🧰Relevant Simulation Platforms
Selected relevant simulation platforms, and automated driving developement software tools.
Simulation Platforms/Tools
Simulation Platforms/Tools | Features | Applications |
Open source, highly portable, microscopic, and continuous multi-modal traffic simulation package | Microscopic simulation; Multimodal Traffic; Automated Driving with Transition of Control; Vehicle Communication; Traffic Management | |
Multimodal traffic simulation software (none open source) | Traffic simulation; Mobility Trends; Transportation Planning; Modelling; Operation | |
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Open-source simulator; Flexible API with sensor suite; ROS integration; Maps generation | Training, and validation of autonomous driving systems | |
Simulator built as an extension of CARLA for urban driving in massive mixed traffic; | Testing of crowd-driving algorithms; perception, vehicle control, planning, and end-to-end learning | |
Unity-based multi-robot simulator for autonomous vehicle; integrated with the Duckietown, TierIV's Autoware, and Baidu's Apollo platforms; can generate HD maps | Testing Autonomous Vehicle | |
A simulator for drones, cars and more, built on Unreal Engine; open-source, cross platform, and supports software-in-the-loop simulation | Experiment with deep learning, computer vision and reinforcement learning algorithms for autonomous vehicles | |
A simulator for self-driving; Baseline agent available; Modifiable source; Enable up to eight cameras with depth | Experiment with self-driving AI | |
A driving simulator with key features of : Compositional: generating infinite scenes; Lightweight: it can run up to 300 FPS on a standard PC; Realistic: Accurate physics simulation and multiple sensory input, top-down semantic map | For the research of generalizable reinforcement learning; Single Agent and Multi-Agent simulation | |
A data-driven simulation platform based on Waymo Open Dataset. Default simulation is 10Hz. Support two models for other agents: log playback and an IDM-based route-following model; Direct state-based control, and control via the kinematic bicycle model; Provide adapters to common RLs. | Motion Planning using control theory, data-driven, or reinforcement learning-based methods. Single agent and multi-agent behavior prediction research. | |
A collection of composable benchmarks for motion planning on roads. The benchmarks consist of a scenario with a planning problem, a vehicle dynamics model, vehicle parameters, and a cost function composing a unique ID. | Research on Motion Planning. Evaluating motion planning algorithms in different scenarios and against different benchmarks. | |
A light version of collection of simulated environments for autonomous driving; Based on OpenAI gym | Experiment with autonomous driving and tactical decision-making tasks on: Highway driving; Merging; Roundabout driving; Parking; Intersection; and Racetrack | |
CARLA + SUMO co-simulation environment providing a rich library for Cooperative Driving Automation; | Automated driving components (e.g., perception, localization, planning, control); Connectivity and Cooperation; Full-stack Simulation; CDA Evaluation |
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