CN114023093B

CN114023093B - Multi-vehicle dynamic evacuation method driven smoothly in short distance

Info

Publication number: CN114023093B
Application number: CN202110999635.7A
Authority: CN
Inventors: 才智; 王涛; 郎琨; 苏醒; 米庆; 郭黎敏
Original assignee: Beijing University of Technology
Current assignee: Beijing University of Technology
Priority date: 2021-08-29
Filing date: 2021-08-29
Publication date: 2024-03-15
Anticipated expiration: 2041-08-29
Also published as: CN114023093A

Abstract

The invention discloses a multi-vehicle dynamic evacuation method driven smoothly in a short distance. In a navigation algorithm based on short-range smoothness assurance, a route search is performed based on an a-algorithm. In the searching process, for the blocked road section, the blocking weight is judged according to the distance from the road section to the vehicle, the real length of the road section is further extended according to the blocking weight to simulate the blocking of the road section, and finally, an optimal path under the current condition can be returned. For multiple vehicle evacuation algorithms based on route diversity. The evacuation sequence of the vehicle is divided mainly by two steps. Step 1: and acquiring a driving path by using a vehicle navigation algorithm ensured by short-distance smoothness. Step 2: according to the route diversity principle, we choose to give priority to planning each time the vehicles with the lowest similarity to the previously evacuated vehicle route. Ensuring that the number of vehicles evacuated in all directions of the road network is relatively uniform.

Description

Multi-vehicle dynamic evacuation method driven smoothly in short distance

Technical Field

The invention belongs to the traffic field, and relates to a multi-vehicle dynamic evacuation algorithm driven by short-distance smooth.

Background

As the number of vehicles in cities increases. Urban road network pressure is continuously increased, and road state changes are more complex. In the continuously changing complex road conditions, how to ensure the travel quality of people according to the real-time state of the urban road becomes a focus of attention. In addition, in large-scale activities, how to orderly evacuate participating vehicles and ensure smooth and balanced road network traffic is an important challenge for activity organization personnel and surrounding road networks. In the navigation algorithm existing at present, an optimal path tends to be acquired according to the state of a road at a certain moment. However, in an actual running, only the condition of a road within a certain range from the vehicle needs to be considered, and for a road outside the range, it is not particularly concerned. Thus, in a sense, only one locally optimal solution needs to be obtained. In addition, in the evacuation process of vehicles, the existing algorithm mainly guides traffic or divides the evacuation sequence of vehicles according to the position information of the vehicles. However, due to the different urban road network structures, the driving routes of the vehicles may also have large differences, so that the conventional method has various defects and drawbacks.

Disclosure of Invention

In order to solve the problem, the invention provides a navigation algorithm based on short-distance smoothness assurance and a multi-vehicle dynamic evacuation algorithm based on route diversity. In the navigation algorithm, when the driving route of the vehicle is acquired, a threshold is set to consider only the road condition information within the threshold range from the starting point, and the real-time state of the road beyond the threshold is not considered because of the far distance from the current position. Thereby reducing the time of algorithm operation in ensuring the effect of local smoothness. And in the running process of the vehicle, the algorithm detects the road condition within the threshold range in real time, and ensures that the road condition is smooth, so that the overall planning effect is guaranteed to be the best. For the evacuation problem of multiple vehicles, a multiple vehicle dynamic evacuation algorithm based on route diversity is provided. In the evacuation process, the driving tracks of all vehicles are acquired according to a navigation algorithm, and then vehicles with the lowest track similarity with the planned vehicles are selected for priority planning according to track information each time, so that the evacuation sequence of the vehicles is divided.

The invention mainly comprises a vehicle navigation algorithm based on short-distance smooth guarantee and a multi-vehicle dynamic evacuation algorithm based on route diversity. In a vehicle navigation algorithm based on short-distance unblocked guarantee, the blocking in route searching is subjected to weight analysis, and whether the vehicle navigation algorithm needs to be avoided is judged through calculation. For an evacuation algorithm based on route diversity, calculating route similarity of vehicles needing to be evacuated according to the driving route of the vehicles, and ensuring that the route similarity of the currently-started vehicles and the already-started vehicles is the lowest. The implementation of both algorithms will be described in detail below.

The implementation steps of the vehicle navigation algorithm based on the short-distance smooth guarantee are as follows:

step 1: two lists open and close are created for storing the nodes that have been expanded and the nodes that have not been expanded, respectively.

Step 2: the starting node of the driving vehicle is added to the open table.

