Open-Source Based and ETSI Compliant Cooperative, Connected, and Automated Mini-Cars

This paper proposes a cost-effective, open-source platform utilizing 1:10 scaled mini-cars equipped with ROS2 and an ETSI-compliant OScar stack to bridge the gap between simulation and field testing for cooperative, connected, and automated vehicle research, demonstrated through a validated intersection collision warning application.

The Gist

Imagine the future of driving not as a single, massive leap, but as a series of smaller, safer steps. We are moving from cars driven entirely by humans, to cars that can drive themselves, and finally to cars that can "talk" to each other to avoid accidents.

But here's the problem: Testing these high-tech, talking cars on real highways is incredibly expensive and dangerous. If you want to test a new "collision avoidance" feature, you don't want to crash a $50,000 car just to see if the software works.

The Solution: A "Toy" Car That Thinks Like a Real One

This paper introduces a clever middle ground: a 1:10 scale mini-car. Think of it as a high-tech, autonomous version of a remote-controlled toy car, but one that speaks the exact same language as real-world vehicles.

Here is how the team built this "smart toy" and why it matters, broken down into simple parts:

1. The Body: The "Race Car" Chassis

The team started with a standard remote-controlled car chassis (the Roboracer/F1tenth platform). It's like the skeleton of a race car.

• The Brains: Instead of a human driver, they put a powerful computer (NVIDIA Jetson Orin) inside. This is the car's brain, running ROS2 (Robot Operating System), which is like the "Windows" or "macOS" for robots.
• The Eyes: They added a LiDAR sensor. Imagine this as a super-accurate, 360-degree laser flashlight that constantly scans the room to build a digital map of where everything is.
• The Muscles: The car has electric motors for speed and steering, controlled by the brain to drive itself around a track without crashing.

2. The Voice: The "Talker" (The OBU)

This is the most important part. A car that drives itself is cool, but a car that talks to other cars is revolutionary.

• The Hardware: They attached a small, cheap computer (a Raspberry Pi 5) to the car. This acts as the car's "walkie-talkie."
• The Language (OSCar): Usually, cars use complex, expensive, proprietary software to talk to each other. This team used OSCar, an open-source software that speaks the official European language for car communication (ETSI C-ITS).
  • Analogy: If real cars speak a secret, expensive dialect, this mini-car speaks the official, open-source "UN language" of the road. It can say things like, "I am turning left," or "I am 5 meters away," in a way that any standard-compliant car would understand.

3. The Cost: "Lego" vs. "Ferrari"

Building a full-size autonomous test car can cost hundreds of thousands of dollars.

• The Mini-Car Cost: The team managed to build this entire system for about 3,000 Euros (roughly $3,200).
• Why it matters: It's like comparing building a full-scale Ferrari to build a high-end Lego Ferrari. You can crash the Lego one a hundred times, break it, fix it, and test crazy new ideas without losing your shirt. It makes research accessible to universities and small teams, not just giant car companies.

4. The Test: The "Intersection Warning" Game

To prove it works, they created a simple game: The Intersection Collision Warning (ICW).

• The Setup: They built a small oval track with a "crossing" in the middle (an intersection).
• The Players:
  • Car A: Drives around the oval automatically.
  • Car B: Sits still at the intersection, waiting.
• The Drama:
  1. Car A is far away. Car B doesn't know it's there.
  2. Car A gets closer. It sends a digital "Hello, I'm coming!" message (a CAM message) via its Raspberry Pi.
  3. Car B receives the message before it can even see Car A with its camera.
  4. The Result: Car B's computer immediately flashes a warning light on a screen: "DANGER! A car is approaching!"

This proves that even before the cars can see each other with their "eyes" (cameras), they can "hear" each other with their "ears" (radio), preventing a crash.

The Big Picture

This paper isn't just about building a cool toy. It's about democratizing the future of driving.

By creating a low-cost, open-source platform that follows strict international standards, the researchers are saying: "You don't need a billion-dollar budget to test the future of traffic. You just need a smart mini-car, some open-source code, and a track."

This allows scientists to test safety features, traffic algorithms, and emergency protocols quickly and cheaply, paving the way for the day when our real, full-size cars can talk to each other to keep us all safe.

Technical Summary

Here is a detailed technical summary of the paper "Open-Source Based and ETSI Compliant Cooperative, Connected, and Automated Mini-Cars."

1. Problem Statement

The automotive industry is transitioning toward fully automated, connected, and cooperative vehicles. However, validating new cooperative algorithms and protocols presents a significant challenge:

• Cost Barrier: Moving from simulation to full-scale field tests requires massive investments in real vehicles and infrastructure, which are often unaffordable for many research groups.
• Gap in Existing Solutions: While scaled-down testbeds exist (e.g., Duckietown, F1tenth), most lack a full, standard-compliant communication protocol stack. Many rely on proprietary or simplified Wi-Fi solutions that do not accurately replicate real-world Cooperative Intelligent Transport Systems (C-ITS) standards (specifically ETSI standards).
• Need for an Intermediate Step: There is a critical need for a scalable, low-cost, yet standards-compliant platform that bridges the gap between simulation and full-scale field trials.

