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Virtual vehicle routing method applicable to large-scale traffic flow simulation

A virtual vehicle and traffic flow technology, applied in traffic control systems, road vehicle traffic control systems, special data processing applications, etc., can solve the problem of a large amount of storage space, reduce repeated path calculations, and save shortest path calculation time Effect

Active Publication Date: 2011-05-11
TONGJI UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, to form a representative path library requires a large amount of storage space, because the number of all paths on a road network with tens of thousands of nodes is in the hundreds of millions or even billions, and the average length of each path is hundreds of road sections long.
In this case it is unacceptable to pre-store even a tenth of the path

Method used

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  • Virtual vehicle routing method applicable to large-scale traffic flow simulation
  • Virtual vehicle routing method applicable to large-scale traffic flow simulation
  • Virtual vehicle routing method applicable to large-scale traffic flow simulation

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0027] The invention proposes to imitate the routing mode of the computer network, and store the marking method of the next hop of the path into the routing table of each node. When the vehicle travels to each node, it queries the routing table of the node, in which the ID of the next-hop node to reach the destination can be found, so as to realize the entire routing. Such as figure 1 shown.

[0028] The specific method is: first select a pair of OD points, check whether there is the next hop information of point D in the routing table of point O, if there is, move according to this target, otherwise calculate the entire path, and decompose and store the path into each relevant routing table.

[0029] The biggest advantage of this path generation algorithm is that it can significantly save the shortest path calculation time for a large number of vehicles, because the path results calculated first can often be used by subsequent calculations.

[0030] This method also has gr...

Embodiment 2

[0034] Such as figure 2 As shown, the left figure is a schematic diagram of a simple road network with 5 road nodes, and the right figure is a schematic diagram of the shortest path with road node A as a single source.

[0035] If the shortest path from point A to four points B, C, D, and E is:

[0036] A-B: A-B.

[0037] A-C: A-B-C.

[0038] A-D: A-B-D.

[0039] A-E: A-B-D-E.

[0040] Then, after processing and merging, only the lines [2]A-C: A-B-C and lines [4]A-E: A-B-D-E are left to be processed by the system, which avoids a lot of repeated calculations and improves efficiency and performance.

[0041] The next step of determining the endpoints of all lines is a continuation of the previous step of processing and merging lines. It takes point C and point E in the above example as endpoints. Because point B and point D are included in line [2] or line [4], point B and point D will not be considered as endpoints in the following processing, but only participate in the...

Embodiment 3

[0063] A virtual vehicle routing method suitable for large-scale traffic flow simulation, the method comprising:

[0064] - store the marking method of the next hop of the path into the routing table of each node;

[0065] - When the vehicle travels to each node, query the routing table of the node; if the ID of the next hop node to reach the destination can be found in the table, then move according to this target, so as to realize the entire route; otherwise, calculate the entire route Path, and decompose and store the path into each related routing table.

[0066] In the generation and update of the routing table, a distributed solution method is used to divide the road network according to the number of processors. Each processor processes the local routing table, and then multiple processors interact to synthesize the routing table, which can speed up the global road network routing table. calculate.

[0067] If the road between node A and node B is interrupted, the Dij...

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Abstract

The invention discloses a virtual vehicle routing method applicable to large-scale traffic flow simulation, which comprises the following steps: storing paths in the routing table of each node in a next hop marking method; when a vehicle reaches one node, looking up the routing table of the node; if the next hop node ID which wants to reach the destination can be found in the table, moving in accordance with the target to finish the whole routing; and otherwise, calculating the whole path, decomposing the path and storing the path into each relevant routing table. By using a table lookup modeto reduce the repeated path calculation, the invention can obviously save a lot of time for calculating the shortest path of the vehicle; by using the dynamic variation of the table to characterize dynamic road conditions, the method has big advantages in path calculation of the dynamic road net; and in the path inquiring mode, the update of the optimal path completely depends on the periodic update of the routing table, and the update mode of the optimal path is similar to the computer network routing update mechanism.

Description

technical field [0001] The invention belongs to the technical field of intelligent transportation, relates to a traffic simulation method, in particular to a virtual vehicle routing method suitable for large-scale traffic flow simulation. Background technique [0002] In the existing traffic simulation system, the simulated vehicles often do not follow the shortest path, or drive randomly, or make selective turns at the intersection according to the flow distribution. The driving of vehicles in these simulation methods is not a "rational" behavior. Tracking a simulated vehicle alone will often cause the vehicle to "circle" in a small area, which is very unfavorable for simulation experiments based on vehicle rational behavior. For example, correct results cannot be obtained when investigating changes in traffic flow when a road section is blocked. Therefore, the vehicle in the simulation system should travel in a rational way (shortest path). [0003] However, the calculati...

Claims

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Application Information

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IPC IPC(8): G08G1/00G06F17/50
Inventor 蒋昌俊张栋良陈闳中闫春钢丁志军张亚英
Owner TONGJI UNIV
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