获取路线的算法

发布于 2024-12-23 02:43:18 字数 756 浏览 0 评论 0原文

我有一个沿 gpx 路线按距离排列的点组成的。我想用它来根据我拥有的基础轨迹数据生成方向。它工作得很好,只是数据不准确会导致 gpx 轨道上的缓冲区找不到任何踪迹的一些间隙。如果间隙小于某个单位,我想忽略这些部分。

=========================
  miles  | nearest trail
=========================
   1     |   a
   2     |   a
   3     |   a
   4     |   none *assume it is actually 'a' 
   5     |   a
   6     |   a
   7     |   none
   8     |   none
   9     |   none
   10    |   b    *assume it is actually 'none'
   11    |   none
   12    |   none
   13    |   c
   14    |   c
   15    |   c

我想得到这个:

=====================
 trail   |  travel for
=====================
   a     |   6 miles
   none  |   6 miles
   c     |   3 miles

当我不断遇到问题时,我正在寻找一些关于如何做到这一点的建议。我目前有 mysql 表中的数据并使用 php。

I have a consisting of points along a gpx route by distance. I want to use this to generate directions based upon the underlying trail data I have. It works great except that the inaccuracies of the data cause some gaps where the buffer on the gpx track doesn't find any trails. I want to ignore these sections if the gap is smaller than a certain unit.

=========================
  miles  | nearest trail
=========================
   1     |   a
   2     |   a
   3     |   a
   4     |   none *assume it is actually 'a' 
   5     |   a
   6     |   a
   7     |   none
   8     |   none
   9     |   none
   10    |   b    *assume it is actually 'none'
   11    |   none
   12    |   none
   13    |   c
   14    |   c
   15    |   c

I want to get this:

=====================
 trail   |  travel for
=====================
   a     |   6 miles
   none  |   6 miles
   c     |   3 miles

I am looking for some suggestions on how to do this as I keep running into problems. I currently have the data in a mysql table and am using php.

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评论(2

魂牵梦绕锁你心扉 2024-12-30 02:43:18

您可以使用隐马尔可夫模型。如果你给它提供之前在轨道 y 上之后在轨道 x 上的概率(因此 x=y 的概率将非常高和低),以及当实际在轨道 x 上时记录轨道 y 的概率(这将是x=y 时较高,y=none 时较低,否则较低),您可以根据 维特比算法

You could use a Hidden Markov model. If you feed it the probabilities of being on track x after being on track y previously (so the probability for x=y would be pretty high and low otherwise), and the probability of recording track y when actually on track x (which would be high for x=y, lowish for y=none, and low otherwise), you can calculate a most probable actual path based on the observations with the Viterbi algorithm.

爺獨霸怡葒院 2024-12-30 02:43:18

本质上,听起来您需要一张地图,具体来说,最短路径地图。听起来你有一些代码,但如果不发布它,我就无话可说。

Essentially it sounds like you need a map, a shortest path map to be specific. It sounds like you have some code, but without posting it there is not much I can say about it.

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