The simulation platform has powerful scenario generation capabilities and is fully based on the OpenX standard. Thousands of simulation scenarios can be easily and efficiently generated in a variety of ways, effectively improving the authenticity, effectiveness and coverage of simulation tests, and escorting the mass production of automatic driving.

Dynamic Scenario Editor

Fully compatible with OpenSCENARIO 1.0 standard Support the placement and configuration of static and dynamic objects Support interactive editing of scenario elements such as Event, Action, and Condition Come with OpenSCENARIO text editor with syntax highlighting Support previewing the editing results of the debugging scenario in the case editor

Static Scenario Editor WorldEditor

Fully compatible with OpenDRIVE1.5 Support road and 3D scenario drawing of high-precision maps Preset various traffic element templates Automation tools to improve user editing efficiency Support the generation of high-precision maps through multiple data types Vector data file conversion Combine imagery, point cloud and 3D model sketch

Rich Scenario Generation Methods

Build the scenario through the scenario editor A toolchain based on semantic generalization enables fast definition of scenarios Convert into a scenario that can be used for simulation based on collected data

Scenario Generalization

Provide the ability to generalize scenarios based on parameter combinations Semantic generalization toolchain provides the ability to quickly define and generalize scenarios

Third-Party Scenario Library

Scenario Library of Suzhou Automobile Research Institute of Tsinghua University Rich Dangerous (Edge) Scenarios Special thematic sub-library to meet the special testing needs of users China Automotive Research China typical scenario library v2.0 Standards and regulations, artificial experience data, traffic accident data in China, natural driving data

Perception Simulation

Outstanding sensor simulation ability and physical level real sensor simulation model make test verification more accurate.

Sensor Model

Simulation of physical camera, lidar and millimeter wave radar based on real sensor calibration Support distributed multi-sensor clock synchronization and joint simulation Support hardware in the loop simulation of multiple sensors

High-Fidelity Rendering

Support 24-hour dynamic lighting Support rain, snow, fog dynamic weather system Built-in a large number of high-precision virtual assets Support automatic generation of 3D environment based on OpenDRIVE

Virtual Data Set

Support to generate RGB map, depth map, segmentation map, instance map and true value of object detection Support generating point cloud and true value of object detection

Planning and Control Simulation

Provide multiple simulation modules to easily meet various needs of regulatory testing.

Rich Data Interface

Support for a variety of common data interfaces, such as C++, Python, ROS, Simulink, etc Support various object level sensors, which can directly output target information Support multiple control modes, such as perfect control, brake throttle control, speed control, etc

Traffic Flow Simulation

Support the simulation of various traffic elements, including motor vehicles, non-motor vehicles, pedestrians, traffic lights, traffic rules, etc. Support vehicle following, lane change, intersection conflict model and signal light timing. Support the generation of random dynamic traffic flows in a parametric fashion Support third-party traffic simulation system co-simulation including SUMO, PTV Vissim

Dynamic Simulation

Built-in self-developed 26-degree-of-freedom dynamic simulation engine. Built-in dynamic simulation models of fuel vehicles and electric vehicles. Support the access of third-party dynamics modules such as CarSim®, CarMaker®, VI-grade®, etc. for co-simulation

Driver Model

Built-in driver model SimOne Driver, which can control the vehicle through control signals such as accelerator, brake, steering wheel angle, etc Support driver model and autonomous driving algorithm switching or hybrid control

Evaluation System

There is a rich index library for users to choose and evaluate, covering multiple dimensions such as safety, violation, comfort, efficiency, economic energy consumption, and control accuracy Support users to flexibly configure the scoring function and evaluation weight Support multi-scenario concurrent evaluation Support single-scenario and multi-scenario statistical evaluation

Large-Scale Cloud Simulation Test

The native cloud architecture simulation platform is large-scale and highly concurrent, with a daily cumulative test mileage of 100,000 kilometers.

Cloud Native Architecture

Support large-scale concurrent simulation Support elastic expansion Flexible deployment to public cloud and private cloud Schedule cloud system based on K8S

Online Simulation Tool Chain Based on BS Architecture

Case management tools Scenario editing tools Main vehicle configuration tool Task management tools Simulation visualization tools, etc

Automatic Deployment CI / CD

Provide rich RESTful process control API Support version management of the algorithm via Docker hub Easy to be integrated into mainstream CI/CD frameworks

Multi-User Collaboration

Cloud sharing of data to facilitate multi-role collaboration Support multi-user grouping and role authority management Support algorithm security and encryption management