Route Optimization with GraphHopper The GraphHopper Directions API - - PowerPoint PPT Presentation

route optimization with graphhopper
SMART_READER_LITE
LIVE PREVIEW

Route Optimization with GraphHopper The GraphHopper Directions API - - PowerPoint PPT Presentation

Route Optimization with GraphHopper The GraphHopper Directions API and new developments using OpenStreetMap and TomTom Data Who we are What we do Our software core is open source We use open data Open vs. Closed Route Optimization What is


slide-1
SLIDE 1

Route Optimization with GraphHopper

The GraphHopper Directions API and new developments using OpenStreetMap and TomTom Data

slide-2
SLIDE 2

Who we are

slide-3
SLIDE 3

Our software core is open source We use open data

What we do

slide-4
SLIDE 4

Open vs. Closed

slide-5
SLIDE 5

What is Route Optimization?

https://www.graphhopper.com/blog/2017/09/18/route-optimization-explained/

Companies dealing with deliveries face vehicle routing problems: Find a way to service customers under certain customer requirements:

  • time windows
  • which vehicles and its available capacities
  • e.g. refrigerated, must be picked up first
  • driver skills and breaks

Route Optimization

slide-6
SLIDE 6
  • 1. Customers send us problem wit: services or shipments, vehicles and

all the constraints like time windows

  • 2. Calculate distance and time matrix between all involved locations
  • 3. Assign services/shipments to vehicles
  • 4. Optimize order of those locations

Point 3+4 happen at the same time always watching the constraints

Route Optimization

Roughly route optimization works like:

slide-7
SLIDE 7

Why TomTom?

Customers demanded verified and known/trusted data source

Improved ETAs through traffic data

Compared to the other 2 world wide providers (HERE, INRIX) we got a better offer with good terms for our customers

Open vs. Closed

slide-8
SLIDE 8

Time-dependent route optimization

Allows to utilize less vehicles and better arrival estimates Time-dependency is also direction-dependent, i.e. at a given time speed into city != out of city

Time-dependent

slide-9
SLIDE 9

Time-dependent

Without historic traffic data all customers can be served with 6 vehicles in 8 hours and 55 min (regardless of start time)

slide-10
SLIDE 10

Time-dependent

Starting at 2am all customers can be served with 4 vehicles in 6 hours and 30min

slide-11
SLIDE 11

Time-dependent

Starting at 8am all customers can be served with 7 vehicles in ~11 hours Taking traffic into account can have considerable implications on total costs.

slide-12
SLIDE 12

Optimization problems require calculating distance matrices Large problems (>100 locations) requires special routing algorithm

(Otherwise infeasible response times)

For more than 1000 locations even this algorithm takes minutes With time-dependent route optimization this got even more demanding due to many required distance matrices but This should be fast too!

Fast Distance Matrix

slide-13
SLIDE 13

That‘s what we did (single thread):

Fast Distance Matrix

matrix size

  • ld matrix

new matrix 100² 2.4s 1.2s 500² 40s 4s 1000² 2.5min 8s 2000² 9.5min 22s

slide-14
SLIDE 14

Not our strength but important for debugging and tuning Many possibility to visualize the time dependent traffic flow in one area One is: reachable area

Visualization

slide-15
SLIDE 15

Berlin: Time- dependent reachable areas of 1h for the different times of the day with different colors for different distances (blue = ‘far away’)

Visualization

slide-16
SLIDE 16

Time-dependent reachable areas (30min) with colors for different slowdown

  • factors. Red roads

mean that they are slower as its night speed.

Visualization

slide-17
SLIDE 17

How does the reachable area change over a typical weekday? The orange dots show the maximum reached distance

Visualization

slide-18
SLIDE 18

Peak is at different time for reverse reachable area (traveling into the city)

Visualization

slide-19
SLIDE 19

In 2018 we released v0.10 & 0.11 of our open source routing engine. New Features:

Isochrone API is now open source too

Path details (e.g. max speed, toll or surface info for the whole path)

Elevation support for Northern Europe too

Improved public transit (e.g. real time support)

30% faster routing for speed mode

Hybrid routing also faster

Easier to create navigation applications based on GraphHopper

Moved to a more comfortable web framework (easier to use)

Routing Engine

slide-20
SLIDE 20

New Navigation Example based on a fork of the Mapbox Navigation SDK

Shows how to utilize the Routing API and also Route Optimization API

independent from Mapbox services

Uses tiles from mapilion.com but can use any other too

100% open source (unlike the Mapbox Navigation SDK)

Routing Engine

slide-21
SLIDE 21

Routing Engine

slide-22
SLIDE 22

We‘ll further invest into our open source routing engine Biggest goal for 2019: make it easier to customize and more flexible for non-Java developer

Routing Engine

slide-23
SLIDE 23

Route Optimization with GraphHopper Route Optimization with GraphHopper

peter.karich@graphhopper.com