Simple Explanation (ELI5)

Think of cities as playgrounds where walking and cycling are like choosing to walk instead of running fast: both get you places, but walking and biking are healthier and cut pollution.

Key Advantages & Current Limits

🟢 Pros: Migliorano la salute pubblica, riducono le emissioni di CO2 e rendono le città più vivibili e meno congestionate. 🔴 Cons: Esistono ancora barriere come l'assenza di infrastrutture dedicate, la scarsa applicazione delle norme di sicurezza e lo stigma sociale.

Future Outlook & Takeaways

In 3-5 anni, l'intelligenza artificiale analizzerà i flussi di mobilità per ottimizzare le reti ciclabili e pedonali, mentre le politiche includeranno prospettive di genere e infrastrutture resilienti al clima. L'integrazione con i trasporti pubblici e l'uso di dati digitali per monitorare l'uso delle infrastrutture renderanno le città ancora più sicure e accessibili a tutti.

Why Walking and Cycling Are Transforming Our Cities

Article

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Walking and cycling are not just sports: they are real modes of transport that cut emissions and boost health. A review of 56 studies, published in *Future Transportation*, examined what drives people to choose these trips. Using the COM‑B model (Capability, Opportunity, Motivation‑Behaviour), researchers identified four main barriers: lack of dedicated infrastructure, weak enforcement of safety rules, accident‑related fears, and social stigma. To tackle these, experts suggest concrete actions: integrated bike networks, financial incentives, urban planning that puts pedestrians and cyclists first, and behaviour‑change programs. After the pandemic, many cities created new pedestrian zones and bike lanes, a golden chance to make them permanent. Digital tools can also help coordinate routes and monitor infrastructure use. Looking ahead, artificial intelligence could analyse mobility flows, support climate‑resilient infrastructure, and bring gender perspectives into transport policies. Investing in safe routes and linking them to public transit is the key to livable, less congested, and more equitable cities for everyone.

Bonus

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The COM‑B model, developed by Michie et al. (2011), is a theoretical framework for understanding how capability (knowledge, skills), opportunity (environmental, social) and motivation (emotions, beliefs) interact to produce behavior. In urban contexts, capability includes knowledge of traffic rules and the technical skill to ride a bike. Opportunity is heavily shaped by the presence of protected infrastructure: segregated bike lanes, safe pedestrian crossings, and low‑traffic zones. Motivation can stem from perceived benefits (health, cost savings) or psychological factors like the identity of an "active citizen." Recent studies show that financial incentives, such as subsidies for e‑bikes, boost intrinsic motivation, but only when paired with concrete opportunities. Mobility data analysis via AI, for example{using convolutional neural networks}, enables prediction of congestion points\u {...}

[Truncated due to length constraints]... (Note: The full English bonus would mirror the Italian version, covering COM‑B components, AI applications, gender‑specific safety concerns, and traffic‑calming policies.)