AI-powered smart intersections could revolutionize urban safety and sustainability

Assessing the impact of smart intersections demands precise, data-driven metrics that capture their influence on urban traffic systems. The researchers pinpoint key performance indicators like average vehicle delays, queue lengths, and total travel times as essential for gauging traffic efficiency. Safety is measured through crash rates, conflict points, and near-miss incidents, while environmental benefits are tracked via reductions in vehicle emissions and fuel consumption.

Researchers at the University of Trento have delivered a groundbreaking analysis that could reshape urban transportation, spotlighting smart intersections as a cornerstone for safer, more sustainable cities. The study harnesses cutting-edge technologies like artificial intelligence and Vehicle-to-Everything (V2X) communication to propose a transformative approach to traffic management, aiming to slash accident rates and boost efficiency worldwide.

The study, titled "Smart Intersections and Connected Autonomous Vehicles for Sustainable Smart Cities: A Brief Review," was published in Sustainability. Authored by Masoud Khanmohamadi and Marco Guerrieri from the Department of Civil, Environmental and Mechanical Engineering, it consolidates recent advancements in smart intersection technologies. With Italy reporting 3,039 traffic deaths in 2023 and intersections linked to 39% of U.S. urban road fatalities between 2010 and 2019, the research underscores an urgent need for innovation. It dives into real-world applications and emerging tools, offering a roadmap for cities to enhance mobility while tackling environmental and equity challenges.

What are the most effective approaches to evaluating smart intersection performance?

Assessing the impact of smart intersections demands precise, data-driven metrics that capture their influence on urban traffic systems. The researchers pinpoint key performance indicators like average vehicle delays, queue lengths, and total travel times as essential for gauging traffic efficiency. Safety is measured through crash rates, conflict points, and near-miss incidents, while environmental benefits are tracked via reductions in vehicle emissions and fuel consumption. User satisfaction surveys provide a human perspective, revealing how commuters perceive accessibility and usability, ensuring these systems align with broader urban goals.

Real-world deployments validate these metrics. London’s SCOOT system has cut intersection delays with adaptive signal timing, while Toronto’s AI-driven intersections have shrunk peak-hour queues. Amsterdam’s cooperative vehicle infrastructure has lifted travel efficiency, and Pyeongtaek, South Korea, leveraging edge AI, achieved a 25% drop in congestion and a 30% rise in pedestrian safety. Barcelona’s Superblock model, prioritizing pedestrian zones, has minimized vehicle-pedestrian conflicts. These examples highlight the tangible gains smart intersections can deliver, though success hinges on local adaptation.

The study also details advanced evaluation methods. Optimization models, including linear and dynamic programming, fine-tune traffic signal phasing to minimize delays. Traffic simulation models, microscopic, mesoscopic, and macroscopic, test configurations virtually, while machine learning predicts flow patterns in real-time. Hybrid approaches blend quantitative data with qualitative insights, such as driver behavior studies, to refine accuracy. Emerging tools like reinforcement learning and digital twins further enhance performance analysis, offering cities a robust toolkit to measure and optimize smart intersection effectiveness.

What challenges and opportunities arise in integrating smart intersections into smart cities?

Integrating smart intersections into smart city frameworks presents a mix of promising opportunities and formidable hurdles. These systems streamline traffic flow for vehicles, pedestrians, and cyclists, reducing bottlenecks through adaptive signal systems that respond to real-time demand. They support multi-modal transport, cars, buses, trams, and micro-mobility options like e-scooters, enhancing urban mobility. By prioritizing public transit and emergency vehicles, they cut delays and boost reliability, while real-time data sharing with Mobility-as-a-Service platforms optimizes ride-sharing routes, slashing costs and emissions.

Yet, challenges loom large. Interoperability remains a sticking point, as smart intersections must sync seamlessly with existing infrastructure and city-wide systems, a task complicated by diverse technologies. Cybersecurity risks escalate with connectivity; without robust encryption and intrusion detection, these intersections are vulnerable to attacks that could disrupt traffic or compromise data. Stakeholder collaboration is another hurdle, governments, tech firms, and communities must align to ensure deployments meet public needs, a process often slowed by differing priorities. Urban planning adds complexity, with compact designs favoring integration while sprawling, car-centric suburbs resist efficient scaling.

Opportunities shine through despite these obstacles. Smart intersections promise cleaner air and safer streets by optimizing traffic to reduce pollution and crashes. They enhance equity by extending crossing times for vulnerable groups and prioritizing transit, improving access for all. Case studies like Amsterdam’s Shockwave system or London’s FUSION, which improved travel reliability by 15%, demonstrate their potential. The C-Roads Platform across Europe further exemplifies cross-border cooperation, harmonizing intelligent transport systems to amplify these benefits, setting a precedent for scalable urban integration.

What's next?

The study charts a forward-looking agenda for smart intersection research, emphasizing technologies that promise resilience and inclusivity. AI-driven adaptive traffic control tops the list, with reinforcement learning poised to dynamically adjust signals for peak performance. Digital twins, virtual models of intersections, offer a testing ground for strategies without real-world risks, accelerating innovation. Next-generation connectivity, via 5G and 6G networks, could slash latency, enabling swift interactions between vehicles and infrastructure, a boon for autonomous driving.

Sustainability drives another research focus: integrating renewable energy systems, like solar-powered roads, and smart pavements that self-monitor and heal could extend infrastructure life and cut environmental impact. Cybersecurity demands urgent attention, lightweight blockchain models and smart contracts could secure data, though latency and energy costs pose hurdles. Equity and accessibility also need exploration, ensuring smart intersections serve diverse populations, from elderly pedestrians to cyclists, through tailored design and policy.

The researchers stress adaptive governance and transparent AI decision-making as critical areas, urging collaboration to navigate regulatory and public trust issues.