## [Remote Driving Station: Steering The Future](/spotlight/student-project/remote-driving-station-steering-future) ![IGEN D+ID](/sites/default/files/styles/max_480w/public/spotlight-images/2024-05/Team_IGEN.jpg.webp?itok=b2RSV6Wr) ## Parker Gu, Tony Jiang, Rowan Zawadski, Mankanwar Singh and Harrison Narvey Share- [ ](https://www.facebook.com/sharer/sharer.php?u=https%3A%2F%2F"e= "Share on Facebook") - [ ](https://twitter.com/intent/tweet?source=https%3A%2F%2F&text=:%20https%3A%2F%2F "Tweet") - [ ](http://www.linkedin.com/shareArticle?mini=true&url=https%3A%2F%2F&title=&summary=&source=https%3A%2F%2F "Share on LinkedIn") - [ ](mailto:?subject=&body=:%20https%3A%2F%2F "Send email") - **Degree:** - Bachelor of Applied Science - **Program:** - [Integrated Engineering](https://engineering.ubc.ca/programs/undergraduate/integrated-engineering "Find out more about Integrated Engineering") - **Campus:** Vancouver ## Our project > We designed the Remote Driving Station with the goal of integrating a human-assisted decision-making system into autonomous vehicles. While artificial intelligence excels at recognizing patterns and predicting events based on observed data, the situations encountered on our roadways are often unpredictable. Human intuition, judgment and the ability to understand social cues are still necessary to navigate complex scenarios. For example, Waymo, an autonomous taxi in San Francisco, has been involved in numerous incidents, such as stopping on a fire hose during a fire and driving through a crime scene. > Through our project, we empower human operators to remotely connect to autonomous vehicles, enabling them to assist in making decisions in situations that AI struggles to handle. ![IGEN project](/sites/default/files/styles/max_325x325/public/2024-05/igen_project_1.png.webp?itok=A9UsjoSv) ## Our process This complex project integrated mechanical, electrical and software engineering disciplines. It involved constructing a scaled-down model of the Cybertruck, developing a remote driving station, and creating a user interface. ![IGEN project demonstration](/sites/default/files/styles/max_325x325/public/2024-05/igen_project_2.jpg.webp?itok=fpQxidU2) We designed and 3D-printed a 1:4 scale Cybertruck to serve as our test vehicle, using a custom-fitted chassis on a repurposed kid's ride-on car. To simulate real driving conditions, our vehicle included essential features such as headlights, steering and turn signals. It collected real-time images through front and rear USB cameras and used a GPS-based telemetry system for location and speed data. We also equipped the vehicle with radar on both sides for blind spot detection. > All data collected by our car was sent to our driving station via an onboard computer installed inside the vehicle, connected through Wi-Fi/cellular. ![IGEN project station](/sites/default/files/styles/max_325x325/public/2024-05/igen_project_3.png.webp?itok=xs7-Gztl) > The driving station included a Logitech G29 Driving Force Racing Wheel and Floor Pedals, along with a laptop featuring a dual-monitor setup (one for GPS navigation and one for the dashboard and camera feeds). The user interface (UI) was specifically designed for the driver, providing a comprehensive and intuitive control system. The real-time camera feed was crucial for the UI, offering immediate visual feedback and enhancing the overall driving experience. Our remote system operated ROS2 (Robot Operating System) as its backend, ensuring low-latency communication between the car and the driving station. ![IGEN Poster](/sites/default/files/styles/max_325x325/public/2024-06/igen_poster.png.webp?itok=tVkCwWez) ## The challenges we faced > One of the biggest challenges we faced was minimizing the delay between the driver's actions in the driving station and the car's response. Achieving low-latency (below 50ms) required addressing the bandwidth-intensive nature of camera feed transmission. Initially, the raw camera feeds (1080p, 60FPS) consumed up to 10MB/s when the car was in motion, leading to significant delays. To tackle this issue, we processed the raw camera feeds through ROS2 using the H264 algorithm. This optimization resulted in reliably transmitting a 720p front camera feed and a 240p rear feed, each at 30FPS, consuming under 60 KB/s. This represented a significant improvement of 99.41% in bandwidth utilization. ## What we’re most proud of Our final prototype successfully demonstrated the reliability of our remote system, operating smoothly throughout Design and Innovation Day without encountering any technical issues. Each member of our team brought sophisticated expertise in their respective fields, demonstrating dedication to the project with high-quality finishes. > Furthermore, our mechanical team implemented a systematic car modeling process, employing 3D printing technology to construct the scaled-down Cybertruck. ![IGEN team photo](/sites/default/files/styles/max_325x325/public/2024-05/team_photo.jpg.webp?itok=xdiTERq5) ## Our project’s future We aim to continue our exploration of expediting the advancement of autonomous vehicles by positioning our project as an intermediary step. Our next phase will focus on implementing our remote-control system across a wide range of vehicle types on a larger scale. [ UBC Integrated Engineering ![UBC Integrated Engineering logo](/sites/default/files/styles/max_325x325/public/2026-02/ubc-integrated-engineering-logo-shortname-379x28.png.webp?itok=j5t_Plbi) ](https://www.igen.ubc.ca/ "UBC Integrated Engineering") - [Student Project](/spotlight-type/student-project "Student Project") - [Engineering](/topics/engineering "Engineering") - [International Student Experience](/topics/international-student-experience "International Student Experience") - [Student Experience](/topics/student-experience "Student Experience")