Step 2.1: and creating nodes according to the actual information of the starting position of the vehicle. Each node here represents an intersection in a road network environment. The data information included in the node includes a distance from the start point of the vehicle to the current position, a distance from the current position to the end point of the vehicle, and indexes of parent and child nodes of the current node. If the node is the starting node, its parent node is empty.

Step 3: and judging and expanding the nodes in the open table, and searching for a target node.

Step 3.1 if the open table is empty, the search fails, otherwise, the first node is fetched from the open table.

And 3.2, judging whether the fetched node is a target node or not, and if so, exiting. If not, continuing expanding the new node by using the node.

And 3.2.1, expanding the child nodes of the nodes according to the topological structure of the road network.

Step 3.2.2 for the newly extended node, its associated data information is first determined. The parent node is the node for expanding the parent node, the distance from the parent node to the target node is expressed as a linear distance, and the parent node can be obtained by calculation through longitude and latitude information.

Step 3.2.3 for a blocked road segment, its blocking weight JW is calculated.

For the realization of the short-distance unblocked guarantee, the following ideas are adopted.

When acquiring a vehicle driving route, only the state of a road within a certain threshold range is considered with emphasis, but the state of the road outside the threshold range is not fully concerned. Thus, the impact weight on the path selection is necessarily different for congestion of different road segments. It is expressed as

Where x represents the distance from the start point to the start point of the link, and θ represents the set threshold range to be considered. From the expression, it can be seen that for a blockage closer to the starting point, the influence coefficient is larger, while for a road segment further away, the influence coefficient is smaller.

Step 3.2.4 simulates the real weight of the road section according to the blocking coefficient and determines the real cost of selecting the next node.

In a real road network, if a road is jammed, the time for a vehicle to pass through the road increases. The method comprises the steps of setting the vehicle speed to be constant in the running process of the vehicle, and when a section of road is congested, adopting a method of prolonging the length of the road to prolong the running time of the vehicle on the road so as to simulate the congestion of the section of road. It is set as:

length _true ＝road.length*(1+k*JW(x))

where k is denoted as the amplification factor.

Thus, for a real road segment, if its road is clear, it is not considered, and if it is blocked, it is to calculate its congestion weight by using the blocking coefficient. And acquiring the actual distance from the starting point to the node by calculating the real weight of the road section and the related data of the father node.

Step 3.2.5 generates a new node using the associated data information.

Step 3.2.6, judging whether the new node is already in the open table, if so, judging whether the heuristic value of the new node is larger than the node already existing in the open table, and if so, updating the state of the node.

Step 3.2.7 determines if the new node is in the close table. If yes, judging the heuristic value of the new node and the heuristic value of the node in the close table. If the heuristic value of the new node is smaller, the new node is added into the open table, and the corresponding element in the Close table is deleted. Otherwise, the processing is not performed.

Step 3.2.8 if the new node does not belong to the open table nor to the close table, it is placed in the open table.

Step 4: for the searched target node, the parent node is continuously accessed by using a backtracking algorithm until the starting position of the parent node is encountered. During this time, the travel route of the vehicle is determined according to an iterative process.

The following describes a multiple vehicle dynamic evacuation algorithm based on route diversity, and the route diversity principle will be described before.

In the vehicle evacuation process, the expected result is that the vehicles are uniformly evacuated in all directions of the evacuation center, so that traffic jam caused by road load and unbalance caused by continuous and repeated vehicle evacuation on one road is avoided. Therefore, a principle of route diversity is proposed, the aim of which is to minimize the overlap of the travel route of the currently evacuated vehicle with the travel route of the already evacuated vehicle. The contents of route diversity will be described in detail below.

For a given start point and end point of vehicle travel, the travel route of the vehicle P is set to be an ordered set of road segments p= [ R ] _p1 ,R _p2 ,R _p3 …R _pp ]The travel route of the vehicle S is an ordered set of road segments s= [ R ] _s1 ,R _s2 ,R _s3 …R _ss ]. Where R represents the set of roads in the road network. The line overlap ratio of two lines is defined as the distance of the overlapping of the road sections. It can be expressed as the following equation:

however, during evacuation of a vehicle, the pressure faced by evacuating a center point road is much greater than that of a road farther from the center point. Therefore, the above road overlap ratio is corrected such that the farther from the evacuation center, the lower the weight of the road is.

Furthermore, the more vehicles to be evacuated, the longer the evacuation time is required. In the latter stages of evacuation, the vehicle initially evacuated must not have reached the end point and must not be far from the evacuation center. Thus, their impact on the current evacuated vehicle is much smaller than on the following vehicles. That is, the evacuation effect of the current vehicle on the following vehicles decreases with an increase in time. The sum of the road RC of the current vehicle and all planned vehicles is derived. Which can be expressed as

Then, it is averaged. Where p denotes a vehicle to be evacuated, and Q denotes a collection of vehicles that have been evacuated.

