[Robotics] Types of Autonomous Self-Driving Car Simulator

💡 This document summarizes the 'Types of Autonomous Self-Driving Car Simulators'.
Please note that the features and official website of each simulator are mentioned for the simulators used in self-driving cars and V2X communications.

1. Autonomous Self-Driving Car Simulator

1.1. Commercial Self-Driving Car Simulator (Company)

Morai

• https://www.morai.ai/traffic

Cesium (support Unity, Unreal, Omniverse)

• https://cesium.com/platform/cesium-for-unity/
• https://sandcastle.cesium.com/?src=Clamp to 3D Tiles.html&label=All

Cognata (support Unity)

• Cognata is a commercial autonomous vehicle simulator that uses Unity. However, Cognata also provides a free version of its simulator for academic and research purposes. Cognata provides a high-fidelity environment for testing and validation of autonomous driving algorithms.
• https://www.cognata.com/ko/

Autonomoose (support Unity)

• Autonomoose is an open-source autonomous vehicle simulator that uses Unity. It provides a realistic urban environment with dynamic traffic and pedestrians. Autonomoose also supports various sensors such as lidars, cameras, and radars.
• https://www.autonomoose.net/

These simulators provide a flexible and powerful environment for developing, testing and validation autonomous vehicle algorithms. Each simulator has its own features and capabilities, so it is important to evaluate which one best fits your needs.

1.2. OpenSource Self-Driving Car Simulator

Gazebo

• Gazebo is a general-purpose robot simulation tool that can be used for testing autonomous vehicle algorithms. It provides a physics engine, sensor simulation, and a user interface for creating and running simulations.

CARLA(Car Learning to Act) Simulator(Unreal Engine)

• CARLA is an open-source simulator for autonomous driving research. It is designed to support training, testing, and validation of autonomous driving systems. CARLA provides realistic urban environments with dynamic traffic, pedestrians, and weather conditions.
• CARLA is one of the most popular open-source autonomous vehicle simulators that uses Unreal Engine. It provides a realistic urban environment with dynamic traffic, pedestrians, and weather conditions. CARLA also supports various sensors such as lidars, cameras, and radars.
• Unreal Engine 5부터 지원하지 않음
• [Main] Carla simulator: https://carla.org/
• Carla official docs: https://carla.readthedocs.io/en/latest/
• [Youtube] Carla simulator: https://www.youtube.com/@carlasimulator8782
• (한글)전반적인 소개: https://www.youtube.com/watch?v=z_oulQggw68
• [Github] https://github.com/search?p=1&q=carla&type=Repositories

LG SVL

• LGSVL Simulator is an open-source simulator for autonomous vehicles that uses Unreal Engine. It provides a high-fidelity environment for testing and validation of autonomous driving algorithms with various types of vehicles, sensors, and scenarios.
• https://www.svlsimulator.com/
• https://github.com/lgsvl/simulator

Microsoft AirSim(Unity)

• AirSim is an open-source simulator for autonomous vehicles and drones. It provides a realistic environment for testing autonomous vehicle algorithms with various types of vehicles, sensors, and environments.
• AirSim is an open-source simulator for autonomous vehicles and drones. It supports various game engines including Unity. AirSim provides a realistic environment for testing autonomous vehicle algorithms with various types of vehicles, sensors, and environments.
• https://microsoft.github.io/AirSim/

Baido Apollo

• Apollo is an open-source autonomous driving platform developed by Baidu. It includes a simulation environment for testing and validation of autonomous driving algorithms.
• https://github.com/ApolloAuto/apollo
• https://developer.apollo.auto/index.html

Apollo Cyber RT

• Apollo Cyber RT is an open-source autonomous driving platform that includes a simulation environment based on Unity. It provides a modular architecture for developing and testing autonomous driving algorithms.
• https://cyber-rt.readthedocs.io/en/latest/

Autoware

• Autoware.Auto is an open-source autonomous driving software stack that includes a simulation environment based on Unreal Engine. It provides a modular architecture for developing and testing autonomous driving algorithms.
• https://www.autoware.org/
• https://github.com/autowarefoundation/autoware
• https://autowarefoundation.gitlab.io/autoware.auto/AutowareAuto/index.html
• with LGSVL: https://autowarefoundation.gitlab.io/autoware.auto/AutowareAuto/lgsvl.html

Udacity self driving car simulator(Unity)

• Udacity Self-Driving Car Simulator is an open-source simulator for autonomous vehicles that uses Unreal Engine. It provides a simplified environment for testing and training self-driving algorithms.
• https://github.com/udacity/self-driving-car-sim?fbclid=IwAR3lAdvWyqwaJDxOqnwomrW1jaAGLZGRj2UF3hCNGfSLZkHY74jd3G8NyPU

