amayama/barefoot

Map matching for the cities in China

Barefoot for China Cities

Map server

1. Install prerequisites.

   • Docker Engine (version 1.6 or higher, see https://docs.docker.com/installation/ubuntulinux/)
   • osmosis
   • java

2. Download the map data and extract the city data

   git clone https://github.com/boathit/barefoot
   cd barefoot/map/osm/
   curl http://download.geofabrik.de/asia/china-latest.osm.pbf -o barefoot/map/osm/china.osm.pbf
   osmosis --read-pbf file=china-latest.osm.pbf --bounding-box left=126.506130 right=126.771862 bottom=45.657920 top=45.830905 --write-pbf file=harbin.osm.pbf

   If you want to change the city, remember to modify the input in this line in import.sh.

3. Build Docker image.

   cd barefoot
   docker build -t imap ./map

4. Create Docker container.

   docker run -it -p 5432:5432 --name="harbin-map" -v ${PWD}/map/:/mnt/map imap

5. Import OSM extract (in the container).

   root@acef54deeedb# bash /mnt/map/osm/import.sh

   To detach the interactive shell from a running container without stopping it, use the escape sequence Ctrl-p + Ctrl-q.

   If we want to attach it again, we can do

   docker attach <container id>

6. Make sure the container is running ("up").

   docker ps -a
   ...

We can restart the created container (if it is stopped)

docker start --interactive harbin-map

Matching server

1. Install prerequisites.

   • Maven (e.g. with sudo apt-get install maven)
   • Java JDK (Java version 7 or higher, e.g. with sudo apt-get install openjdk-1.7-jdk)

2. Package Barefoot JAR. (Includes dependencies and executable main class.)

   mvn package -DskipTests

3. Start server with standard configuration for map server and map matching, and option for GeoJSON output format.

   java -jar target/barefoot-0.1.5-matcher-jar-with-dependencies.jar --geojson config/server.properties config/harbin.properties

   Note: Stop server with Ctrl-c.

   Note: In case of 'parse errors', use the following Java options: -Duser.language=en -Duser.country=US

Reference

P. Newson and J. Krumm. Hidden Markov Map Matching Through Noise and Sparseness. In Proceedings of International Conference on Advances in Geographic Information Systems, 2009.