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Time-interval-based feature identification and fast search method for hotspot path

A hotspot path and feature recognition technology, applied to road network navigators and other directions, can solve problems such as not allowing users to choose the time period they are interested in, unfavorable use of frequency roads, and no online query solution.

Active Publication Date: 2013-09-25
GUANGZHOU HKUST FOK YING TUNG RES INST
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

This is obviously not good for those roads that pass through many intersections and are used frequently (such as routes through urban areas)
Also, the roads found by this method may contain road sections that are rarely used, such hotspot paths are meaningless
In addition, this method also does not allow the user to select the period of interest, and does not propose a solution for online query (such as online query of trajectory data)

Method used

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  • Time-interval-based feature identification and fast search method for hotspot path
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  • Time-interval-based feature identification and fast search method for hotspot path

Examples

Experimental program
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Embodiment 1

[0092] Embodiments of the present invention provide a feature recognition method for hotspot paths, such as figure 1 shown. Input parameters include: road network G, historical trajectory collection, starting point v s , destination v d , and the period of interest T. Specifically include the following steps:

[0093] a1. For each historical trajectory, only keep its destination v d before (including v d ), and the part within T.

[0094] a2. Calculate the heat of each road section to reach v through this road section d The number of (filtered) historical trajectories for ;

[0095] a3. For each item from v s to v d The path of , the calculation of its heat is a non-decreasing arrangement of the heat of the road section it passes through;

[0096] a4. Change all from v s to v d The paths of all are sorted according to their popularity, and the most popular path is in the time period T, starting from v s to v d hotspot path.

[0097] The historical trajectory acc...

Embodiment 2

[0116] The embodiment of the present invention provides the basic principle and logical structure of index CFMI. The basic principle of CFMI is to recover a large number of trajectories by reading a small number of dominant trajectories, such as Figure 4 shown. Suppose trajectory Y passes through node v i , with Y (*,vi) Mark trajectory Y to reach v i before (including v i ) sub-trajectories, use Path(Y (*,vi) ) marked Y (*,vi) path passed. For any other path v i The trajectory Y', if either Path(Y (*,vi) ) and Path(Y' (*,vi) ) same, or Path(Y (*,vi) ) is not Path(Y' (*,vi) ), we call Y a node v i dominant trajectory. exist Figure 4 in, v i is a black node in the road network. A total of six trajectories (Y1 to Y6) reach this node. Note that the path traversed by trajectories Y2 and Y3 is included in trajectory Y1, the path traversed by trajectories Y4 and Y5 is contained in trajectory Y6, and the path traversed by Y1 and Y6 before reaching the black node is...

Embodiment 3

[0129] The embodiment of the present invention provides a method and process for creating a heat map, such as Figure 6 shown. Input road network G(V, E), destination v d And the time period T of interest, the heat map G f The specific steps to create are as follows:

[0130] c1. Use the adjacency matrix FG to represent based on (v s , v d , T) heat map G f , all elements in FG are initialized to 0;

[0131] c2. Look up the index CFMI and return two sets: the track record set TR and the dominant track record set DOM. Among them, the set TR stores all the processes (v d , T) is not empty after filtering (that is, the trajectory has passed v in T d ) trajectory information, including (tid, t start , did, sloc), note that tid is the unique identifier of the trajectory; the set DOM stores the information of the dominant trajectory of all the trajectories in the set TR, including (did, len), where did is the only identifier of the dominant trajectory, and len is the arriva...

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Abstract

The invention discloses a feature identification and fast search method for a hotspot path based on route big data, relates to a network path searching method and in particular relates to a method for performing hotspot path identification and search in a road network according to historical route big data. The invention provides a set of core features of a hotspot path and the feature identification method of the hotspot path. The method comprises a vector markup method for path heat and a ranking mechanism based on the path heat; an index mechanism is provided, so that the frequency of query on the route big data and the cost of input / output (I / O) of a disk in the process are reduced. Moreover, the method for rapidly querying the hotspot path based on the time interval comprises the following steps of: determining the starting point, destination and interested time interval and calculating the hotspot path, which meets the conditions, according to the historical route big data. The reasonable definition of the hotspot path is given, the hotspot path query at any time interval is provided, and the method is an important supplement to traditional path query methods and can well provide core technical support for various services based on positions.

Description

technical field [0001] The invention relates to a method for searching a network path, in particular to a method for identifying and searching a hotspot path in a road network by using big data of historical trajectories. Background technique [0002] In network path search, the optimal path usually refers to the one with the shortest weighted path length among all the paths from the origin to the destination. According to the different meanings of link weights in the road network, the optimal path query can evolve into the calculation of the path with the shortest path length, the shortest travel time, the best toll price, and the lowest energy consumption. In more complex applications, the optimal path can also be the best result after comprehensive consideration of multiple weights (such as taking into account both the travel time and the charging price). [0003] However, in many application scenarios, these route query techniques based on optimal weights cannot meet th...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01C21/34
Inventor 罗吴蔓谭浩宇陈雷倪明选
Owner GUANGZHOU HKUST FOK YING TUNG RES INST
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