Simulator List

Choosing a Simulator

< Reference: https://autodrive.readthedocs.io/en/latest/chapters/simulator/comparison.html >

Comparison

../../_images/simulators.gif

Comparison of different simulators:

Table 1: Comparison of Autonomous Simulators

Simulator

Engine

LearningSupport

OpenSource?

Unique Features

Simulator

Deepdrive

Unreal Engine

Tensorflow

YES

+ High FPS due to shared memory+ Terrain is not just flat+ Realistic rendering+ 100GB (8.2 hours) dataset available- Only ground vehicles- Sparse documentation

Deepdrive

Carla

Unreal Engine

TensorFlowChainer

YES

+ Easy to get started- Training code currently unavailable

Carla

Microsoft AirSim

Unreal Engine

CNTK

YES

+ UAV support+ Realtime hardware controller support

Microsoft AirSim

Baidu Apollo

ROSDreamview

TensorflowKeras

YES

+ Support includes free Udacity Apollo course- Hardware focused- Only tested on Lincoln MKZ

Baidu Apollo

Ardupilot

SITL Simulator Gazebo

GymFC

YES

+ UAV support- Hardware focused- Not initially intended for Learning

Ardupilot

TORCS

OpenGL

TensorflowKeras

YES

+ Easy to get started+ Primary research platform for years- Outdated graphics

TORCS

Nvidia DriveWorks

Unreal Engine

Unknown

?

+ Good support for Nvidia GPUs and boards+ Used on Tesla Vehicles

Nvidia DriveWorks

Zoox

Unreal Engine

Unknown

NO

  • Raised $790,000,000

Zoox

Cruise Automation

Unreal Engine

Unknown

NO

  • Raised $3,368,800,000

Cruise Automation

Common notes:

  • All simulators require dedicated GPU

  • Their usage is not always trivial

  • SITL: Software in the Loop

  • Since our objective is for testing in a simulation environment, hardware focused simulators have been given a negative weightage

Knowlegde prerequisites:

  • Linux

  • Python

  • GitHub

  • Docker (Apollo only)

  • Machine Learning Practices

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