM
It is constrained to
If the ith vehicle initial speed vi，0Satisfy the requirement of
vi，0＜VM
It is constrained to
Wherein, amaxIs constant and represents the maximum acceleration of the vehicle; t isiCan be expressed as follows:
Ti＝max{Ti，min，Ti，ear}
wherein, Ti，minRepresenting the time, T, of the i-th vehicle's acceptable earliest arrival at the intersectioni，earRepresents the time, r, of the ith vehicle to reach the intersection that is the fastest possiblecThe radius of the communication area of the intersection is constant.
And 4, step 4: and (3) combining the node distribution obtained in the step (2) with the target equation obtained in the step (3) to form a constraint tree of the traffic decision result of the intersection without the signal lamp.
As shown in fig. 5, the nodes of the constraint tree represent vehicles, and on one hand, the distribution of the nodes of the constraint tree represents the decision result of the traffic sequence: vehicles on the same layer pass through the intersection at the same time, and pass through different layers from top to bottom. On the other hand, the target equation of the constraint tree represents the decision result of the traffic mode. The whole constraint tree gives a conflict-free passing decision result of the intersection.
An example of an intelligent vehicle passing decision at a signal-free intersection is considered below, wherein a scene is shown in fig. 1 and comprises 7 vehicles in 4 directions;
And 2, determining the passing sequence of all vehicles, thereby obtaining the node distribution of the constraint tree.
And 3, after the node distribution is obtained, determining the front train of the sequence according to the method in the step 3.1, calculating the initial distance between trains according to the method in the step 3.2, judging the constraint type according to the method in the step 3.3, and finally calculating the corresponding target equation according to the initial speed state and the constraint type according to the method in the step 3.4.
And 4, combining the node distribution in the step 2 and the target equation in the step 3 to obtain a constraint tree representing a decision result.
The whole process is an iterative form, that is, each time a new vehicle enters a communication area, the node position and the target equation of the new vehicle are supplemented on the basis of the original constraint tree, so that the constraint tree is updated. The design of the target equation can enable the method to be suitable for a scene with time-varying traffic flow, and meanwhile, the target equation further explains the traffic sequence decision of macroscopic traffic to a control target level and plays a guiding role in subsequent steps, namely vehicle control.
Claims (2)
1. A no-signal-lamp intersection intelligent vehicle passing decision method based on a constraint tree is characterized by comprising the following steps:
step 1, receiving vehicle information through a vehicle infrastructure interconnection system, and establishing connection between a roadside intelligent agent arranged near an intersection and a vehicle whenever an intelligent internet automobile drives into a communication zone, so as to receive motion state information of the vehicle when the vehicle enters the communication zone, wherein the motion state information comprises a position x of the vehiclei(t), velocity vi(t)；
Step 2, determining the passing sequence of all N vehicles in the communication area;
step 2.1, defining the ith vehicle as the ith node, and determining the passing sequence of each vehicle from 1 to N for i;
2.2, if the 1 st vehicle passes through the 1 st communication area, placing the node 1 in the first layer of the constraint tree;
step 2.3, when a 2 nd vehicle enters the communication area, if the 2 nd vehicle and the 1 st vehicle do not have cross conflict, confluence conflict or diversion conflict, the 2 nd vehicle and the 1 st vehicle can simultaneously pass through the intersection communication area, and the node 2 is placed on the first layer of the constraint tree; if the 2 nd vehicle and the 1 st vehicle have cross conflict, confluence conflict or shunting conflict, the 2 nd vehicle passes through the communication area after passing through the communication area after the 1 st vehicle, and at the moment, the node 2 is placed on the second layer of the constraint tree;
step 2.4, when the ith vehicle enters the communication area, the previous i-1 vehicle forms a constraint tree with k layers of nodes; if the ith vehicle and all vehicles on the kth layer can pass through the intersection communication area simultaneously, placing the node i on the kth layer of the constraint tree, and if the node i cannot pass through the intersection communication area, placing the node i on the kth +1 layer of the constraint tree;
step 3, determining a target equation of each vehicle;
step 3.1, determining the front vehicle of the sequence of each vehicle;
the 1 st vehicle does not have a vehicle before the sequence, and the vehicle before the sequence of the 2 nd vehicle is the 1 st vehicle; when the ith vehicle is not the vehicle which is reached earliest in the layer where the ith vehicle is located, the vehicle before the ith vehicle is the vehicle which is reached earliest in the layer where the ith vehicle is located, and when the ith vehicle is the vehicle which is reached earliest in the layer where the ith vehicle is located, the vehicle before the ith vehicle is the (i-1) th vehicle; in this way, the front vehicle of the sequence of all the N vehicles is obtained; the relevant parameters of the ith vehicle are all represented by subscript i, and the relevant parameters of the vehicle before the sequence of the ith vehicle are all represented by subscript p;
3.2, calculating the distance between the ith vehicle and the vehicle before the sequence;
calculating the distance between two vehicles according to the following formula
Si(t)＝xp(t)-xi(t)-Lp
Wherein: si(t) represents the inter-vehicle distance of the ith vehicle from the vehicle preceding its sequence at time t, xp(t) represents the position at time t of the preceding train in the sequence, LpRepresenting the body length, x, of the preceding vehicle in the sequencei(t) represents the position of the ith vehicle at time t;
3.3, judging the constraint type according to the initial inter-vehicle distance between the ith vehicle and the vehicle before the sequence;
if S isi(t0) If the distance is more than 30m, the constraint is time type;
if S isi(t0) If the distance is less than or equal to 30m, the constraint is a space type;
wherein t is0Representing the instant at which the ith vehicle enters the communication zone, Si(t0) Represents t0The distance between the ith vehicle and the vehicle before the sequence is the ith vehicle;
3.4, generating a specific target equation according to the constraint type;
and 4, step 4: and (3) combining the node distribution obtained in the step (2) with the target equation obtained in the step (3) to form a constraint tree of the traffic decision result of the intersection without the signal lamp.
2. The no-signal-light intersection intelligent vehicle passing decision-making method based on the constraint tree as claimed in claim 1, characterized in that: step 3.4: determining target equations of all N vehicles in the communication area, wherein the target equations correspond to the ith vehicle, and the target equations are as follows:
if i is 1, the vehicle is the first vehicle passing through the intersection, and no constraint is required to be established;
if i is more than or equal to 2 and less than or equal to N, if the ith vehicle belongs to the space type constraint, the target equation of the vehicle I is
fi(x，v，t)：xp(t)-xi(t)-Lp＝δi
Wherein f isi(x, v, t) represents the target equation, δiRepresenting a desired vehicle spacing; d is a constant;
if the ith vehicle belongs to the time type constraint, recording the flow velocity as a constant VMIf the ith vehicle initial speed vi，0Satisfy the requirement of
vi，0≥VM
It is constrained to
If the ith vehicle initial speed vi，0Satisfy the requirement of
vi，0＜VM
It is constrained to
Wherein, amaxIs constant and represents the maximum acceleration of the vehicle; t isiCan be expressed as follows:
Ti＝max{Ti，min，Ti，ear}
wherein, Ti，minRepresenting the time, T, of the i-th vehicle's acceptable earliest arrival at the intersectioni，earRepresents the time, r, of the ith vehicle to reach the intersection that is the fastest possiblecThe radius of the intersection communication area is D, and D is a constant.
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| CN108564234B (en) * | 2018-05-08 | 2020-06-02 | 北京航空航天大学 | Intersection no-signal self-organizing traffic control method of intelligent networked automobile |
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