In an era where cities are becoming smarter, more connected, and more complex, innovation demands collaboration. At Cubic, innovation doesn’t begin in the lab; it begins in the field. It starts when a rider hesitates at a gate, when an operator flags an unexpected pattern, or when a transit agency challenges us with a problem that may not even have a name yet.
Every partnership, whether with a customer or a research institution, is an opportunity to learn. To see how our systems perform in the real world, and how they can perform even better. Customers are not just clients; they’re collaborators, co-creators, and the ultimate source of truth about what works and what doesn’t. Their feedback often reveals friction points and opportunities that spark entirely new innovations.
From rider research that uncovers hidden accessibility challenges, to agency-led pilots that expose data blind sports, these insights challenge our assumptions and inspire us to think differently. When we combine those real-world perspectives, with the analytical depth of our academic partners, powerful things happen. New technologies emerge, policies evolve, and smarter, more equitable mobility becomes possible.
At Cubic, innovation is not a department. It’s a conversation. One that connects riders, customers, engineers, and researchers in a shared mission – to make every journey simpler, fairer, and more connected than the last.
Why Academic Partnerships Matter
The transport ecosystem is evolving fast, shaped by urban growth, sustainability goals, changing travel patterns, and the rise of intelligent systems. Meeting these challenges requires both technical expertise and fresh thinking. Academic partnerships provide exactly that.
At Cubic, collaboration with universities enable access to:
Cutting-edge research to solve real world challenges
Through working with leading universities across the world Cubic brings together the strengths of both worlds – the rigor and curiosity of academia with the scale, practicality and market insight of industry. Whether it’s modeling passenger behaviors, improving fare equity or developing more reliable ticketing infrastructure, academic partnerships enable cutting-edge research that helps Cubic push boundaries that no organization could reach alone.
Independent validation that strengthens trust and credibility
Academic partnerships provide an external lens that ensures our innovations are not only effective, but also evidence-based and ethically sound. When new algorithms, fare models or maintenance approaches are assessed and validated by independent researchers, the results carry greater weight with our customers, policymakers, and the travelling public. Academic partnerships add rigor to our work, reduce bias, and build confidence that our solutions will perform as promised.
A pipeline of emerging talent that fuels future innovation
Academic partnerships create a steady flow of fresh thinkers who bring new energy, skills, and perspectives to our innovation ecosystem. Students, PhD candidates, and postdoctoral researchers collaborating with our teams are often at the forefront of their disciplines. Their curiosity challenges established approaches, introducing novel ideas and tools that keep our solutions evolving. At the same time, these collaborations help develop the next generation of mobility innovators – individuals who understand both the technical complexity and the human impact of modern transport systems.
These relationships are mutually reinforcing. Universities gain access to complex, real-world data sets, and operational contexts. Cubic gains insights from top researchers who specialize in anything from human-centered design to predictive analytics. Together we translate theory into outcomes, and academic ideas into tangible passenger benefits.
From Research to Real-World Results
The most powerful proof of partnership lies in the results. Cubic and its academic partners have worked on projects that have helped uncover new ways to understand and improve our transit systems.
Predictive Maintenance
Working with academic data scientists from the AIDA Lab at Imperial College, we have explored ways to diagnose which fare gate parts will be required during maintenance ahead of an engineer visit, effectively reducing equipment down-time and the number of site visits required by maintenance engineers.
Fare Evasion analysis
Collaborative studies with institutions have assisted Cubic in creating functional fare evasion analytic models. These models vary from using computer vision to detect fare evasion, anti-social behavior, or security threats, to analyzing passenger behaviors to identify ‘short ticketing’ hot spots.
Passenger Behavior Analysis
Through combining journey data, machine learning and behavioral insights, these collaborative projects have helped identify passenger travel patterns that inform policy and technology solutions. These research projects have guided scheduling and route optimization for transit services and have delved into commuter ‘nudging’ to drive ridership and improve environmental outcomes.
Accessibility and inclusion
Our academic partners specializing in human factors have assisted Cubic in testing user interfaces and equipment designs to ensure equitable access for all passengers. Qualitative and quantitative research has also been conducted with riders representing a wide range of geographies, ages, socioeconomic background, and mobility levels to try and understand their experiences with our transit systems and where pain points can be alleviated to ensure seamless travel.
Sensor fusion for safer stations
Alongside the University of San Diego, we’re exploring ways to make fare gates smarter and more responsive to safety needs. By utilizing advanced sensors and sensor fusion techniques, we aim to create intelligent systems that adapt in real-time to dynamic environments in public transit. To ensure privacy and safety go hand in hand, we’re leveraging machine learning and AI to build robust data safeguards while aiming to deliver practical solutions for public transit environments.
Advancing Intersection Safety through AI
Our collaboration with the University of Tennessee and the City of Knoxville is focused on transforming how intersections serve pedestrians, cyclists and transit users. By applying AI-driven insights to real-world traffic patterns, this research aims to reduce conflicts, improve signal responsiveness, and enhance safety for vulnerable road users. The outcomes will lay the foundation for smarter urban mobility systems that prioritize people, support transit efficiency, and create scalable models for cities worldwide.
Across all these examples, the common thread is transformation and continuous improvement. Our academic collaboration doesn’t just inform innovation; it accelerates it – grounding ideas in evidence and helping align technology with societal value.
The Ecosystem Approach to Innovation
At its core, Cubic’s approach to innovation is ecosystem driven. Rather than viewing research as a one-off project, we invest in long-term relationships that span customers, geographies, universities, and technology partners alike. This approach ensures that innovation remains a continuous process and not a series of isolated breakthroughs. It embeds curiosity, rigor, and empathy into our DNA.
The future of public transport depends on our ability to adapt. To anticipate how people will move, pay, and connect in the years ahead. Academic and customer collaboration are among the most powerful tools we have for staying ahead of that curve.
As the rate of technology advancement increases, and data, AI and urban infrastructure become ever more intertwined; partnerships between industry, academia and the public will only grow more vital. Together, they ensure that innovation remains ethical, inclusive, and focused on outcomes that matter - reliable journeys, sustainable operations, and equitable access for all.
Cubic will continue to champion this collaborative model – working with transit agencies, universities, and our riders to co-create the next generation of mobility solutions. Because innovation doesn’t start in isolation. It starts in collaboration.