A Fast and Customizable Route Planner By Peter: @timetabling - - PowerPoint PPT Presentation

A Fast and Customizable Route Planner

By Peter: @timetabling Berlin, WhereCamp, 2014-11-13

graphhopper.com

2

Overview of this Talk

• What is GraphHopper?
• Who uses GraphHopper?
• Numbers

Find this presentation under graphhopper.com/public/slides/

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What is GraphHopper?

A complete online maps application requires

• 1. Geodata: OpenStreetMap and SRTM (NASA)
• 2. Drawing: Display map from vector or raster data

Like Mapnik, MapSurfer.NET, …

• 3. Geocoding: Search address, get GPS coordinate

Like Photon, Gisgraphy 4.0, Pelias, ...

• 4. Routing: find best path(s) between coordinates

→ GraphHopper is all about routing! Still we offer routing and geocoding in our Directions API for business

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= Address Search + Tiles + GraphHopper

Try at graphhopper.com/maps

GraphHopper Maps

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What is GraphHopper?

• Open Source, Apache License
• Fast routing library and server
• Handles OpenStreetMap data by default
• Ordnance Survey experimental; Navteq possible
• Very memory-efficient but still simple Java API
• Scales to your problems
• Runs world wide as well as indoor graphs
• Can utilize lots of RAM for maximum speed
• Still can run on Android with only 32MB

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What is GraphHopper?

• Routing with optimality guarantees
• Heuristics not necessary
• Large test suite: unit, integration and load tests
• Commercial Support & Consulting

& Matrix and Directions API → Business friendly

• Written in Java:

Runs on the Serverside, Desktop, Rasperry Pi, Android, offline in the Browser and (drum roll) ...

(github.com/konsoletyper/graphhopper)

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GraphHopper for iOS!

… and offline on iOS!

• graphhopper/graphhopper-ios
• Also available under Apache License
• Still experimental, same code base
• Fast: ~1sec for a route through Germany

for iPhone 6

• Big Thanks goes to Tobias and Calin!
• Works for iOS 7.0+ and OS X 10.10
• might work for older versions
• Xcode 6.0+
• including a sample project →

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Demos

GraphHopper Maps https://graphhopper.com/maps

• Online Maps powered by GraphHopper Directions API

In-Browser Offline Routing thanks to TeaVM https://graphhopper.com/teavm

• Showcase usable in real world for hybrid solutions
• Combine with pure JS solutions like instantnavi/ffwdme

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GraphHopper Use Cases

• Point to point routing for car, bicycle, mountainbike,

motorbike, horse, foot, ambulance, wheelchair, ...

• Track vehicles via map matching:

'snap' real world GPS points to digital road network

• Urban planning
• Traffic simulation
• Isochrone calculation

= reachability for cars or bikes

• For tourism e.g. find

neighbouring POIs

• Graph traversal and statistics
• Education

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GraphHopper Use Cases

• Indoor routing
• Warehouse optimizations
• Tradeshow planning and visitor routing
• Virtual reality games ala 'scotland yard'
• Outdoor routing like biking
• For logistics:

Fast route matrix calculation

… and more!

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Who uses GraphHopper?

• GPSies: used a self-hosted GraphHopper and will

switch to our Directions API

• Gnome: uses our API for the 'Maps' Desktop app
• Komoot: we made routing over 500x faster than

home-grown routing engine

• Some IT companies for the taxi sector
• Several IT companies for logistics

OpenDoorLogistics, Optitool, market-ip, …

• Rome2rio: multimodal routing
• University Clausthal: education and traffic simulation

→ For Outdoor and Logistics!

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Who uses GraphHopper?

→ For Outdoor!

Komoot Route planning Route suggestions

Komoot Wearable

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Who uses GraphHopper?

A typical scenario: Get the optimal route to deliver 'goods' to many locations

• With GraphHopper or our Matrix Add-on:

Calculate the distance matrix

• With external software: Optimize order of

locations e.g. for one or more vehicle → For Logistics!

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Flexibility & Speedup Mode

The flexibility mode

• allows customized queries
• n-the-fly changes possible: e.g. prefer/avoid silent roads, steps, mountains
• still fast: <1sec through entire Germany

The speedup mode (Contraction Hierarchies)

• very fast queries: <50ms through Europe
• requires preparation
• smaller RAM usage per query
• more RAM for base graph

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Numbers!

For Worldwide Scenario

For car: 130 mio edges, ~100 mio nodes

• Takes ~1h to import and requires 20GB RAM
• Using memory mapped configuration decreases RAM

but increases query and import time

• To run this ~10GB are required

Speed-up mode

• preparation takes ~2h (car) and requires 25GB
• to run this 17GB are required

Comparable to the fastest commercial Maps APIs

• for embedded or LAN queries even ~5x faster

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Numbers!

Routing API, Europe 20 via-points for 1 route

Disclaimer: of course, firebug is no scientific performance analysis ;)

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Numbers!

Same 20 points but use Matrix API → results in 380 distances

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Thanks!

• Join Mailing list!
• Get Started: graphhopper.com/#community
• Sources & Issues at github.com/graphhopper
• Twitter: @graphhopper

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Backup slides

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What is a Graph?

• In a graph we have nodes and edges
• In the real world we have junctions and streets
• Edges and nodes get properties like position

Real world Graph

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Dijkstra

→ Input: one start and one end node

• 1. nodeX := start node
• 2. Get all neighboring nodes of nodeX
• 3. Put distance of edges for those nodes into a

priority queue

later steps: add old distance

• 4. nodeX : getMin(priority queue)
• 5. Go to 1, break if nodeX == end node

→ Output: Smallest distance from start to end

Get final path via shortest path tree

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Bidirectional Dijkstra

• Search from start and end at the same time

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A*

• Goal directed approach:

investigate more 'appropriate' nodes first

• Use linear distance

to estimate which node is 'appropriate'