Furthermore, in one evacuation, if two vehicles are the same as the avg_rc of the planned vehicle, but their target points are not the same distance from the center point, their priorities also need to be considered. Here, the principle of higher priority is selected as closer to the center point. This is because the farther the vehicle is from the center point, the longer it must travel, and the greater the impact on the road network. The shorter the road section which is closer to the evacuation center point is, the shorter the travel time on the road network is, so that the influence on the road network is smaller.

From the viewpoints presented above, theories of route diversity are presented. The expression is as follows:

where sim (p) represents the similarity of the current vehicle p to the route of the planned vehicle set. The smaller the sim value, the weaker the similarity, the more preferably the planning. dis represents the distance of the current vehicle endpoint from the active center point. Maxdis represents the maximum value of the unplanned point vehicle endpoint from the active center point.

In accordance with the above route diversity principle, a multi-vehicle dynamic evacuation algorithm based on route diversity is described below.

Step 1: generating a vehicle to be evacuated, taking an evacuation center as a starting point of the vehicle and randomly generating an evacuation end point.

Step 1.1 for the vehicle generated, the data information contains a start point (i.e. evacuation center), an end point (random generation), and a speed (considered set).

Step 1.2, generating a track route according to the start point and the end point information of the vehicles to be evacuated and the vehicle navigation algorithm for guaranteeing the short-distance smoothness. For a certain vehicle P with determined start and end points, its route may be represented as an ordered road segment set p= [ R ] _p1 ,R _p2 ,R _p3 …R _pp ]. Where R represents the set of roads in the road network.

Step 2: and according to the route diversity principle, sequencing all vehicles to be evacuated in the evacuation sequence.

Step 2.1 first two sets are defined, one for storing all the vehicles to be evacuated unfreshed list and the other for storing vehicles to be evacuated fireshed list for which evacuation order has been planned.

And 2.2, calculating the distances between the end points of all vehicles to be evacuated and the evacuation center.

Step 2.3 if no vehicles have been planned, i.e. the finish list is empty, the vehicle nearest the evacuation center is selected and added to the finish list, while it is deleted from the unfulfilled list.

Step 2.4 when there are vehicles for which the evacuation order has not been determined, selecting a lowest vehicle similar to the current all vehicle routes from the un-ordered set of un-ordered lists using the ordered set of vehicles finish list according to the route diversity principle described above.

Step 2.5 for the selected vehicle, add it to the finish list while deleting it from the unFinishedList.

Step 3: and for the ordered vehicles to be evacuated, evacuating according to the route information of the vehicles and the road state.

Step 3.1, for each vehicle to be evacuated, first acquiring a first road in the route.

And 3.2, judging the state of the road, and if the road is blocked, waiting until the road unblocked party starts to start. If the road is clear, the vehicle is evacuated directly.

Compared with the prior art, the invention has the following advantages:

(1) For the vehicle navigation system with the short-distance smooth guarantee, the system can make corresponding adjustment according to possible sudden accidents in the road in real time, so that serious traffic jam is avoided.

(2) Because the vehicle navigation system ensured by the smooth short distance only considers the road condition in the threshold range, the algorithm searching efficiency can be greatly improved.

(3) For a multiple vehicle evacuation algorithm based on route diversity, it takes less time under comparable evacuation conditions than for an evacuation algorithm based on spatial diversity.

Drawings

Fig. 1 is a flow chart of an implementation of the method.

Fig. 2 is a road network node map.

Fig. 3 is an actual state diagram of the road network.

Fig. 4 is a road network vehicle evacuation flow chart.

Fig. 5 is a schematic diagram of an embodiment.

Detailed Description

The invention is explained and illustrated below in connection with the associated drawings.

The road network data on which the invention is based is road data in three rings of Beijing city.

The following first describes a vehicle navigation algorithm based on short-range smoothness assurance. First, the steps according to fig. 1 are performed. In the following examples, for simplicity and clarity of explanation, the explanation will be based on the road network in fig. 2. Here, the start point of the vehicle is set to a and the end point is set to f, while the de section is assumed to be blocked.

Step 1: open= { }, close= { }

Step 2: open= { a }

Step 2.1: since a is the starting point, its parent node is empty, g (a) =0, h (a) =dis (a, f).

Step 3: the nodes in the open table are searched and expanded.

Step 3.1, fetching node a, then open= { }, close= { a }

Step 3.2.1:a is not equal to f, so node a is extended according to the road network structure.