2. Methodology

The authors propose a novel hardware and software platform based on 1:10 scaled mini-cars designed to replicate the functionality of full-sized vehicles while adhering to ETSI C-ITS standards.

A. Hardware Architecture

The platform consists of two main computational units integrated into a Roboracer (F1tenth) chassis:

1. Autonomous Control Unit:
   • Hardware: NVIDIA Jetson Orin (NX or Nano Super).
   • Sensors: 2D LiDAR (Hokuyo UST-10LX) for localization and navigation; VESC motor controller with an inertial sensor (BMI160).
   • Software: Runs ROS2 (Robot Operating System 2). The stack includes a particle filter for localization and a pure pursuit algorithm for trajectory following.
2. C-ITS On-Board Unit (OBU):
   • Hardware: Raspberry Pi 5 Model B connected via a PCIe HAT to a MikroTik R11e-5HnD wireless card (Qualcomm Atheros AR9580 chipset).
   • Connectivity: The wireless card is modified via software patches to the ath9k Linux driver to support the 5.9 GHz ITS band and IEEE 802.11p (DSRC) operation, enabling ETSI ITS-G5 messaging.
   • Cost: The OBU hardware costs approximately €150, significantly lower than commercial V2X solutions.

B. Software Stack: OScar

The core innovation is the use of OSCar (Open Stack for Car), a fully open-source (GPLv2) implementation of the ETSI C-ITS networking stack.

• Compliance: It implements the full ETSI protocol stack, including the transmission of Cooperative Awareness Messages (CAMs).
• Modularity: Designed for low-power embedded systems, it can be compiled into a single <3 MB executable.
• Functionality:
  • Supports ETSI Decentralized Congestion Control (DCC).
  • Maintains a Local Dynamic Map (LDM) populated by V2X messages and on-board sensor data.
  • Provides a JSON-based API over TCP for external applications to query LDM data (e.g., relative distance, kinematic state of surrounding vehicles).
  • Supports multiple positioning sources, including a virtual GNSS provider that converts local Cartesian coordinates into NMEA sentences for the stack.

3. Key Contributions

1. First Full Standard-Compliant Scaled Platform: To the authors' knowledge, this is the first 1:10 scaled testbed that implements a full ETSI C-ITS compliant protocol stack (including 5.9 GHz 802.11p and ITS-G5 messaging), distinguishing it from previous Wi-Fi-based scaled solutions.
2. Cost-Effective Scalability: The total cost of the autonomous mini-car is approximately €3,000, with the specialized OBU costing only €150. This makes large-scale multi-vehicle experiments feasible for academic and research institutions.
3. Open-Source Ecosystem: The entire stack (ROS2 drivers, OScar, configuration scripts) is open-source, allowing the community to customize, extend, and reproduce the experiments without licensing fees.
4. Hybrid Positioning Integration: The system successfully bridges the gap between local sensor-based localization (Jetson) and V2X positioning requirements (OBU) by converting local coordinates to standard NMEA formats.

4. Results (Case Study: Intersection Collision Warning)

The authors validated the platform by implementing a Day-1 Intersection Collision Warning (ICW) application.

• Experimental Setup: An oval track with a simulated intersection. Mini-car A moved autonomously at 1 m/s; Mini-car B remained stationary.
• Process:
  • Mini-car A transmitted CAMs containing its position and kinematic data.
  • Mini-car B's OBU received these messages and updated its LDM.
  • A Python script queried the LDM via the OScar API to detect if Mini-car A was approaching the intersection.
• Outcome:
  • The system successfully detected the approaching vehicle before it was visually visible to Mini-car B's camera.
  • A visual warning was triggered on a connected screen, demonstrating the system's ability to prevent collisions using V2X data rather than just line-of-sight sensors.
  • The system handled coordinate scaling (1:10) and speed calculations correctly, generating warnings with appropriate latency.

5. Significance

• Bridging the Simulation-Reality Gap: This platform offers a crucial "intermediate step" for researchers. It allows for the testing of complex cooperative algorithms in a physical environment with realistic communication constraints (latency, packet loss, standard compliance) without the prohibitive cost of full-sized vehicles.
• Standardization Validation: By using a strict ETSI-compliant stack, the platform ensures that research results are directly transferable to real-world deployment scenarios, validating protocols like CAM and DCC in a controlled setting.
• Future Roadmap: The authors plan to expand the platform's capabilities to Day-2 (Collective Perception) and Day-3+ (Maneuver Coordination) applications, specifically targeting complex intersection scenarios.

In conclusion, this work provides a robust, affordable, and standards-compliant foundation for the next generation of cooperative autonomous vehicle research, democratizing access to C-ITS field testing.