GPS Visualizer will take a Google Map route (url) and convert to .gpx
"You can ignore most the options, just select Gpx and paste the
Google Maps URL into the box labelled “provide the URL of a file on
the Web” and then press the Convert button"
The truth is that most people use a custom variation of the A* algorithm. You will see this across the most of the "big guys"(I can't say who they are in a public forum, but I can tell you that you probably use one of them - guaranteed), where the modification of the heuristics is very dependent on the datasets that they use.
You mentioned pgrouting ...
Often it is good to address the need that is stated rather than answering the question that was asked. I would like only to point out that there is a well-known parallel solution that neatly circumvents all the technical computing issues: Santa has helpers. These agents work asynchronously and independently to identify the houses that need visits and carry ...
Not sure if it is newer but pgRouting has a Shooting-Star algorithm:
Shooting-Star algorithm is the latest
of pgRouting shortest path algorithms.
Its speciality is that it routes from
link to link, not from vertex to
vertex as Dijkstra and A-Star
algorithms do. This makes it possible
to define relations between links for
example, and it ...
I haven't been up to speed on the research or best practice on this so forgive me if I miss anything and it's been 3 years since I worked with a Travel Demand Model. And when I did travel demand models, I didn't spend a whole lot of time and effort into building turning penalty/restriction models.
Turning restrictions and penalty settings (TR/TP)...
(SELECT SUM(cost) FROM -- or whatever you want to do with the routing result
(SELECT * FROM shortest_path_astar('...',
) AS foo
) AS cost
Total Costs from københavn(denmark) to tekirdağ(turkey) (based on default values)
Toll 0.00 EUR | Petrol 223.22 EUR | Road tax 29.39 EUR
27h19 which 17h10 on motorways
2500 km which 1900 km on motorways
You can custom your route in fine detail - by type of car - engine size etc:
Contraction Hierarchy is a very fast algorithm:
This algorithm is RAM friendly while executing a query (to hold a contracted graph some more RAM is necessary as well as massive preprocessing)
There are some other algorithms - including the ones that solve public transit routing:
To export a route to KML you'll have to use Google MyMaps.
add a route to new or existing layer
drag and drop the route to suit your needs
Open the maps options menue (3 dots above the layers)
Export to KML
You can then use any service to convert the KML to GPX. I prefer GPSies.
I have not used ArcGIS Schematics for more than some quick demos quite a few years ago, but there is a blog posting on Create route maps with the ArcGIS Schematics extension that may provide a solution.
Just to close this loose end, since I asked the question a new package was released called osmar which contains a vignette of how to implement shortest path algorithms in R using Open Street Map data: http://osmar.r-forge.r-project.org/ . It uses the function get.shortest.paths from the igraph package.
Excellent article on this can be found here:
I'm currently exploring the same problem as you, for the purpose of research paper. Before I started to test these two databases, I had the same presumption as you. That Neo4j graph database would be perfect solution for this kind of problem. And partially it is, but with lot of problems.
First problem is that A-Star is only implemented if you are using ...
Depending on your purpose and the number of requests you need to put through the service, the Bing Maps REST APIs are generally free to use - they just require you to sign up for a key first from https://www.bingmapsportal.com/.
The API for the Route service is at:
http://msdn.microsoft.com/en-us/library/ff701717.aspx, which can return driving distances and ...
I think that the type of software you are looking for is called a chart plotter software. There are several solutions used in navigation, where using a laptop is more and more common. I will not list here the solutions using dedicated hardware (AIS/navigation systems for example).
Amongst paying options you have the "best seller" called MaxSea (http://www....
The link given by MappaGnosis is the first attempt to implement Graph theory algorithms in Python (by Guido van Rossum, the creator of Python).
Since, many modules were developed:
One of the most comprehensive is NetworkX, mentioned before in GS
it can read or write shapefiles natively (thanks to bwreilly in ...
the grass algorithm v.net.alloc can produce the subnets - you can call it from the Processing toolbox (tested in QGIS 2.16)
You'll need a point layer (for facilities) and a lines layer with costs (either time/length). It'll create a new line layer with a field called cat added, which will be the id of the nearest facility.
Here's an example based on ...
You can use GraphHopper for that task, which also supports different mode like walking or biking and uses OpenStreetMap per default. You'll need some Java coding which explores the road network from the starting point similar to how the Dijkstra algorithms works but then you can get something like the following even in real time (<0.5s):
The code will ...
It may seem like laziness on the part of Watershed tool developers to stick with the simplest and oldest flow algorithm, D8, but there is a very sound reason for doing so. The difference between the D8/Rho8 flow algorithm and the more advanced algorithms that you mention (e.g. D-infinity) is mainly in their inability to represent the dispersion of overland ...
(This is not exactly the solution you require - but close.)
Google Maps API (v2) Driving Radius
This takes a starting location (city centre of Memphis)
and radiates out (like a spider) to 10 miles (default)
FULL CREDIT goes to Marcelo Montagna
You could have a look at the Route360°-API, a pretty simple but powerful JS library which you can use with Leaflet (or even Google maps if you like).
It adds travel time polygons to your map for the travel times you require (e.g. 10, 20, 60 minutes) and for the following travel modes: walk, bike, car, transit.
There are quite a few examples on how to use ...
Okay, I looked further into the idea of Steve above. I'll try to demontrate his idea in a QGIS/PostGIS/pgrouting environment. You will get results such as this:
First, let's assume you have a geodata table with your shelves/obstacles looking like this (I made them up for this purpose):
Make sure your shelf data is in a projected coordinate system with ...
OSM has a page dedicated to routing, which is worth going over:
There is a special tool for importing OSM data into a PGRouting system and generating the required structure:
Lastly, there is a workshop tutorial on getting routing working with OSM data here:
The only practical way is to add the 'missing' routes the data yourself. OSM probably shouldn't be putting parking lots into its walking routes. There are liability issues with adding routes that aren't real, properly maintained pedestrian paths. A parking lot, though walkable, could be dangerous and could be private property. You'll have similar issues with ...
This is something you can probably solve by using the Warshal's or Dijkstra's algorithm
Although the number of houses in the world is way too big it would take a long time to compute that, I think this is a good initial point. Now I don't have the time to explain them but i give you an initial point. I'll go out with my family now and maybe I'll go back to ...
We are working on a multimodal routing for Austria (also for pedestrians). What I can say till now:
You need the data: It took at least 4 years and even longer to collect all the necessary walkways, barriers, steps, opening times, streets, railways, bikeways, ferrys, and, and and...and its still going on
You need a router which can interprete theses graphs ...