Transforming road safety for two-wheel mobility through AI and computer vision
Safety has always been a central concern for mobility. Yet while cars have benefited from decades of driver-assistance innovation, cyclists and motorcyclists still lack comparable tech-enabled safety systems, despite high exposure to risk and a pivotal role in sustainable, multimodal urban mobility systems.
Luna Systems responds to these persistent and wide-spread rider safety concerns by bringing computer vision and edge AI to two-wheel mobility through an integrated hardware-and-software rider-assistance solution that works in real time and after the ride. Its camera-based systems deliver contextual in-ride warnings and post-ride safety insights that help riders anticipate risk, build confidence and travel more safely in shared traffic environments. For EIT Urban Mobility, this is impact-driven innovation: accelerating safer uptake of cycling and light mobility as practical, sustainable modes for everyday trips.
Highlights of why we invested in Luna Systems
- Cycling safety: Luna Systems has developed a rear-facing AI camera paired with a smartphone app for cyclists, delivering contextual in-ride alerts (e.g., vehicle proximity and higher-risk passing situations) alongside post-ride incident review and mapping to identify risk hotspots and support safer route choices.
- Advanced Rider Assistance Systems (ARAS): Luna Systems has developed ARAS for bikes and powered two-wheelers, designed for OEM integration. Safety functions include headway monitoring, forward collision warning, road-surface and pedestrian detection, plus rear-proximity and blind-spot awareness, including Luna’s proprietary AI Reverse Blind Spot Detection.
- Post-ride intelligence and safety coaching: Luna Systems technology ensures that data is interpreted, not just recorded, so riders can review incidents, identify risk hotspots, and adjust behaviour and route choices over time.
- Scalable edge AI on constrained hardware: Models are optimised for low-power, cost-constrained devices suitable for bikes and powered two-wheelers, supporting real-time performance at price points that can scale beyond premium segments.
- Privacy-by-design: Privacy-sensitive measures, including facial and number plate blurring, are embedded in Luna Systems’ solutions, supporting practical deployments without exposing identifiable road users, aligning with GDPR-oriented practices.
- Clear route to scale: The recent €1.5m late-seed round (led by Fundracer Capital with EIT Urban Mobility, and Enterprise Ireland) supports Luna’s shift from software-only delivery to market-ready camera hardware and expanded OEM integration pathways.
- Policy-aligned solutions: Luna Systems’ platform supports major road-safety and sustainable mobility priorities, including the UN Decade of Action for Road Safety (2021–2030), the UN Decade of Sustainable Transport (2026–2035), and the EU Urban Mobility Framework.
Peter Vest, Senior Investment & Portfolio Manager at EIT Urban Mobility, highlights the strategic rationale for continuing support as Luna builds on its earlier shared-mobility deployments and refocuses its advanced computer-vision expertise on cycling and motorcycling safety:
“We are proud to continue supporting Luna, a company that embodies EIT Urban Mobility’s mission to make urban mobility safer. We are equally delighted to welcome Fundracer, whose deep expertise in the cycling industry brings invaluable insight. With both investors actively engaged in advancing mobility innovation, I am confident we can help Luna scale across Europe and beyond to make cycling more accessible for all.”
Computer vision rider assistance for two-wheel mobility
Founded in Dublin in 2020 by Maria Diviney and Andrew Fleury, Luna Systems develops computer-vision rider-assistance systems for cycling and powered two-wheelers. The ambition is clear: provide the situational awareness tools riders need to feel confident choosing cycling and light mobility for everyday trips.
At the core of Luna Systems’ solutions is a camera-based edge-AI stack that turns live-video inputs into actionable safety insights for riders, both during a journey and after it. In 2026, Luna is taking these capabilities from software-only delivery into market-ready camera hardware, starting with a rear-facing consumer camera and expanding into single- and dual-camera configurations for OEM integration.
Luna’s camera-based edge-AI computer vision stack delivers:
- Real-time rider assistance: the Advanced Rider Assistance Systems (ARAS) use single or dual cameras with embedded software to deliver real-time alerts: headway monitoring, forward collision warnings, road-surface and pedestrian detection, plus rear-proximity and blind-spot alerts, including Luna’s proprietary AI Reverse Blind Spot Detection.
- Post-ride safety coaching: The same vision data is mapped into incident analysis and coaching insights, revealing risk hotspots to help riders adjust behaviour and improve route choices over time.
From pilots to market scale: privacy, integration and deployment pathways
Because Luna Systems’ approach relies on interpreting images captured in public space, privacy-by-design is a key feature of their offer. With privacy protection measures, including facial and number plate blurring, Luna Systems enables safety insights without exposing identifiable personal data, supporting GDPR-aligned practices.
To scale, Luna is moving from software-only delivery into market-ready camera hardware, while advancing OEM and Tier-1 integration pathways. Notably, at Eurobike 2025, the company presented a dual AI-camera ARAS system for the OEM e-bike market, combining front and rear vision, real-time safety alerts, and multiple integration options (including embedded and retrofit alternatives).
Looking beyond Europe, Luna has also extended its ARAS work into India’s motorcycle market, a proving ground where dense traffic, diverse road conditions, and extreme price sensitivity demand technology that’s both robust and affordable, helping validate and refine the system for effective global scaling.
Policy and regulatory context
The European Commission’s New EU Urban Mobility Framework explicitly links the transition to sustainable urban mobility with safer streets. Similarly, the EU’s Road Safety Policy Framework 2021–2030 sets out the next steps towards Vision Zero, reinforcing a Safe System approach and the objective of halving road deaths and serious injuries by 2030, with particular attention to vulnerable road users, including motorcyclists and cyclists. It also underlines the importance of stronger, more granular safety data to target preventive measures effectively – an area where computer vision can help by interpreting road interactions and identifying recurring risk situations for riders (e.g., close passes, blind-spot exposure, and conflict points) at scale.
The policy emphasis on road safety reflects a real adoption constraint: while a study has found that 52% of people globally believe cycling in their area is too dangerous, EU road-safety statistics show why: almost 70% of fatalities in urban areas are vulnerable road users, including pedestrians, cyclists and users of powered two-wheelers.
At global level, the UN Decade of Action for Road Safety (2021–2030) sets an ambition to prevent at least 50% of road traffic deaths and injuries by 2030, while the UN Decade of Sustainable Transport (2026–2035) positions safe, accessible and low-carbon transport as an enabling condition for development.
It is noteworthy that regulation for rider-assistance on two-wheelers, however, is still evolving.
Unlike passenger cars, where multiple driver-assistance functions have established regulations, there is not yet an equivalent, harmonised set of ARAS requirements for L-category vehicles across markets. At the same time, it is important to notice that policy is beginning to catch up with connected two-wheelers, illustrated by UNECE’s move to extend UN Regulation No. 155 on cybersecurity to motorcycles (L-category).
In this evolving context, Luna Systems’ approach is well positioned to support both sustainable urban mobility policy direction and road-safety agendas.
Looking ahead
EIT Urban Mobility recognises that Luna Systems addresses a critical gap in the transition to sustainable urban mobility: making two-wheel journeys safer for riders and lowering a key adoption barrier – real and perceived safety risk – that prevents many people from choosing cycling and light mobility for everyday travel. We look forward to keep supporting Luna Systems as it scales its computer-vision rider-assistance solutions across European cities and into wider two-wheeler markets globally.
Do you want to know more about Luna Systems mission and its solutions?
Visit the company website and LinkedIn.
This article is part of Why we invested? Series presenting EIT Urban Mobility equity portfolio.