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Fusion Processing is leading a collaborative effort to introduce No User In Charge (NUIC) automated driving technology into operational London bus depots. This initiative focuses on enhancing safety, efficiency, and space utilization through advanced automation systems integrated with electric buses.
Key Highlights
- Partnership Involved: Fusion Processing teams up with Transport for London (TfL), Alexander Dennis, and Metroline for a ten-month feasibility study.
- Technology in Use: The project employs Fusion Processing’s CAVstar Automated Drive System (ADS) for precise bus maneuvers in constrained depot spaces.
- Demonstration Phases: Trials start with off-highway testing, progressing to live depot environments with remote monitoring and eventual driverless operations.
- Funding Source: Supported by the UK Government’s CAM Pathfinder Feasibility Studies Competition, part of a £150 million program to advance connected and autonomous mobility.
- Potential Benefits: Aims to improve depot safety, reduce costs, and optimize space without expensive infrastructure upgrades.
Project Overview and Objectives
The consortium is evaluating how NUIC automation can assist in safe and efficient bus movements within depots, including navigation to cleaning bays, charging points, and parking positions. Fusion Processing’s CAVstar system will be installed on demonstration buses, both diesel and electric models, to demonstrate its adaptability in dense urban settings. A key feature is the development of a remote operator interface for real-time monitoring and intervention, ensuring high safety standards.
The trials build on prior collaborations between Alexander Dennis and Fusion Processing, now extending to electric vehicles with enhanced remote capabilities. Metroline contributes by providing depot access and insights into operational impacts, such as infrastructure, insurance, and safety protocols.
Technological Implementation
Testing commenced with off-highway validation of the CAVstar system, equipped with redundant steering and braking on an Alexander Dennis Enviro100AEV electric bus and an Enviro200AV. Once validated, operations shift to live depots, initially with a safety driver aboard, then transitioning to fully autonomous modes under remote supervision. Trained operators in a control center remain ready to intervene.
The buses achieve maneuver accuracy of 2 to 3 centimeters using an advanced sensor suite—radar, lidar, and cameras—for a 360-degree environmental view. This SAE Level 4 capability enables precise path determination and execution in complex layouts.
Broader Impacts and Future Potential
Automation in bus depots addresses challenges like high relocation costs and operational disruptions. By implementing NUIC technology, the project promises smarter solutions: boosted safety through reduced human error, cost savings via efficient space use, and support for electric fleet integration.
Jim Hutchinson, CEO of Fusion Processing, emphasized the project’s role in advancing autonomous systems for real-world applications, paving the way for broader adoption in urban transport.
About the Partners
Fusion Processing, founded in 2012, specializes in vehicle automation and safety systems. Its innovations, including the CAVstar platform, have logged over 2 million kilometers in trials and operations.
Visit www.fusionproc.com for more details.
The Centre for Connected and Autonomous Vehicles (CCAV), a joint unit of the Department for Transport and Department for Business and Trade, drives UK policies on connected and autonomous vehicles.
Zenzic champions the UK’s connected and automated mobility ecosystem, fostering innovation to position the nation as a global leader.
Innovate UK, under UK Research and Innovation, supports companies in developing and commercializing new technologies through an inclusive innovation network.
This project exemplifies how collaborative efforts in autonomous driving technology can transform public transport operations, particularly in space-limited environments like London bus depots. With a focus on feasibility and real-world demonstrations, it sets a foundation for scalable, efficient urban mobility solutions.
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