
Could emergency response systems save lives on gridlocked Irish roads?
It's a familiar scene: sirens blaring, lights flashing, but the emergency vehicle barely inches forward in traffic. Every second matters when an ambulance or fire truck is trying to navigate traffic. Yet even the fastest emergency vehicles often find themselves stuck in gridlock.
Conventional traffic management systems are reactive at best and often incapable of adapting quickly when an ambulance, fire engine, or police car needs to get through. The delays aren't just frustrating—they can be deadly. But what if city traffic could think for itself?
From RTÉ Radio 1 Liveline, listeners share stories of how traffic snarl-ups and bad drivers cause ambulance delays
We may be familiar with the Internet of Things, which includes vehicles, but the Internet of Vehicles takes the same principle of connecting items to the broader internet to allow them to exchange data and information. This network represents an ecosystem where every participating vehicle communicates with other vehicles and roadside units, such as sensors and communication towers that detect when an emergency vehicle is coming.
Within this framework, emerging technologies like connected autonomous vehicles, public key infrastructure for security and real-time vehicle-to-infrastructure communication could enable dynamic traffic responses when emergencies strike .
How would this system work?
When an emergency vehicle is on the move, its digital identity would be authenticated using public key infrastructure-based certificates, which operate like digital IDs for emergency vehicles to prevent other vehicles abusing the system. This ensures only verified emergency vehicle receive priority, protecting the system from spoofing or cyberattacks.
From RTÉ Radio 1's Today with Sean O'Rourke Show in 2019, reporter Brian O'Connell goes out on call with the Dublin Fire Brigade
Once verified, nearby roadside units instantly alert surrounding connected and autonomous vehicles to make way. But rather than just pulling over randomly, these vehicles respond in a coordinated way. They shift lanes, form platoons and create a clear, structured path for the emergency responder.
The beating heart of this system would be an algorithm that quickly identifies which vehicle should lead the pack. The selection isn't random and is based on three key factors:
(i) Proximity to the emergency vehicle
(ii) Communication reliability
(iii) Current lane alignment
The system would be able to decipher which vehicle would be best 'leader' for the platoon. The chosen vehicle would guide others, ensuring a seamless and safe formation that clears the road and maintains flow.
From RTÉ Radio 1's Today With Claire Byrne, the hugh cost of traffic congestion in our cities
This algorithm is what would allow for the wide range of considerations and manoeuvres: having received the signal from the emergency vehicles, other cars would calculate the best way to move out of its path based on far they are from other cars and which lane would be least disrupted.
Could such a system work with human drivers on the road?
Our research proposes an Enhanced Traffic Management System powered by data, connectivity, and collaboration. While this current model focuses on connected and autonomous vehicles, future iterations of this system will support hybrid environments where human-driven cars share space with connected vehicles. Roadside infrastructure will play a larger coordinating role in these mixed-traffic scenarios, acting as traffic conductors to guide all vehicles and not just the smart ones.
Security and scalability remain paramount. Embedding public key infrastructure certificates into ambulances and fire engines ensures that only authorised entities get traffic priority. The system performs robustly even with multiple emergency vehicles navigating through four and six lane setups.
From RTÉ News, National Ambulance Service figures show average response time has increased across the country
What we found in our study
We built high-fidelity simulations, integrated with 5G-enabled V2X communication models, to test our approach. We're not talking about virtual toy cars here: we recreated realistic traffic scenarios, from steady morning commutes to high-density rush hour chaos.
The results were promising. In heavy traffic conditions (up to 100 vehicles per kilometre), the system increased the mean speed of traffic by nearly 28% compared to traditional Controllable Path Planning systems and by over 16% compared to existing Emergency Vehicle Priority systems Fuel usage dropped significantly as vehicles avoided unnecessary braking and idling.
Most notably, travel times stayed stable, even during peak congestion. While traditional systems showed erratic delays, our system maintained consistency, thanks to its real-time adaptability. With connected and autonomous vehicles adoption accelerating and smart city infrastructure gaining momentum, systems like this could become vital tools in the urban planner's toolkit.
From reducing emergency response times to easing congestion and eliminating emissions, our system shows how intelligent machines can work together to protect lives in the moments when every second counts.
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