I have a cost network, but it's not a street mapping network. I know the nodes and edges as I defined them. pgRouting looks like a good choice, but every single example I can find uses Open Street Map as the data. I don't have GPS coordinates. The x1,y1 for nodes makes no sense in my graphs, my nodes have specific ids, not coordinates. The costs aren't calculated from the coordinates, they're assigned by me on the various edges based on domain knowledge specific to my domain.
Are there any examples of how to create a custom network in pgRouting? I'm really struggling because the examples are "and then you use this tool to import OSM data"...which doesn't help me at all.
#Chris Kessel
I don't know if this is still relevant, but it may help others:
Basically, what you need to have is a table with edges, where in column 'source' is the id of a node on one end of the edge and in column 'target' - id of the node on the other end. You also have to have a defined cost for the edge, I'm not sure what this will be for you - usually it's distance or time units.
Ususally this is done with geo info using pgr_createTopology function, but in your case you will need to just create this yourself, I suppose.
I think this link can help you:
https://anitagraser.com/2011/02/07/a-beginners-guide-to-pgrouting/
The answer to the question "Are there any examples of how to create a custom network in pgRouting?" is Yes there are.
Related
I want to calculate a route from A to B using only a subset of the routes available in a city, as long as it is possible (if A or B is not on the subset of roads I still need to calculate the route). I tried to use avoidareas but it's quite difficult to define rectangles to avoid outside of the roads (and I saw somewhere the number of boxes is limited).
Can you please explain what do you mean by "subset of the routes". Do you mean to avoid a particular kind of road?
if you want to always include a certain road(s) you can always use waypoints to direct the route through those roads. Generally, Routing algorithms are designed to "avoid" not "prefer" an area.
Various examples on how to avoid a rectangle(s) is explained here- https://developer.here.com/documentation/routing/topics/example-route-avoiding-an-area.html
How to use a waypoint is explained here - https://developer.here.com/documentation/routing/topics/resource-param-type-waypoint.html
How to avoid a certain road type is explained here - https://developer.here.com/documentation/routing/topics/avoiding-certain-road-types.html
I have a OSM node Id/ latitude-longitude for a point in the road(say point Z). How do I find the previous x points that I need to travel to reach Z in all directions? I was thinking overpass API could help me. But it is able to return points only with tags. I am not able to get it return the node Ids on the road/way.
Can you please suggest any API/tutorial that could help?
if i'm not wrong what you are asking is: given a osm node id with coordinate x and y what are all points to do in order to arrive there from a starting point?
if this is the question well this is a graph oriented question; you should create a grah and then use some algorithm in order to find all the routes between starting point and end point; you should use some graph oriented software.. something like neo4j and spatial contrib (https://github.com/neo4j-contrib/spatial)
In past i built a project where i read an osmfile, create a graph and used A* algorithm; you may give to it a look https://github.com/angeloimm/neo4jAstarTest
I suggest to get started by reading about OSM elements, especially nodes and ways. Afterwards take a look at OSM XML format. It might also help to open an OSM editor (e.g. iD) and to take a look at the raw data.
Nodes don't have any order or "next node" themselves. Nodes can be part of one or multiple ways. Each way references a list of ordered nodes. So you have to look at all ways a node belongs to, then look at the way's node list to determine the previous and next nodes. If the node is at the start or end of a way then you have to look if there are one or more consecutive ways. Consecutive ways share the same node at their start/end.
I have been trying to wrap me head around the personalized page rank algorithm and how it works. I came across this paper which gives this graph:see link to image below with weights calculated by PPR. I am have trouble reproducing the calculations with the models they give.
Can anyone break it down for me to help me wrap me head around the concept?
Thanks!
The paper is a good reference to personalized page rank. Basically my understanding, ppr scores tell you the probability from the source node move to the target node. It is a specific score describe the relationship between specific source and target nodes in the graph.
If you have problem to reproduce the results, you can use networkx in python, load a graph and compute ppr using
networkx.pagerank(graph, personalization={'a':0, 's':1, 'b':0....})
Networkx use power iteration approach to compute ppr, you can get exact result as what shown in the example.
The author of this thesis have c++ code here https://github.com/snap-stanford/snap/blob/master/snap-core/randwalk.h Since this method is random walk based approach, you could not get exactly same results as what shown in the example, but the rank is correct.
Hope that helps.
I have a map with about 80 annotations. I would like to do 3 things.
1) From my current location, I would like to know the actual route distance to that position. Not the linear distance.
2) I want to be able to show a list of all the annotations, but for every annotation (having lon/lat) I would like to know the actual route distance from my position to that position.
3) I would like to know the closest annotation to my possition using route distance. Not linear distance.
I think the answer to all these three points will be the same. But please keep in mind that I don't want to create a route, I just want to know the distance to the annotation.
I hope someone can help me.
Best regards,
Paul Peelen
From what I understand of your post, I believe you seek the Haversine formula. Luckily for you, there are a number of Objective-C implementations, though writing your own is trivial once the formula's in front of you.
I originally deleted this because I didn't notice that you didn't want linear distance at first, but I'm bringing it back in case you decide that an approximation is good enough at that particular point of the user interaction.
