Dataset Introduction¶
In this section, we introduce the datasets used in LibSignal, basic units called atomic files, and conversion tools.
Datasets¶
For details, you can see Reinforcement Learning for Traffic Signal Control and RESCO.
Dataset name |
Number of Intersections |
Support Environment |
|---|---|---|
hangzhou_1x1_bc-tyc_18041610_1h |
1 |
CityFlow |
hangzhou_1x1_kn-hz_18041608_1h |
1 |
CityFlow |
hangzhou_1x1_qc-yn_18041608_1h |
1 |
CityFlow |
hangzhou_1x1_sb-sx_18041608_1h |
1 |
CityFlow |
hangzhou_4x4_gudang_18010207_1h |
16 |
CityFlow |
manhattan_28x7 |
196 |
CityFlow |
cologne1 |
1 |
SUMO |
cologne3 |
3 |
SUMO |
grid4x4 |
16 |
SUMO |
.. Note:: All the datasets’ time span is set to 3600 seconds.
Atomic Files¶
To make datasets configurations adaptive across different simulators, we consider two basic units called “atomic files” that can map to the different simulation environments.
Road Network File¶
It stores the basic structure of a traffic network consisting of road, lane, and traffic light information. For CityFlow, the atomic file is in the format of roadnet.json, while in SUMO is .net.xml.
Traffic Flow File¶
It defines the traffic flow and stores the vehicles’ information. The format under CityFlow is flow.json, while in SUMO is .rou.xml.
Conversion Tools¶
We provide converter.py tool to convert basic atomic files between different simulators. It takes in Road Network File and Traffic Flow File from the source simulator, sometimes also needs configuration files, and generates new files in the target simulator’s formation.
The following code converts a SUMO roadnet file,
grid4x4/grid4x4.net.xml, and a traffic flow file,grid4x4.rou.xml, to CityFlow format with the information from SUMO configuration filegrid4x4/grid4x4.sumocfg.
python converter.py --typ s2c --or_sumonet grid4x4/grid4x4.net.xml --cityflownet grid4x4/grid4x4_roadnet_red.json --or_sumotraffic grid4x4/grid4x4.rou.xml --cityflowtraffic grid4x4/grid4x4_flow.json --sumocfg grid4x4/grid4x4.sumocfg
The following code converts a CityFlow roadnet file,
hangzhou_1x1_bc-tyc_18041610_1h/roadnet.json, and a traffic flow file,hangzhou_1x1_bc-tyc_18041610_1h/flow.json, to SUMO format.
python converter.py --typ c2s --or_cityflownet hangzhou_1x1_bc-tyc_18041610_1h/roadnet.json --sumonet hangzhou_1x1_bc-tyc_18041610_1h/hangzhou_1x1_bc-tyc_18041610_1h.net.xml --or_cityflowtraffic hangzhou_1x1_bc-tyc_18041610_1h/flow.json --sumotraffic hangzhou_1x1_bc-tyc_18041610_1h/hangzhou_1x1_bc-tyc_18041610_1h.rou.xml