Step 3.2.2: according to the road network structure, the newly expanded nodes are b and d respectively, and the father nodes are the nodes a, h (b) =dis (b and f) and h (d) =dis (d and f).

Since the road < a, b >, < a, d > is not blocked, g (b) =g (a) +dis (a, b) =20, g (d) =g (a) +dis (a, d) =18.

For ease of description of the algorithm, we will first assume that the newly extended node is e. At this time, congestion occurs due to the < d, e > segment. At this time, the distance from the start point of the road is g (d) =18 of the parent node d

Step 3.2.3: its congestion weight is calculated, where a threshold θ=15 is set.

JW(e)＝1/(1+exp^(18-15))＝0.04742587317756678

Step 3.2.4: and simulating the blockage of the road section by increasing the distance of the road section according to the congestion weight and the amplification factor.

length _true ＝10+(1+10*JW(e))＝14.7

At this time, the actual state of the road network can be represented by fig. 3.

Step 3.2.5: generating a new node from the above information, for node e, g (e) =g (d) +dis (d, e) =18+length _true =18+14.7=32.7, h (e) =dis (h, f), f (e) =g (e) +h (e), and the parent node is d.

For step 3.2.6,3.2.7,3.2.8, the algorithm steps can be performed according to the above corresponding information, and the corresponding states in the open table and close table.

Step 4: when node f is accessed, it is indicated that the endpoint has been reached. At this point backtracking is performed with its parent node. A path may be obtained. I.e. < f, c, b, a >.

Based on the above vehicle navigation algorithm, a multi-vehicle dynamic evacuation algorithm based on route diversity will be described below by taking the example shown in fig. 5 as an example.

Step 1: and generating vehicles, determining evacuation centers and randomly generating target end points of vehicle driving.

Step 1.1: the vehicle information is set according to the above information, and at the same time, the vehicle speed is uniformly set to 20m/s.

Step 1.2, acquiring the driving track information of the vehicle according to the starting point information of the vehicle. The results are shown in the following table.

TABLE 1 vehicle ID and travel route therefor

Step 2: and sorting the vehicles to be evacuated according to the route diversity principle.

Step 2.1: two sets of unfinishedlists are defined for storing vehicles that have not yet been planned. The finish list is used to store vehicles that have been planned. I.e., un finish list = { c_1, c_2, c_3, c_4, c_5, c_6, c_7, c_8, c_9}, finish list = { }.

Step 2.2: the distances from all vehicles to the endpoint are calculated. The results are shown in the following table.

TABLE 2 distance of vehicle end point from start point

Step 2.3: at this time, since the unFinishedList is empty, c_1 nearest to the end point is selected for priority planning. At this time, finnishedlist= { c_1}, un finnishedlist= { c_2, c_3, c_4, c_5, c_6, c_7, c_8, c_9}.

Steps 2.4,2.5 describe the process of dividing the evacuation sequence using the principle of route diversity.

After the first selection of C_1, according to the route diversity, the vehicle with the lowest route similarity with the evacuated vehicles is selected for planning each time.

Route similarity between Table 3 and C_1

At this time, C_2 is selected for planning

Table 4 after c_2 is selected

And C_3 is selected for planning according to the calculation result.

Table 5 after c_3 is selected

Further, c_4 is selected.

Table 6 after c_4 is selected

And selecting C_5, and sequencing the planning of the vehicle according to the data in the table in the later planning.

TABLE 7 planning procedure for subsequent vehicles

And finally, evacuating the vehicles according to the ordered result.

Claims

1. A multi-vehicle dynamic evacuation method driven smoothly in a short distance is characterized in that: the method is realized based on two aspects, namely a vehicle navigation method based on short-distance smooth guarantee and a multi-vehicle dynamic evacuation method based on route diversity;

the implementation steps of the vehicle navigation method based on the short-distance smooth assurance are as follows:

step 1-1: creating two lists open and close for storing the expanded nodes and the nodes which are not expanded respectively;

step 1-2: adding a starting node of the running vehicle to the open table;

step 1-3: judging and expanding nodes in the open table, and searching for a target node;

step 1-4: for the searched target node, continuously accessing the parent node until the starting position of the parent node is touched by using a backtracking algorithm; determining a vehicle driving route according to the iterative process;

the method for realizing the multi-vehicle dynamic evacuation based on route diversity comprises the following steps:

step 2-1: generating a vehicle to be evacuated, taking an evacuation center as a starting point of the vehicle and randomly generating an evacuation end point;

step 2-2: according to the route diversity principle, sequencing all vehicles to be evacuated in evacuation sequence;

step 2-3: for the ordered vehicles to be evacuated, evacuating according to the route information of the vehicles and the road state;

