traffic-simulation

A Multi-Agent Reinforcement Learning Environment for Large Scale City Traffic Scenario

TrafficSim using Unity ECS 2019.3

Fast shortest path calculations for Rust

A simple tool to generate fake web browsing and mitigate tracking

A Unity asset that lets you easily simulate very simple traffic into your scene.

We have used Deep Reinforcement Learning and Advanced Computer Vision techniques to for the creation of Smart Traffic Signals for Indian Roads. We have created the scripts for using SUMO as our environment for deploying all our RL models.

Easy-to-build realistic roads in Unity. Foundation of any simcity game.

Containerised SUMO. Use sumo, sumo-gui and TraCI with Docker. 🐳 🚗

This repository documents MATLAB implementation of a dynamic user equilibrium solver, including a dynamic network loading sub-routine

🚙 Small scale traffic simulation with a playful approach

Another AI toy project, of a traffic intersection controlled by a Reinforcement Learning AI agent to optimize traffic flow in an intersection of vehicles or pedestrians

Python traffic simulation libarary based on Martin Treiber's Java applet from: http://www.traffic-simulation.de/. Implement IDM follower model and Lanechange model.

A traffic simulation software based on SUMO that incorporates driver behavior.

Traffic generator for local analytics testing

Traffic Control Test Bed

Multiagent hybrid simulator of road traffic in Qt/C++ and OpenStreetMap.

Simple JavaScript based traffic simulation

Traffic Intersection Simulation Using C++ and Qt

We propose a driver modeling process and its evaluation results of an intelligent autonomous driving policy, which is obtained through reinforcement learning techniques. Assuming a MDP decision making model, Q-learning method is applied to simple but descriptive state and action spaces, so that a policy is developed within limited computational load. The driver could perform reasonable maneuvers, like acceleration, deceleration or lane-changes, under usual traffic conditions on a multi-lane highway. A traffic simulator is also construed to evaluate a given policy in terms of collision rate, average travelling speed, and lane change times. Results show the policy gets well trained under reasonable time periods, where the driver acts interactively in the stochastic traffic environment, demonstrating low collision rate and obtaining higher travelling speed than the average of the environment. Sample traffic simulation videos are postedsit on YouTube.

OpenTrafficLab is a MATLAB environment capable of simulating simple traffic scenarios with modular vehicle and junction controllers.

A traffic simulation using the intelligent driver model and the MOBIL lane change model. Mirror of the original repository.

Reinforcement Learning + traffic microsimulation (via SUMO). Uses Ray RLLIB and forces SUMO into the OpenAI Gym Framework

A general formulation for multi-modal dynamic traffic assignment considering multi-class vehicles, public transit and parking

A little traffic simulator webpage/application written in elm+node.js

Town growth simulator that creates road networks

A lightweight Python-based 3D network multi-agent simulator. Uses a cell-based congestion model. Calculates risk, loudness and battery capacities of the agents. Suitable for 3D network optimization tasks.

We propose a driver modeling process of an intelligent autonomous driving policy, which is obtained through Q-learning.

Simulation of Nagel and Schreckenberg's cellular automaton model for freeway traffic simulation