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Benchmark suite for dissertation "Map matching methods for assigning vehicle positions to road networks"
Faculty
Contributor(s):
Publisher Information:
Otto-Friedrich-Universität Bamberg
Year of publication:
2026
Date of creation:
September 22, 2026
Language:
English
In supplemented to:
Abstract:
Map matching methods for assigning vehicle positions to road networks
Complete benchmark suite for the thesis
The benchmark was initially run on a dedicated server with 2x 64 cores AMD Epyc 7742 with 1024 GB of DDR4 system memoryon local PCIe 3.0 NVMe storage.
This benchmark suite contains three major scenarios:
- The data_set_benchmarks for an extensive comparison benchmark of our Map Matching 2 solution against multiple third-party solutions.
- The memory_profiling suite for analysing the memory consumption and memory types of our Map Matching 2 solution over time.
- An analysis set of tools for preparing some data for figures in our thesis.
- The simulation folder contains a copy subset of the SUMO simulation from the data_set_benchmarks prepared and documented for individual usage.
For creating a virtual python environment on the host system, use:
python3 -m venv venv
source venv/bin/activate
pip install -r benchmarks/data_set_benchmarks/requirements.txt
Any *.sh scripts should be run from this python venv and within the respective directories they are located in.
This benchmark suite is licensed under AGPL 3.0.
Complete benchmark suite for the thesis
The benchmark was initially run on a dedicated server with 2x 64 cores AMD Epyc 7742 with 1024 GB of DDR4 system memoryon local PCIe 3.0 NVMe storage.
This benchmark suite contains three major scenarios:
- The data_set_benchmarks for an extensive comparison benchmark of our Map Matching 2 solution against multiple third-party solutions.
- The memory_profiling suite for analysing the memory consumption and memory types of our Map Matching 2 solution over time.
- An analysis set of tools for preparing some data for figures in our thesis.
- The simulation folder contains a copy subset of the SUMO simulation from the data_set_benchmarks prepared and documented for individual usage.
For creating a virtual python environment on the host system, use:
python3 -m venv venv
source venv/bin/activate
pip install -r benchmarks/data_set_benchmarks/requirements.txt
Any *.sh scripts should be run from this python venv and within the respective directories they are located in.
This benchmark suite is licensed under AGPL 3.0.
Type:
Software
DDC:
Keywords: ; ; ; ; ; ;
benchmark
map matching
geographical information science
open source
ground truth
data set
simulation
Extent:
86.2 MB
Format:
application/zip
Permalink
https://fis.uni-bamberg.de/handle/uniba/117327