in the step 1-2, the specific implementation process is as follows,

step 1-2.1: creating nodes according to actual information of the starting position of the vehicle; each node here represents intersection information in a road network environment; the data information included in the node includes a distance from the start point of the vehicle to the current position, a distance from the current position to the end point of the vehicle, and indexes of parent nodes and child nodes of the current node; if the node is the starting node, the father node is empty;

in the steps 1-3, the specific implementation process is as follows,

step 1-3.1, if the open table is empty, searching fails, otherwise, the first node is taken out of the open table and added into the close table;

step 1-3.2, judging whether the fetched node is a target node or not, and if so, exiting; if not, continuing expanding the new node by using the node;

step 1-3.2.1, for the above nodes, expanding the child nodes according to the topological structure of the road network;

step 1-3.2.2 for the newly extended node, determining its related data information first; the father node is the node for expanding the father node, the distance from the father node to the target node is expressed as a linear distance, and the father node can be obtained by calculation by using longitude and latitude information;

step 1-3.2.3, calculating the blocking weight JW of the blocked road section;

for realizing the smooth guarantee of short distance, the following ideas are adopted;

when the driving route of the vehicle is acquired, only the state of the road in a certain threshold range is considered, and the state of the road outside the threshold range is not fully concerned; thus, for a blockage of different road segments, the impact weights on the path selection are necessarily different; it is expressed as

Wherein x is the distance from the starting point to the starting point of the road section, and θ is the set threshold range to be considered; as seen from the expression, for a jam closer to the starting point, the influence coefficient is larger, and for a road section farther away, the influence coefficient is smaller;

step 1-3.2.4, simulating the real weight passing through the road section according to the blocking weight, and determining the real cost of selecting the next node;

in a real road network, if a road is blocked, the time for a vehicle to pass through the road is increased; setting the speed of the vehicle to be constant in the running process, and when a section of road is congested, adopting a method for prolonging the length of the road to prolong the running time of the vehicle on the road so as to simulate the congestion of the section of road; the method comprises the following steps:

length _true ＝road.length*(1+k*JW(x))

wherein k is expressed as an amplification factor;

for a real road section, if the road is unblocked, the real road section is not considered, and if the road is blocked, the blocking coefficient is used for calculating the congestion weight; acquiring the actual distance from the starting point to the node by calculating the real weight of the road section and the related data of the father node;

steps 1-3.2.5 generate a new node using the associated data information;

1-3.2.6, judging whether a new node is in an open table, if so, judging whether the heuristic value of the new node is larger than the node existing in the open table, and if so, updating the state of the node;

step 1-3.2.7, judging whether the new node is in a close table; if yes, judging the heuristic value of the new node and the heuristic value of the node in the close table; if the heuristic value of the new node is smaller, adding the heuristic value of the new node into an open table, and deleting the corresponding element in the Close table; otherwise, not processing;

step 1-3.2.8 if the new node does not belong to the open table or the close table, putting the new node into the open table;

in the step 2-1, the specific implementation process is as follows,

step 2-1.1, for the generated vehicles, the data information of the vehicles comprises a starting point, namely an evacuation center, the end point is generated randomly, and the speed is considered to be set;

step 2-1.2, generating a track route according to the start point and end point information of the vehicles to be evacuated and the vehicle navigation ensured by the short-distance smoothness introduced above; for a certain vehicle P with determined start and end points, its route is represented as an ordered set of road segmentsWherein R represents a set of roads in the road network;

in the step 2-2, the specific implementation process is as follows,

step 2-2.1, firstly, defining two sets, wherein one set is used for storing all the vehicles to be evacuated unfinishedLists, and the other set is used for storing the vehicles to be evacuated finishedLists for which evacuation orders are planned;

step 2-2.2, calculating the distances between the end points of all vehicles to be evacuated and the evacuation center;

step 2-2.3 if no vehicles are planned yet, i.e. the finish list is empty, selecting the vehicle nearest to the evacuation center and adding it to the finish list, and simultaneously deleting it from the unffinish list;

step 2-2.4, when there are vehicles with no evacuation sequence determined, selecting a lowest vehicle similar to the current all vehicle routes from the un-divided evacuation sequence set by using the divided sequence vehicle set finish list according to the route diversity principle described above;

step 2-2.5, adding the selected vehicle to the finish list, and deleting the selected vehicle from the unFinishedList;

in the step 2-3, the specific implementation process is as follows,

step 2-3.1, for each vehicle to be evacuated, first acquiring a first road in a route of the vehicle;

step 2-3.2, judging the state of the road, and if the road is blocked, waiting until the road unblocked party starts to start; if the road is clear, the vehicle is evacuated directly.