PGROuting – Getting Nearest Node to a Given Point with Latitude and Longitude

latitude longitudeopenstreetmappgroutingpoint

I have a point whose latitude and longitude (only) are known, and a table of nodes with their geom. I want to find the closest node in the table to the given point.

I think I can achieve this with pgr_findNearestNodeDwithin function, but i cannot find the exact syntax of the function and the parameters it takes.

Any pointers in this direction will be appreciated.

Best Answer

To find the nearest point you only need a little bit PostGIS. With PostGIS 2.0 or higher you can use nearest neighbor KNN gist functionality.

I assume you have a table with all nodes ("vertices"):

SELECT * FROM vertices 
    ORDER BY the_geom <-> ST_GeometryFromText('POINT(lon lat)',4326) 
    LIMIT 1;

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Firstly few questions:
1. what do you mean by converting roads to nodes? Maybe you meant network graph?
2. Are you able to find at least one way and the trouble is with many ways?
3. Nearest school euclidean or by the roads?
4. What was the work-flow of this conversion form roads to nodes?
5. What are the names of tables and column names in this tables?
6. How big are your tables with students and schools?
7. Is it OK to select nearest school euclidean

Please add information to your question so maybe there will be simplest to help you.

But back to the point:

PG_Routing is not a resolution out of the box since it provides a kind of 'low level' stored procedures. You can't write query like 'select pg_CountMeTheWay(student, scholl), but it can find shortest way if you'll give it source edge id, target edge id and set of edges as graph with cost.

Also function st_DrivingDistance is not finding route, but it's creating set of edges reachable in specified time (e.g. how far you can go in 15 minutes).

Also 2 you need distance from student to nearest school but which is nearest if you don't know the distance? Do you have some kind of relation between schools and students? If not you have to count distance from one student to every school to know which is nearest. In most cases nearest euclidean (in straight line) will be also nearest by the roads, but if you have some special cases in your graph such as river with one bridge you cant be sure.

There are many resolutions of your problem even without this questions to your question, so please try to be more specific.

EDIT

Ok, so hope you have a lot of time :)

Firstly - to know the driving distance you have to (one way or another) find shortest path - there is no smoke without fire...
1. Driving distance is not doing anything different then this, but under another conditions. It's like space-time in military meaning - you have to dig ditch from here to everywhere till 4:00pm.
2. Also as far as I know driving_distance is working like window functions (e.g. row_number() over()) so it's designating cost during calculations, so you can't make him to do calculations for all edges, but designate cost only to few. Of course you can do select from select but this means that distance to every edge will be calculated anyway.
3. pgr_Driving_distance is much more slower then pgr_dijkstra - finding one route between points spaced about 15km is taking on my dataset (all Poland) about 1s (0,5-2,5), driving distance with the same condition will be about 15s

Basing upon this times counting:
1. Shortest paths between all students and scholls (100000x50x2) will last 115 days
2. Shortest paths between all students and scholls with minimal time will last about 46 days
3. Mixed version - Shortest paths between all students and 10 euclidean nearest to them scholls will last about 10 days
4. driving_distance for all students till 15km will last 17 days
5. Short version - Shortest paths between all students and 1 euclidean nearest to them scholl will last about 1 day.
6. Performance depends on numer of rows in edges table (network graph) so less records less time you'll need.

Possible resolution (1):

Write stored procedure with your pgr_djikstra() with id_source, id_target as input and cost as output (there are many exapmples on network)
create table with id_student, id_source, id_school, id_target, cost
Fill it with Id's and nearest edges of network graph
update it with cost of shortest path using your function
select for every student record with the lowest cost

Possible resolution (2):

Write stored procedure with driving_distance with source_id as input and retorn output of driving_distance
Write stored procedure with geometry as input and nearest edge id as output.
create tables with students and their nearest edges using above procedure, the same for schools
create table a as select *, your_proc(nearest_edge_id) as dist from students_nearest.
create another table b as select * from a where exists id of nearest student and school id
Select from this table records with student_id, school_id, min(cost) group by student_id, school_id

IMO the best resolution as compromise of time and quality is to find 3 euclidean nearest schools for every student and count for them shortest paths, then choose one - the shortest. With some tuning and only absolutely necessary edges in network graph you can feet in few hours.

[GIS] Calculating shortest path between each lat/lon point in one table and each lan/lon point in another in PostgreSQL

Read this answer to Nearest facility with pgRouting which is a quite similar case. If it will not then some information that would help is:

Size of your source and target tables
Size of your table with road network
Whether it is OK to find nearest point euclidean and then count road distance

One of resolutions is (pseudo-code):

Create table with distance from every source to every target:

Create table distances_tmp as
SELECT
  sources.id as source_id
  nearest_node(sources.x, sources.y) as source_node
  targets.id as target_id
  nearest_node(targets.x, targets.y) as target_node
  give_me_cost(sources.x, sources.y,targets.x, targets.y) as cost
FROM
  sources
JOIN
  targets on 1=1

Create table with only lowest costs

Create table distances as
select * 
from distances_tmp d1
where not exists (select 1 from distances_tmp d2 where d2.cost < d1.cost)

I wrote it in two steps cause it's easier to understand it, but there is some ways to join this two queries into one (eg. select from select or WITH clause)

Also consider changes in nearest_node function - nearest vertex of nearest edge is not always best place to start (or stop) routing if nearest edge is one-way street, so your cost will not always be accurate.

Best Answer

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