2024 Tournament Competition Overview

Competition outline

Please check the page below for development environment and competition details.
https://automotiveaichallenge.github.io/aichallenge-documentation-2024/index.html

Team Introduction (Advanced Class)

iASL (Gifu University)

Overview

This is the Alex Laboratory, an iASL (intelligent Autonomous Syst ems Lab) in the Department of Electrical, Electronic and Information Engineering (Information Course), Faculty of Engineering, Gifu University. The group consists of 4 members, including B1, M1 and D10, and is researching autonomous driving. Although they struggled with self-location estimation in last year's Integration Competition Finals, they won second place in the preliminaries. In last year's winter racing-themed simulation competition, two members won the Community Contribution Award.

Strategy

This year marks the second year since iASL was established. With the busy first year over, we will make further leaps from here. We plan to deeply integrate both hardware and software, and to achieve intelligent performance and driving, as the name of the laboratory suggests.

Pictures

teammate

Japan Automotive AI Challenge2023 (Integration) Final

Other

Current interests of our lab:
LiDAR, autonomous racing, autonomous safety, event camera, E2E, LLM, ASV (small unmanned boat), SLAM

TPAC (Team Panasonic Automotive Challengers)

Overview

We are a volunteer team primarily made up of members from Panasonic Automotive Systems.
We are a group of mobility enthusiasts who enjoy working together. In previous Japan Automotive AI Challenges, we have achieved success by placing highly in the simulation competition, advancing to the finals of the integration competition, and winning the Community Award.

Strategy

In addition to pursuing robustness and a deeper technical understanding of autonomous driving systems, the team will utilize the skills of all members of the team to compete in competitions.
Our strength is our willingness to learn new things. We will take on the challenges in a cheerful, fun and cooperative manner, making use of the strengths of our members, such as their Robocon experience, research activities and curiosity about mobility.

Pictures

Group photo

Japan Automotive AI Challenge 2023 (Integration) Final Venue

Other

Volunteer Activity Site Link Technology Challenge Department: https://challenge-club.connpass.com

ADRobo Racing Members of TOYOTA MOTOR CORPORATION

Overview

We are a team of three people from the same department at Toyota Motor Corporation. We formed the team after participating in the winter autonomous driving simulation competition together. Each member has a wide range of expertise and experience in areas such as vehicle dynamics, autonomous mobile robots, small formula car production, and autonomous driving technology development, and we are working on development by making the most of each of our strengths. At the last racing simulation competition, we were able to take advantage of our strengths and win the top prize.

Strategy

Our goal is to realize "autonomous driving that feels like a human being driving." Specifically, we are focusing on developing a planner that can automatically generate driving routes that experienced drivers would choose. To achieve this, we are collecting driving data from experienced drivers and developing software that uses machine learning technology to imitate their driving based on that data.

Pictures

Ugajin

Kodama

Yokota

B(oo)ARS (former Kobe National College of Technology)

Overview

B(oo)ARS is a team formed by former members of the Kobe Tech Robot Contest Club. The members are Eguchi, a second-year master's student at the University of Tsukuba, Hara, and Harada, both working adults, and each of them is working on developing autonomous mobility algorithms in different fields. This is their second year competing in the Japan Automotive AI Challenge, and last year they placed fourth in the simulation division.

Strategy

We have extensive experience in integrating outdoor mobile robots through the Tsukuba Challenge and developing autonomous mobility algorithms through research activities. We will fully utilize this experience to build a robust autonomous mobility system and develop advanced autonomous mobility algorithms to ensure victory.

Pictures

Participate in the Tsukuba Challenge (completed in 2023)

Research on autonomous mobility algorithms

Other

In addition to the activities mentioned here, we are engaged in a wide range of other activities. Please refer to each member's portfolio for details.
Eguchi: https://eguchis-portfolio.super.site/
Original: https://hrjp.github.io
Harada:https://autumn60.github.io/

CIT CATS (Chiba Institute of Technology)

Overview

We are a four-person team consisting of members of the Ueda Laboratory of the Department of Future Robotics at Chiba Institute of Technology and alumni. All team members are conducting research on autonomous mobility. Team member Ikebe has been participating since the year before last. We won the 2022 simulation competition.

Strategy

CIT CATS has expanded its team by welcoming new members with diverse robot competition experience, ranging from third-year undergraduate students to first-year master's students. We will win again this year!!!

Pictures

Other

Areas of Interest
・Probabilistic robotics, self-localization, behavioral decision-making

Rits-Auto (Ritsumeikan University)

Overview

The participants are members of the Nishio Laboratory at the Faculty of Information Science and Engineering, Ritsumeikan University (9 people).

In addition to autonomous driving, our laboratory is conducting a variety of research projects, including positioning and recommendation systems using various sensors.This year, the team size limit was lifted, and seven people not involved in the autonomous driving field participated (keywords: PDR, UWB, IMU, etc.).
We will aim to win a top prize by utilizing our diverse backgrounds and research knowledge!!

This will be the third time in a row that we have participated in the Integration Competition. In the 3 Integration Competition, we placed 3th in the Challenge Class qualifying round and advanced to the finals, and in the 2022 Integration Competition, we placed 9rd in the Student Division qualifying round and advanced to the finals.

Strategy

Until now, we have not been able to perform the runs we have prepared in the final competition using a real car, so this year we will do our best to reproduce 100% of what we have prepared.

Pictures

AIChallenge 2022 Integration Competition Final

Japan Automotive AI Challenge2023 (Integration) Final

Recommended environment

here Please confirm