VISSIM

• VISSIM is a commercial traffic simulation software that offers the following key features and advanced capabilities:
  1. Microscopic simulation for modeling the behavior of individual vehicles and drivers
  2. Customizable traffic scenarios with various parameters
  3. 3D visualization for analyzing simulation results
  4. Evaluation of traffic management strategies
  5. Detailed vehicle dynamics models
  6. Multi-modal simulation for various modes of transportation
  7. Advanced analysis tools for safety and traffic flow
  8. Integration with other transportation planning and analysis software
• https://www.vissim.no/

2. Opensource V2X communication simulator

2.1. Opensource V2X communication simulator

V2X (Vehicle-to-Everything) communication is a key technology for enabling autonomous driving and improving road safety. Here are some open-source V2X communication simulators:

SUMO

• SUMO is a simulation tool for modeling and analyzing traffic systems. It can be used to simulate autonomous vehicles in urban traffic scenarios.
• https://sumo.dlr.de/docs/Topics/V2X.html
• https://sumo.dlr.de/docs/TraCI.html

Veins

1. Veins (Vehicles in Network Simulation) is an open-source framework for simulating V2X communication in urban and highway scenarios. It is built on top of the popular network simulator, OMNeT++, and supports various wireless communication technologies such as IEEE 802.11p and LTE-V.

OpenV2X

• OpenV2X is an open-source implementation of the ETSI ITS-5G standard for V2X communication. It provides a complete solution for simulating V2X communication between vehicles, infrastructure, and other road users.
• https://openv2x.org/project/
• https://github.com/open-v2x

ITS-S

• ITS-S (Intelligent Transportation System Simulator) is an open-source simulation platform for V2X communication. It supports various communication protocols such as DSRC and C-V2X, and provides a realistic environment for testing and validating V2X communication technologies.

VSimRTI

• VSimRTI is an open-source simulation framework for V2X communication that supports the HLA (High-Level Architecture) standard for distributed simulation. It provides a flexible and scalable environment for simulating large-scale V2X scenarios.
• https://www.sciencedirect.com/science/article/abs/pii/S1389128611001605
• https://omnetpp.org/download-items/VSimRTI.html
• https://sumo.dlr.de/pdf/SUMOWorkshop2010/BjoernSchuenemannVSimRTI.pdf

2.2. Opensource autonomus vehicle simulator using SUMO traffic data

SUMO (Simulation of Urban MObility) is an open-source traffic simulation software that can be used for developing autonomous vehicle simulators. Here are some open-source autonomous vehicle simulators that use SUMO traffic data:

Flow

1. Flow is an open-source framework for reinforcement learning-based control of traffic lights in urban road networks. It uses SUMO as a traffic simulator to generate traffic data for training and validation of autonomous driving algorithms.
2. Flow, which was mentioned earlier, also provides a wrapper for integrating SUMO traffic data with its framework for reinforcement learning-based control of traffic lights in urban road networks.
3. https://arxiv.org/abs/1710.05465
4. https://flow.readthedocs.io/en/latest/flow_setup.html#remote-installation-using-docker

TraCI4Unity

• TraCI4Unity is an open-source Unity package that allows communication between Unity and SUMO via the TraCI (Traffic Control Interface) protocol. It enables developers to create autonomous vehicle simulators using SUMO traffic data in Unity.

SUMO-GUI

• SUMO-GUI is the graphical user interface of SUMO that allows developers to create and run traffic simulations. It provides a wide range of traffic models, traffic lights, and vehicle types to simulate various traffic scenarios for testing and validation of autonomous driving algorithms.

SUMO SimWrapper

• SUMO SimWrapper is an open-source Python package that provides an interface for integrating SUMO traffic simulations with other simulators. It allows developers to create autonomous vehicle simulators that use SUMO traffic data for testing and validation.

SimMobility

• SimMobility is an open-source mobility simulation platform that includes a wrapper for integrating SUMO traffic data. It provides a realistic environment for testing and validation of autonomous driving algorithms.

2.3. Opensource misbehaviour detection simulator

There is an open-source framework available for Misbehavior Detection (MBD) simulation.

The Framework For Misbehavior Detection (F2MD)

• F2MD is free to use and provides a complete solution for real-time simulation and evaluation of an MBD system. F2MD is a VEINS module that extends VEINS with a large panel of MBD, evaluation, and other general Cooperative Intelligent Transport Systems (C-ITS) modules. Additionally, F2MD is a simulation framework used for data-centric misbehavior detection to autonomously identify patterns.

Breach and Attack Simulation (BAS), also known as Adversary Simulation,

• In addition to the field of Misbehavior Detection, there are other open-source tools available for security purposes.
• is an emerging IT security technology that enables security professionals to assess their security infrastructure's detection capabilities against various different kinds of attackers. Open-source BAS tools like Caldera and Atomic Red Team are available for use. 

CERT Workforce Development (CWD)

• Furthermore, internet simulation tools can be used for various purposes, including cybersecurity training.
• The CERT Workforce Development (CWD) Team has recently released a suite of open-source and freely available tools for creating realistic internet simulations for cybersecurity training and other purposes. These tools improve the realism, efficiency, and cost-effectiveness of cybersecurity training.