I think as pointed out before, your query would be extremely heavy for google maps API if you perform exactly what you are saying. Do you need all that information at once ? Maybe first it would be good enough to query just some of the distances based on some heuristic or in the user needs.
To obtain the distances, you could use a Google Maps GDirections object... as pointed out here ( at the bottom of the page there's "Routes and Steps" section, with an advanced example.
"The GDirections object also supports multi-point directions, which can be constructed using the GDirections.loadFromWaypoints() method. This method takes an array of textual input addresses or textual lat/lon points. Each separate waypoint is computed as a separate route and returned in a separate GRoute object, each of which contains a series of GStep objects."
Using the Google Maps API in the iPhone shouldn't be too difficult, and I think your question doesn't cover that, but if you need some basic example, you could look at this question, and scroll to the answer.
Good Luck!
Calculating route distance to about 80 locations is certain to be computationally intensive on Google's part and I can't imagine that you would be able to make those requests to the Google Maps API, were it possible to do so on a mobile device, without being severely limited by either the phone connection or rate limits on the server.
Unfortunately, calculating route distance rather than geometric distance is a very expensive computation involving a lot of data about the area - data you almost certainly don't have. This means, unfortunately, that this isn't something that Core Location or MapKit can help you with.
What problem are you trying to solve, exactly? There may be other heuristics other than route distance you can use to approximate some sort of distance ranking.
It is possible to easily use the GPS functionality in the iPhone since sdk 3.0, but it is explicitly forbidden to use Google's Maps.
This has two implications, I think:
You will have to provide maps yourself
You will have to calculate the shortest routes yourself.
I know that calculating the shortest route has puzzled mathematicians for ages, but both Tom Tom and Google are doing a great job, so that issue seems to have been solved.
Searching on the 'net, not being a mathematician myself, I came across the Dijkstra Algorithm. Is there anyone of you who has successfully used this algorithm in a Maps-like app in the iPhone?
Would you be willing to share it with me/the community?
Would this be the right approach, or are the other options?
Thank you so much for your consideration.
I do not believe Dijkstra's algorithm would be useful for real-world mapping because, as Tom Leys said (I would comment on his post, but lack the rep to do so), it requires a single starting point. If the starting point changes, everything must be recalculated, and I would imagine this would be quite slow on a device like the iPhone for a significantly large data set.
Dijkstra's algorithm is for finding the shortest path to all nodes (from a single starting node). Game programmers use a directed search such as A*. Where Dijkstra processes the node that is closest to the starting position first, A* processes the one that is estimated to be nearest to the end position
The way this works is that you provide a cheap "estimate" function from any given position to the end point. A good example is how far a bird would fly to get there. A* adds this to the current distance from the start for each node and then chooses the node that seems to be on the shortest path.
The better your estimate, the shorter the time it will take to find a good path. If this time is still too long, you can do a path find on a simple map and then another on a more complex map to find the route between the places you found on the simple map.
Update
After much searching, I have found an article on A* for you to to read
Dijkstra's algorithm is O(m log n) for n nodes and m edges (for a single path) and is efficient enough to be used for network routing. This means that it's efficient enough to be used for a one-off computation.
Briefly, Dijkstra's algorithm works like:
Take the start node
Assign it a depth of zero
Insert it into a priority queue at its depth key
Repeat:
Pop the node with the lowest depth from the priority queue
Record the node that you came from so you can track the path back
Mark the node as having been visited
If this node is the destination:
Break
For each neighbour:
If the node has not previously been visited:
Calculate depth as depth of current node + distance to neighbour
Insert neighbour into the priority queue at the calculated depth.
Return the destination node and list of the nodes through which it was reached.
Contrary to popular belief, Dijkstra's algorithm is not necessarily an all-pairs shortest path calculator, although it can be adapted to do this.
You would have to get a graph of the streets and intersections with the distances between the intersections. If you had this data you could use Dijkstra's algorithm to compute a shortest route.
If you look at technology tomtom calls 'IQ routes', they measure actual speed and travel time per roadstretch per time of day. This makes the arrival time more accurate. So the expected arrival time is more fact-based http://www.tomtom.com/page/iq-routes
Calculating a route using the A* algorithm is plenty fast enough on an iPhone with offline map data. I have experience of doing this commercially. I use the A* algorithm as documented on Wikipedia, and I keep the road network in memory and re-use it; once it's loaded, routing even over a large area like Spain or the western half of Canada is practically instant.
I take data from OpenStreetMap or elswhere and convert it into a directed graph, assuming (which is the right way to do it according to those who know) that any two roads sharing a point with the same ID are joined. I assign weights to different types of roads based on expected speeds, and if a portion of a road is one-way I create only a single arc; two-way roads get two arcs, one in each direction. That's pretty much the whole thing apart from some ad-hoc code to prevent dangerous turns, and implementing routing restrictions.
This was discussed earlier here: What algorithms compute directions from point a to point b on a map?
Have a look at CloudMade. They offer a free service for iPhone and iPad that allows navigation based on your current location. It is built on open street maps and has some nifty features like making your own mapstyle. It is a little slow from time to time but its totally free.