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Autoware Centers of Excellence

Make Autoware
Development Easy & Effective

Easy -> Develop a Ready-to-install system supported by training tutorials and Ready to-run use cases through reference designs in simulation & on deployed vehicles.

Efficient -> Develop a solid perception, planning and control stack with well-defined functionality and instructions for extensions.

Working Together

Autoware Foundation Centers of Excellence is initiated at the Pennovation Center of the University of Pennsylvania and now spread over 11 universities in around the world, and continues to expand.

Each Autoware Foundation Centers of Excellence brings fresh energy and effort to make Autoware development easy and efficient mission for a success.

Arizona State University

USA

Operational Safety Testing

Safety evaluation and enhancement for CAVs

Beihang University

China

Control of Connected AVs

(The subpage for this CoE is being updated)

Boğaziçi University

Turkey

System Verification & Validation

Property-based testing and beyond for autonomous systems

City University of Hong Kong

China

Perception and Sensor Fusion

(The subpage for this CoE is being updated)

Clemson University

USA

Verification & Validation

Open autonomy Verification & Validation frameworks

Czech Technical University

Czech Republic

RTOS and Optimization for AVs

Optimization algorithms and real-time support for AVs

ETH Zurich

Switzerland

Full-stack AVs

(The subpage for this CoE is being updated)

Florida Polytechnic University

USA

Validation & Verification

PolyVerif: Autoware-based open-source V&V toolchain

Gyeongsang National University

South Korea

Formal Methods for Safe Autonomy

(The subpage for this CoE is being updated)

HUMDA Lab

Hungary

Autonomous Racing

Using motorsports to promote STEM for young talents.

Nagoya University

Japan

Driving Behaviour & Sensor Signal Processing

Full-stack autonomous driving

National Taiwan University

Taiwan

Real-time AV Stack

Collaborative autonomous systems

Poznań University of Technology

Poland

Perception & SLAM

Perception, planning and SLAM for autonomous vehicles

Purdue University

USA

Digital Twins of Automated Vehicles

Closing Sim2Real Gap

Soongsil University

South Korea

Performance Analysis on AD Stacks

Performance guarantees for Software-Defined Vehicles

SUNY Buffalo

USA

Full-stack AVs

(The subpage for this CoE is being updated)

Technical University of Munich

Germany

Path & Behavioral Planning

Simulation focused development of full stack AV software

TU Delft

Netherlands

Scalable AV Perception and Planning

Developing more scalable AVs to operate in any environment

University of Alberta

Canada

Perception and Control

Safe Connected Autonomous Systems

University of California, Irvine

USA

Software testing and analysis techniques

Assurance of autonomous driving dependability and security

University of Delaware

USA

Real-time Systems

Real-time operation systems for autonomous vehicles

University of Pennsylvania

USA

Learning-based Safe Autonomous Systems

Perception, planning and control for safe autonomous systems

University of Tokyo

Japan

Trustworthiness Assurance and Engineering

Creating a quality assurance methodology to ensure trustworthiness

University of Waterloo

Canada

AV Control, Learning and Logic-based Testing

Bridging the Sim2Real gap in autonomous vehicle testing

Virginia Tech Transportation Institute

USA

Real Time Perception System for Safety of AVs

3D perception system for AVs, and naturalistic driving data acquisition systems.

Xi’An Jiao-Tong University

China

Simulation and Synthesized Data for Safe Autonomous Systems

Yıldız Technical University

Turkey

Perception, Prediction and Control

Developing methodologies for safer mobility

Cutting Edge Research

Check out the latest Autoware-related publications contributed by the Centers of Excellence.

APRIL 11,2018

Autoware on Board: Enabling Autonomous Vehicles with Embedded Systems

2018 ACM/IEEE 9th International Conference on Cyber-Physical Systems (ICCPS)

JUNE 5,2022

Winning the 3rd Japan Automotive AI Challenge - Autonomous Racing with the Autoware.Auto Open Source Software Stack

2022 IEEE Intelligent Vehicles Symposium (IV)

MARCH 17,2023

PolyVerif: An Open-Source Environment for Autonomous Vehicle Validation and Verification Research Acceleration

IEEE Access, vol. 11, pp. 28343-28354, 2023