- The 2021 IEEE Autonomous Driving AI Test Challenge
is now an online only event. It will take place from 23rd August to 26th August
- Please check for all training recordings and slides
- Click to See Deliverables
We would also like to remind you that the submissions are accepted through GitHub (NOT via website).
We have sent submission instructions to all registered teams via emails. If you registered but have not received the instructions,
please let us know ASAP by sending emails to email@example.com
Deliverable#1 extended to 05/17/2021, 11:59pm PST.
Deliverable#2 extended to 07/23/2021, 11:59pm PST.
Mar. 24 2021:
We are going to host the first Q&A / demo sessions on March 26 / March 27 and April 9/10. Please click the details
Oct. 26 2020:
Please check the the new Announcement on participating the online challenges. For further details about the online challenges, please take a look at the online venue page.
Testing autonomous driving vehicles refers to a quality assurance process in which diverse validation activities are performed based on well-defined quality assurance standards and assessment criteria. In a quality validation process, unmanned autonomous driving vehicles are validated at different levels (component, integration, and system) based on the pre-defined quality requirements to assure system quality in algorithms, functions, components, behaviors, connectivity, sensing, performance, intelligence, and decision-making in diverse contexts and conditions. To reduce the cost and increase the testing efficiency in the autonomous driving industry, simulation testing receives increasing attention and effort in recent years. A high-fidelity simulation software usually contains the mathematical representations of the environment, the dynamics of autonomous vehicles and surrounding vehicles, the sensors models, etc., at different levels, and is needed to facilitate the testing and development of autonomous driving systems. In order to perform efficient simulation testing, techniques for optimizing and accelerating testing processes are in great demand.
This challenge is set up as a platform to address this demand, and advocate the importance and need of quality validation and automation for autonomous driverless cars. This platform provides a global competition opportunity for international student teams and professional teams to develop diverse simulation testing techniques and approaches in test scenario generation and automation.
In this challenge, LGSVL simulator will be used to support simulation testing and execution. LGSVL simulator is a Unity-based autonomous vehicle simulator developed by LG Electronics America R&D Center. The LGSVL simulator can generate various realistic 3D environments by adjusting environmental parameters including maps, weather, traffic, and pedestrians. It can also simulate different sensor outputs, including camera, Lidar, radar, ultrasonic, etc., and lots of virtual sensors to generate ground truth data (e.g. depth, semantic/instance segmentation, 2D/3D bounding box, etc.). Users can generate and test arbitrary edge case scenarios and simulate billions of miles. LGSVL simulator is fully integrated with the open-source platforms Baidu Apollo and Autoware. In this challenge, teams will use LGSVL integrated with Baidu Apollo to generate and evaluate test cases.
The challenge consists of two phases:
1. Training and team selection. During this phase, training materials including tutorial
videos, documents, and online Q&A sessions will be delivered to the teams so that the
teams will get familiar with LGSVL simulator.
Available training materials:
> Tutorial: End-to-end video tutorial of LGSVL simulator with Apollo driving
> Getting started with LGSVL simulator
> Getting started with Baidu Apollo
> Online course on Software Testing for Complex Intelligent Systems and Autonomous Vehicles, video list
Two Q&A / demo sessions details
(1) March 26, 2021 from 5pm - 6:30pm PST
March 27, 2021 from 9am - 10:30am PST)
(2) April 9, 2021 at 5pm - 6:30pm PST
April 10, 2021 at 9am - 10:30am PST
Please check for all the Zoom links and recordings
2. Competition. During this phase, teams use the traffic accident/crash database to create scenarios, automation scripts,
and UI and submit them for evaluation.
1. Form a team and make your challenge registration via specified challenge platform. Each
team can have up to 6 members.
2. Attend challenge training sessions
3. Work and submit the first phase deliverable. Each team needs to work on deliverable #1 and submit the following artifacts for each scenario to the team’s submission folder in the given challenge submission link.
-- Scenarios and associated scripts
-- Simulation execution report (Note that “Test Results” are not available in LGSVL Simulator 2020.06 which was initially recommended for deliverable #1, so this report is not required for deliverable #1. Teams may instead choose to include any interesting console output generated by the scenario script during the execution of each scenario. If using SVL Simulator 2021.1, a report may be generated by enabling the Create Test Report option, printing the resulting Test Results screen as a PDF and including that report.)
-- Scenario demo videos (e.g. screen capture video; submit link to YouTube, Google Drive, etc.)
-- Selected scenario trip/route and map information (e.g. which maps were used; include descriptions and/or sketches of routes for ego and NPC trajectories)
-- A (written) simulation test report, which documents the generated test scenario scripting methods, and problem findings.
4. Work and submit the second phase deliverable. Each team needs to work on deliverable #2 and submit your challenge project artifacts (same as before, listed above) for each scenario to the team’s submission folder in the given challenge submission link.
5. Final challenge demo and evaluation for selected final teams (for the selected final teams).
6. Final paper submission and presentation for selected final teams (for the selected final teams).
Click to See Deliverables
The results will be evaluated based on
1) Test simulation automation in test simulation modeling, auto-script generation, auto-result validation, auto-coverage analysis, and auto-report
2) Models and methodology
3) Simulation demos based on specified routes, scenarios, and rules
4) The number of test simulation scenarios
The submissions will be evaluated based on the following criteria:
This evaluation criteria listed below provides detailed assessment rubrics for AV test simulation scenario generation and script generation from different teams.
This evaluation criteria listed below provides detailed assessment rubrics for challenge demos given from different teams.
The instructions on how to get started with LGSVL and Apollo including the system requirements can be found at
Each team must have local machines running LGSVL Simulator and Apollo.
LGSVL cloud will be used to run scenarios by judges for verification. LGSVL cloud can run LGSVL Simulator, Apollo ad stack, and scenario/Python scripts. However, users can only view the visualization of recorded data and can see an analysis report of all the simulations after simulations are finished.
Amazon AWS cloud environment
- First place team ($5K)
- Second place team ($3K)
- 2 Third place teams ($2K, each with 1K)
Register for challenge
Registration deadline :
March 15 2021
Training, preparation starts:
First phase challenge submission:
May 7 2021
Notification of selected teams :
May 15 2021
Second phase challenge submission:
July 15 2021
July 23 2021
Complete review and notification:
August 06 2021
AI Test Conference presentations
August 23 2021
Announcement of winners: