I'm new to OSM and would like to know if my approach for finding the next intersection ahead is possible when doing it offline.
The goal is to get the coordinates (latitude/longitude) of the next intersection on the street I'm currently driving on. For that I have my actual position (lat/lon coordinates) and heading (w.r.t. the north-pole) at disposition.
My current approach right now is to first use my coordinates for getting the name of the street/way/trace in which I am driving; then use that name for knowing which are the next intersections on that street (to both sides); and then use the heading for knowing which direction is the one I should pay attention to.
Once I have the intersection, I would get its coordinates and continue with the program.
My questions are then, is it possible to do all of that offline, i.e. with a .osm file (or similar)?
And, do you know a better approach for getting the coordinates of the next intersection ahead?
Thanks a lot in advance!
PS. I was able to get the name of the street by using nominatim and to get all the intersections of a street by using Overpass turbo, but this solutions would need internet; or is there a way of using them offline?
Related
I have a high volume dataset with keys like this:
lat:6.897585,
long:52.785805,
speed:12,
bearing:144
Basically it is a dataset of records of various trips on cars. The data was stored every few seconds during each trip. The main goal of this project is to be able to visualize only u-turns (turn arounds) on a map. But for now, I am trying to at least show the data on specifc roads. For that, I am using Overpass API
With the help of Overpass Turbo, I can get a dataset with all the roads I need.
However, in the dataset, the road's geometry is represented with LineString type.
My question is, How can I get a bounding box(es) of the roads from Overpass API, so later on, I can display events that happened only on the given roads? Or maybe you have a better solution on how to achieve this?
A bounding box wouldn't be very helpful here, as using it to filter your points would show everything that falls within the box (which could include other nearby roads)
It sounds like getting a buffer around a linestring might get you closer, but could still include points that are within the buffer but not on the road you are inspecting.
The smarter way to do this would be to assign each event to a road segment using some logic based on their attributes/properties, so you don't have to depend on a spatial filter.
I have an iOS app that is using the Google Maps SDK. I track a user as they walk or run then use those coordinates to plot their course along the road using snap to roads.
I have found however the snap to roads uses the direction of the road to plot the course so when it comes to roundabouts the course follows this around even if the user was on the inside of the block.
Is there a way to use snap to roads (or directions) that allows for walking tracks and follows the shortest distance?
Thanks
Looking at the documentation, snap to road is not for walking...
The snapToRoads method takes up to 100 GPS points collected along a route, and returns a similar set of data, with the points snapped to the most likely roads the vehicle was traveling along.
but well.. what you can do it to compare the points, and if the returned points are "some" distance faraway then the original point, you know that this points should be inside the block.
Let's say I have a lot of JSON data relating to intersections and their geolocations.
I have an app where the user uses his or her current location, and I want to be able to figure out what block they're on (i.e. the street they're on, and between what two cross streets). What's the best way to do this? Is there a good way?
Example: I get the user's geolocation, reverse-geocode it into 435 W. 42nd st. Using that data, I want to know that the user is between 9th ave and 10th ave on 42nd st.
Any help is much appreciated!
You'll need to have the geolocations of each of the intersections, blocks or whatever you want to relate the user position to. Once you have that information, you can easily find the nearest intersections to the user's current geolocation.
If all of the geolocation information is in your JSON data, then work only in geolocations (don't reverse geocode) until you've determine the nearest intersections, etc.
You'll likely do best to convert your JSON data to a database so you can query more easily.
I have a series of nature reserves that need to be plotted, as polygon overlays, on a map using the coordinates contained within KML data. I’ve found a tutorial on the Apple website for displaying KML overlays on map instances.
The problem is that the reserves vary in size greatly - from a small pond right up to several hundred kilometers in size. As a result I can’t use the coordinates of the center point to find the nearest reserves. Instead I need to calculate the nearest point of the reserves polygon to find the nearest one. With the data in KML - how would I go about trying to achieve this?
I've only managed to find one other person ask this and no one had replied :(
Well, there are a couple different solutions depending on your needs. The higher the accuracy required, the more work required. I like Phil's meanRadius parameter idea. That would give you a rough idea of which polygon is closest and would be pretty easy to calculate. This idea works best if the polygons are "circlish". If the polygon are very irregular in shape, this idea loses it's accuracy.
From a math standpoint, here is what you want to do. Loop through all points of all polygons. Calculate the distance from those points to your current coordinate. Then just keep track of which one is closest. There is one final wrinkle. Imagine a two points making a line segment that is very long. You are located one meter away from the midpoint of the line. Well, the distance to these two points is very large, while, in fact you are very close to the polygon. You will need to calculate the distance from your coordinate to every possible line segment which you can do in a variety of manners which are outlined here:
http://www.worsleyschool.net/science/files/linepoint/distance.html
Finally, you need to ask yourself, am I in any polygons? If you're 10 meters away from a point on a polygon, but are, in fact, inside the polygon, obviously, you need to consider that. The best way to do that is to use a ray casting algorithm:
http://en.wikipedia.org/wiki/Point_in_polygon#Ray_casting_algorithm
I'd like to know (from a high level view) what would be required to take a pdf floor plan of a building and determine where exactly you are on that floor plan using GPS coordinates? In addition to location, the user would be presented with a "turn by turn" directions to another point on the map, navigating down hallways, between cubicles, etc.
Use case: an iPhone app that determined a user's location and guided them to a conference room or person's office in the building.
I realize that this is by no means trivial, but any help is appreciated. Thanks!
It's an interesting problem. When you're using Core Location, you're not necessarily using GPS. Using WiFi and cell tower triangulation, you can get pretty good location results. So from Core Location you get a latitude and longitude fix. (You might also get altitude info, since GPS data is 3-dimensional. You also will get an accuracy value.)
So you have lat and lon. You need to map these coordinates to the PDF plan's coordinates. Assuming that the plan is aligned with the latitude and longitude lines, and that you have a lat-long fix for one of the points on the plan, you need to calculate the x-axis scale and y-axis scale. Then it's some calculations to map the lat-long to x-y coordinates on the PDF plan.
GPS may not be accurate enough for this purpose, especially indoors. Assuming errors on
the order of 10 meters, you'll have difficulty determining which floor the user is on.
Here's a neat (?) idea that might work: can you post some "You are here" placards
at various locations around the building? You could label each one with a unique,
machine-readable location code (maybe a QR code or something similar), then take an
image using the camera, have your app read that image and interpret the location code,
and use that instead of GPS to determine the start location.
GPS inside? That's your first -- and biggest -- hurdle.
Next hurdle is knowing the GPS coordinates of at least three points on that PDF to define the plane of of your map in the real world. (The PDF will need to be to scale, of course.)
So that gives you where you are on the PDF. Now you'll need to figure out some way to determine where you can walk (or where you can't) to get directions.