CityFlow is a multi-agent reinforcement learning environment for large scale city traffic scenario.
Checkout these features!
- a microscopic traffic simulator which simulates the behavior of each vehicle, providing highest level detail of traffic evolution.
- support flexible definitions for road network and traffic flow
- provides friendly python interface for reinforcement learning
- Fast! Elaborately designed data structure and simulation algorithm with multithreading. Capable of simulating city-wide traffic. See the performance comparison with SUMO .
Performance comparison between CityFlow with different number of threads (1, 2, 4, 8) and SUMO. From small 1x1 grid roadnet to city-level 30x30 roadnet. Even faster when you need to interact with the simulator through python API.
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