Graham McIntire
eac817cd57
- Local prominence: each cell's elevation vs. its 8-neighbor ring (~1.3 km radius) feeds a small additive bonus so broad hilltops rank above isolated SRTM voxels - Road proximity: one Overpass call per Calculate fetches drivable ways inside the bbox; cells beyond ~0.5 km of any road get a light dB penalty, gated off in tests
110 lines
3.4 KiB
Elixir
110 lines
3.4 KiB
Elixir
defmodule Microwaveprop.Rover.RoadProximity do
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@moduledoc """
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Approximate distance from each rover candidate cell to the nearest
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drivable road, sourced from OpenStreetMap via the Overpass API.
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One Overpass query is issued per Calculate, fetching all motorway,
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trunk, primary, secondary, tertiary, unclassified, and residential
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ways inside the candidate bounding box. We then scan road segments
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per cell to find the minimum point-to-segment distance.
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Failure (network down, Overpass throttled, no roads in box) returns
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`:unavailable` and the scorer falls back to ignoring road proximity.
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"""
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require Logger
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@overpass_url "https://overpass-api.de/api/interpreter"
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@road_types ~w(motorway trunk primary secondary tertiary unclassified residential)
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@type latlon :: {float(), float()}
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@type segment :: {latlon(), latlon()}
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@type bbox :: %{required(String.t()) => float()}
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@spec road_distances([map()], bbox(), keyword()) ::
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{:ok, %{latlon() => float() | nil}} | {:error, term()}
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def road_distances(cells, bbox, opts \\ []) do
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fetch = Keyword.get(opts, :fetch, &fetch_segments/1)
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case fetch.(bbox) do
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{:ok, segments} when segments != [] ->
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{:ok, Map.new(cells, fn c -> {{c.lat, c.lon}, nearest_road_km(c, segments)} end)}
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{:ok, []} ->
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{:error, :no_roads}
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{:error, reason} ->
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Logger.warning("rover road proximity fetch failed: #{inspect(reason)}")
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{:error, reason}
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end
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end
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@spec fetch_segments(bbox()) :: {:ok, [segment()]} | {:error, term()}
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def fetch_segments(%{"south" => s, "west" => w, "north" => n, "east" => e}) do
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types = Enum.join(@road_types, "|")
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query = """
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[out:json][timeout:25];
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way["highway"~"^(#{types})$"](#{s},#{w},#{n},#{e});
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out geom;
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"""
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case Req.post(@overpass_url, form: [data: query], receive_timeout: 30_000) do
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{:ok, %{status: 200, body: %{"elements" => elements}}} ->
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{:ok, segments_from_elements(elements)}
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{:ok, %{status: status}} ->
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{:error, {:http, status}}
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{:error, reason} ->
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{:error, reason}
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end
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end
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defp segments_from_elements(elements) do
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Enum.flat_map(elements, fn
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%{"type" => "way", "geometry" => geom} when is_list(geom) and length(geom) >= 2 ->
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geom
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|> Enum.map(fn %{"lat" => lat, "lon" => lon} -> {lat, lon} end)
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|> Enum.chunk_every(2, 1, :discard)
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|> Enum.map(fn [a, b] -> {a, b} end)
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_ ->
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[]
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end)
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end
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defp nearest_road_km(%{lat: lat, lon: lon}, segments) do
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pt = {lat, lon}
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segments
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|> Enum.map(&segment_distance_km(pt, &1))
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|> Enum.min(fn -> nil end)
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end
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# Approximate point-to-segment distance using equirectangular projection
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# (km), which is plenty accurate over the few-km segments we care about.
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defp segment_distance_km({plat, plon}, {{alat, alon}, {blat, blon}}) do
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cos_lat = :math.cos(plat * :math.pi() / 180.0)
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px = plon * cos_lat * 111.0
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py = plat * 111.0
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ax = alon * cos_lat * 111.0
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ay = alat * 111.0
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bx = blon * cos_lat * 111.0
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by = blat * 111.0
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dx = bx - ax
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dy = by - ay
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seg_len_sq = dx * dx + dy * dy
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t =
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if seg_len_sq <= 0,
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do: 0.0,
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else: ((px - ax) * dx + (py - ay) * dy) / seg_len_sq
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t = t |> max(0.0) |> min(1.0)
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cx = ax + t * dx
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cy = ay + t * dy
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:math.sqrt((px - cx) ** 2 + (py - cy) ** 2)
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end
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end
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