mkostiv / kharita

Robust and online map inference from gps data

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kharita

Kharita (Map in Arabic) is a robust and online algorithm for map inference from crowd-sourced gps data. The details of the algorithm can be found in:

Rade Stanojevic, Sofiane Abbar, Saravanan Thirumuruganathan, Sanjay Chawla, Fethi Felali, Ahid Aliemat: Kharita: Robust Map Inference using Graph Spanners. Submitted to ACM SIGKDD'2017 [Arxiv version].

Input

The input is a csv file in the following format: vehicule_id,timestamp,lat,lon,speed,angle

Vehicule_id: important to identify trajectories. Timestamp: important to sort gps points within trajectories timestamp: in the format: yyyy-mm-dd hh:mm:ss+03 angle: in 0-360 interval. Angle to the north.

Running Kharita

Kharita can be invoked from command line as follows:

python kharita_star.py -p data -f data_2015-10-01 -r 25 -s 10 -a 40

-p: the folder containing the input data

-f: the input file name without its extension

-r: the radius (cr) in meters used for the clustering

-s: the densification distance (sr) in meters

-a: the angle heading tolerance in degrees (0-360)

Example

python kharita_star.py -p data -f data_uic -r 100 -s 20 -a 60

Output

The code will produce a txt file containing the edges of the generated directed graph.

UIC map examples

Kharita* map

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Kharita map

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Citation

For any use of this code, please cite our work as follows: Rade Stanojevic, Sofiane Abbar, Saravanan Thirumuruganathan, Sanjay Chawla, Fethi Felali, Ahid Aliemat: Kharita: Robust Map Inference using Graph Spanners. In Arxiv. 2017.

Contact

Sofiane Abbar (sofiane.abbar@gmail.com)

About

Robust and online map inference from gps data

License:MIT License


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Language:Python 100.0%