karl. -- A Research Vehicle for Automated and Connected Driving

2026-02-09

AI Summary

This work addresses the lack of accessible, open platforms for Level 4 autonomous driving research outside large enterprises, which hinders independent development and validation of advanced autonomous technologies in academia and small-to-medium institutions. To bridge this gap, we present and open-source *karl.*, a flexible and extensible L4 autonomous driving research platform that integrates perception, decision-making, control modules, and a C-ITS (Cooperative Intelligent Transportation Systems) communication system. The platform enables real-world deployment of algorithms, data collection, and demonstration of cutting-edge applications under actual road conditions. By providing non-industrial researchers with robust vehicle-based validation capabilities, *karl.* has already facilitated the construction of public datasets and validation of novel driving scenarios, thereby fostering open collaboration and innovation in autonomous driving research.

Technology Category

• Application Domains: Mobility, Driving & Flight
• Planning, Routing, and Scheduling: Planning with Language Models
• Computer Vision: Vision for Robotics & Autonomous Driving

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• Search and Retrieval-Augmented AI: Multilingual and cross-lingual Web search
• Responsible Web: Machine-in-the-loop, human agency and autonomy

Abstract

As highly automated driving is transitioning from single-vehicle closed-access testing to commercial deployments of public ride-hailing in selected areas (e.g., Waymo), automated driving and connected cooperative intelligent transport systems (C-ITS) remain active fields of research. Even though simulation is omnipresent in the development and validation life cycle of automated and connected driving technology, the complex nature of public road traffic and software that masters it still requires real-world integration and testing with actual vehicles. Dedicated vehicles for research and development allow testing and validation of software and hardware components under real-world conditions early on. They also enable collecting and publishing real-world datasets that let others conduct research without vehicle access, and support early demonstration of futuristic use cases. In this paper, we present karl., our new research vehicle for automated and connected driving. Apart from major corporations, few institutions worldwide have access to their own L4-capable research vehicles, restricting their ability to carry out independent research. This paper aims to help bridge that gap by sharing the reasoning, design choices, and technical details that went into making karl. a flexible and powerful platform for research, engineering, and validation in the context of automated and connected driving. More impressions of karl. are available at https://karl.ac.

Problem

• automated driving
• connected driving
• research vehicle
• L4 autonomy
• C-ITS

Innovation

• research vehicle
• L4 autonomous driving
• connected driving
• real-world validation
• C-ITS