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Authoring Hierarchical Road Networks Eric Galin :: Adrien Peytavie :: Eric Guerin :: Bedřich Beneš.

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Presentation on theme: "Authoring Hierarchical Road Networks Eric Galin :: Adrien Peytavie :: Eric Guerin :: Bedřich Beneš."— Presentation transcript:

1 Authoring Hierarchical Road Networks Eric Galin :: Adrien Peytavie :: Eric Guerin :: Bedřich Beneš

2 Outline Motivation Previous work Algorithm – Overview – Road generation – Removing redundant roads – Mergin roads Results

3 Motivation Roads in Cities?

4 Motivation Roads in Cities? Roads over Landscape?

5 Motivation Roads in Cities? Roads over Landscape?

6 Motivation Roads in Cities? Roads over Landscape? Road Hierarchies! Cities Towns Villages Highways Major roads Minor roads

7 Previous work

8 Algorithm - Overview 1)For each city pair, find a road over terrain 2) Discard some of the roads as redundant 3) Merge nearby pieces of road Basically, Galin et al. 2010Interesting graph theorySome topology

9 Algorithm - Overview 1)For each city pair, find a road over terrain 2) Discard some of the roads as redundant 3) Merge nearby pieces of road Basically, Galin et al. 2010Interesting graph theorySome topology

10 Find a road over terrain… Isolines Lattice 1.Generate graph 2.Find shortest path 3.Account for curvature, elevation, environment, “other”

11 …for each city pair A B C D E FG H i.e. AB, AC, AD, …, FG, FH, GH => Complete Graph over Cities Road type depends on city size

12 Algorithm - Overview 1)For each city pair, find a road over terrain 2) Discard some of the roads as redundant 3) Merge nearby pieces of road Basically, Galin et al. 2010Interesting graph theorySome topology

13 Discard Redundant Roads Complete Graph – too dense MST – too sparse Some candidates: β-skeleton, 1983 Relative Neighbour Graph, 1980 Gabriel Graph, 1969 Is a kind of

14 Relative Neighbour and Gabriel Graphs Contains edge (p i,p j )  no other point in Ω Relative Neighbour Gabriel ΩΩ Both Contain MST as subgraph; Euclidean Dist.

15 Our Version 1)Road length  Euclidean distance Changes the shape of neighborhood balls 2) Parameterize graph density by γ

16 Our Version, cont. Gabriel Ω γ = 2 Ω Relative Neighbour γ -> ∞ γ = 1 Continuum of densities

17 Density Continuum A little sparse, γ = 2 Quite sparse, γ = 8 Rather dense, γ = 1,2

18 Algorithm - Overview 1)For each city pair, find a road over terrain 2) Discard some of the roads as redundant 3) Merge nearby pieces of road Basically, Galin et al. 2010Interesting graph theorySome topology

19 Merge nearby roads Distance between curves – Length of leash? Frechet distance – (over all reparameterizations)

20 Road Merging, cont. Roads are close AND road types allow it => MERGE Merge: e.g. Highways and Highways, Major and Minor Don’t Merge: e.g. Highways and Major

21 And more.. Waypoints User steering Road interaction

22 Results We generate realistic road networks

23 Results We generate realistic road networks Real-life CorsicaOur Corsica

24 Results 512x512 ~ 380 m resolutionGrid size of 256x256 FAST - O(n 3 ) w/o heuristic

25 Future Work Urban fringe Highway intersections

26 Thank you!


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