ASU Researchers Drive Global AI Innovation for Safer Roads
Every time we step into a vehicle, we take a calculated risk. Traffic collisions, tragically, remain the leading cause of death for children and young adults across the globe. But as the era of autonomous vehicles gains momentum, a fresh wave of innovation is shifting gears in traffic safety. And at the heart of this global drive is Arizona State University.
Within the School of Computing and Augmented Intelligence at ASU, Associate Professor Yezhou “YZ” Yang is leading a project that’s quietly turning heads and saving lives. His focus? Developing computer vision systems that make streets smarter, without compromising personal privacy.
Computer vision, a specialised branch of AI, enables machines to interpret their surroundings using cameras, sensors, and software. It’s the lifeblood of many emerging technologies, from self-driving cars to industrial robotics. But now, it’s making a decisive entrance into traffic safety, thanks to Yang and his team.
Data Without the Drama: Meet eTraM
The crown jewel of Yang’s work is eTraM — short for event-based Traffic Monitoring. Unlike traditional CCTV systems, eTraM doesn’t store images or video. Instead, it captures up to 10 hours of high-resolution data, detailing traffic patterns, lighting conditions, and environmental factors like weather — all while respecting privacy.
Yang puts it plainly: “The cities of the future must address concerns about personal privacy and security. eTraM records data and not images, providing information that can help train AI models but doesn’t use anyone’s image without their knowledge.”
This ethical shift could be a game-changer. Real-time, anonymised insights make it easier to identify high-risk zones, especially during late-night hours when visibility drops and the chance of collisions rises.
The system is already in use around ASU’s Tempe campus, helping to log near misses and dangerous junctions. But that’s just the start. The next step is to supercharge eTraM with machine learning models that don’t just record traffic events — they anticipate them.
Building the Brain Behind Safer Intersections
With help from ASU Engineering Assistant Teaching Professor Bharatesh Chakravarthi, Yang’s team is training AI to detect and learn from patterns in the eTraM data. The result? Tools that help city planners design intersections that reduce confusion and improve visibility, re-time traffic signals, and determine optimal signage placement.
By analysing micro-movements and traffic flows, these models can simulate how changes on the ground affect the overall ecosystem. This proactive design approach can help shift road planning from reactive to preventative.
And it’s not just for academic purposes. These technologies have real-world implications for municipalities, road agencies, and even private developers who want to embed safety-first principles into infrastructure projects.
From Tempe to the World: Workshops Without Borders
Ensuring these technologies reach the right hands is a critical part of the journey. That’s where Professor Kamil Kaloush comes in. A pavement engineering expert at ASU’s School of Sustainable Engineering and the Built Environment, Kaloush also serves as Chairman of the Board for the International Road Federation (IRF Global).
He’s not just talking the talk — he’s been driving change in over 70 countries, building bridges between researchers and road safety stakeholders. “ASU is an IRF Global university member, and we support the organisation with various requests for training and benchmarking,” he explains. “Our mission is to advance the transfer of knowledge among road and transportation professionals and experts, ensuring the development of safe and sustainable infrastructure.”
To that end, ASU researchers, including Yang, Kaloush, and computer science Assistant Professor Hua Wei, teamed up to develop a workshop: AI and Big Data Applications for Future Traffic and Incident Management.
UAE Takes the Lead in Piloting Innovation
The team gave their new programme its first outing in the United Arab Emirates, during a two-day workshop hosted by Abu Dhabi Mobility in partnership with IRF Global. Organised by IRF’s Middle East and North Africa Director, Aliaksandr Smirnou, the event brought together a melting pot of transport professionals, policymakers, and tech innovators.
Fulton Schools adjunct faculty member Mohammad Farhadi Bajestani led in-person sessions, while others joined remotely. The workshop focused on using AI and big data to:
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Reduce congestion
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Boost emergency response times
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Enable autonomous vehicle integration
Participants didn’t just sit through presentations. They got their hands dirty, experimenting with AI modelling tools and datasets, learning how to build customised systems tailored to their specific environments. This hands-on approach ensured that each delegate left with more than just ideas — they gained applicable skills.
Spreading the Message Closer to Home
With one successful event under their belt, the ASU team and IRF Global are already planning to replicate the workshop elsewhere. Kaloush confirms that discussions are ongoing with the city of Phoenix to roll out a similar programme. That local adaptation could serve as a vital testbed for broader US implementation.
The long-standing relationship between ASU and IRF Global is proving to be a sturdy backbone for these ambitions. With cities increasingly looking to smart solutions for safer infrastructure, the appetite for practical AI education is only growing.
Racing Toward a Safer Tomorrow
For Yang, the road ahead is clear — and it’s paved with opportunity. “Now it’s back to work. No pit stops!” he laughs, hinting at the relentless pace of innovation that his team has embraced.
It’s an exciting time. From anonymous traffic data to international training bootcamps, Arizona State University isn’t just pushing the envelope — it’s redesigning it entirely.
Thanks to these initiatives, the idea of a world where traffic fatalities fall and roads become intuitively safer no longer seems out of reach. It’s becoming a reality, one data point at a time.
Shaping the Future, One Smart Road at a Time
In a world overwhelmed by information, clarity and purpose are rare commodities. ASU’s work on traffic safety doesn’t just check the box on innovation — it reshapes what’s possible for modern infrastructure.
As technology races forward, the challenge will be ensuring that progress remains people-centred. Fortunately, with privacy-first systems like eTraM, global training workshops, and forward-thinking researchers at the helm, that future is well on the way.
