Open-Source Based and ETSI Compliant Cooperative, Connected, and Automated Mini-Cars
Authors: Lorenzo Farina, Federico Gavioli, Salvatore Iandolo, Francesco Moretti, Giuseppe Perrone, Matteo Piccoli, Francesco Raviglione, Marco Rapelli, Antonio Solida, Paolo Burgio, Carlo Augusto Grazia, Alessandro Bazzi
Organizations: DEI, Università di Bologna, 40136 Bologna, Italy · National Laboratory of Wireless Communications (WiLab), CNIT, 40136 Bologna, Italy · DIEF, University of Modena and Reggio Emilia, 41125 Modena, Italy · Dipartimento di Automatica e Informatica, Politecnico di Torino, 10129 Torino, Italy · Dipartimento di Elettronica e Telecomunicazioni, Politecnico di Torino, 10129 Torino, Italy
The automotive sector is following a revolutionary path from vehicles controlled by humans to vehicles that will be fully automated, fully connected, and ultimately fully cooperative. Along this road, new cooperative algorithms and protocols will be designed and field tested, which represents a great challenge in terms of costs. In this context, in particular, moving from simulations to practical experiments requires huge investments that are not always affordable and may become a barrier in some cases. To solve this issue and provide the community with an intermediate step, we here propose the use of 1:10 scaled cooperative, autonomous, and connected mini-cars. The mini-car is equipped with a Jetson Orin board running the open Robot Operating System 2 (ROS2), sensors for autonomous operations, and a Raspberry Pi board for connectivity mounting the open source Open Stack for Car (OScar). A key aspect of the proposal is the use of OScar, which implements a full ETSI cooperative-intelligent transport systems (C-ITS) compliant stack. The feasibility and potential of the proposed platform is here demonstrated through the implementation of a case study where the Day-1 intersection collision warning (ICW) application is implemented and validated.
Figures & tables
Fig. 1 : Cooperative, connected and automated mini-car, equipped with the low-cost OBU.
Fig. 2 : Block scheme of the hardware components.
Fig. 3 : Block diagram of the OScar stack and its main functional components
Device
Details
Cost
F1tenth
Chassis
Radio-controlled Traxxas mini-car
450 €
Core control unit
Jetson Orin Nano Super/NX
350/800 €
SD and SSD cards
Memories for the control unit
30 €
LiDAR
2D Hokuyo UST-10LX
1500 €
VESC
Car mobility controller with inertial sensor
250 €
TABLE I : List of hardware components and indicative prices.
Fig. 4 : Environment used to test the applications.
Fig. 5 : Screenshot of the map with red points illustrating the position of mini-car A as indicated in its transmitted CAM .
Fig. 6 : External and on-board views of three experimental phases. (a–-c) External camera snapshots of the three phases: mini-car A away from the intersection area, approaching the intersection area and crossing the intersection area, respectively. (d–-f) Corresponding on-board (vehicle perspective) views for the same phases.
Autonomous driving develops vehicles that perceive road scenes, predict interactions, and plan and control safe movement with limited or no human input.
Intelligent Transportation Systems (ITS) increasingly rely on vision-based perception and learning-based control, necessitating experimental platforms that support realistic hardware-in-the-loop validation. Small-scale platforms for autonomous racing offer a practical path to hardware validation, but often suffer from limited modularity, high integration complexity, or restricted extensibility. This paper presents TEACAR, a 1/14- to 1/16-scale autonomous driving platform designed with modular mechanical architecture, hardware abstraction, and ROS 2-based software. The system adopts a four-layer deck structure that physically decouples sensing, computation, actuation, and power subsystems, improving structural rigidity while simplifying reconfiguration. We constructed and comprehensively evaluated the prototype of TEACAR. Its mechanical stability, structural characteristics, and software performance were quantified based on three CNN-based steering controllers. Inference latency, power consumption, and system operating time were measured to evaluate computational capability and robustness. Our experiments demonstrated that TEACAR offers a scalable, modular, and cost-effective testbed for ITS research, education, and development. Our project repository is available on GitHub.
Zhongzheng Zhang, Maxwell Ruyle, Andrew Kappes +5
Trustworthy Engineered Autonomy (TEA) Lab, Department of Electrical and Computer Engineering, University of Florida
OpenPodcar2 is a robust, ROS2-interfaced, low-cost, open source hardware and software, autonomous vehicle platform based on an off-the-shelf, hard-canopy, mobility scooter donor vehicle. It is a modification of the previous OpenPodcar design, which extends it with robust electronics and ROS2 interfacing, to enable both research and also potential deployment use cases. The platform consists of (a) hardware components: documented as a bill of materials and build instructions; (b) integration to the general purpose OSH R4 mechatronics board and a Gazebo simulation of the vehicle, both presenting a common ROS2 interface (c) higher-level ROS2 software implementations and configurations of standard robot autonomous planning and control, including the nav2 stack which performs SLAM and enacts commands to drive the vehicle from a current to a desired pose around obstacles. OpenPodcar2 can transport a human passenger or similar load at speeds up to 15km/h, for example for use as a last-mile autonomous taxi service or to transport delivery containers similarly around a city center. It is small and safe enough to be parked in a standard research lab robust enough for some deployment cases. Total build cost was around 7,000USD from new components, or 2,000USD with a used Donor Vehicle. OpenPodcar2 thus provides a research balance between real world utility, safety, cost and robustness.
Rakshit Soni, Chris Waltham, Md Umar Ibrahim +2
School of Engineering and Physical Science, University of Lincoln, UK
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.