A GPU-accelerated Large-scale Open Microscopic Traffic Simulation System
Website: https://moss.fiblab.net
- Efficient: MOSS adopts GPU as the computational engine, which accelerates 100 times compared to existing microscopic traffic simulators, allowing rapid simulation of large-scale urban road networks.
- Realistic: MOSS provides the cutting-edge AIGC method to generate globally available realistic OD matrices for travel demand generation and allows the user to quickly calibrate the simulation parameters to obtain realistic simulation results.
- Open: The simulator, toolchain, and sample programs will be open-sourced on Github for community access, and we hope that more people will join in the development and application of MOSS.
- Linux
- CUDA 11.8
- Python >= 3.8
pip install python-mossQ1: How to resolve the error ImportError: /.../libstdc++.so.6: version 'GLIBCXX_3.4.30' not found?
A1: Run conda install -c conda-forge libstdcxx-ng=12 in the current conda environment.
- Install Boost
wget -O boost_1_86_0.tar.gz https://archives.boost.io/release/1.86.0/source/boost_1_86_0.tar.gz
tar -zxvf boost_1_86_0.tar.gz
cd boost_1_86_0
./bootstrap.sh --with-libraries=filesystem,iostreams,program_options,regex,system --prefix=/usr/local # avro dependency
./b2 install
cd ..
rm -r boost_1_86_0
rm boost_1_86_0.tar.gzThat is what we change and why we change it.
- Focus on the microscopic traffic simulation only (vehicle and pedestrian), no crowd in AOI, no bus for more clear code to support community contribution.
- No overlap in junction to avoid deadlock following CBLab's design.
- Can output files with widely-used data format for visualization (visualization is the first for the user to understand the simulation). We choose AVRO as the output format.
- AOI is just as a marker of the starting/ending point of vehicles/pedestrians, no other functions for more clear code.
- clear code structure and documentation written in English.