Climate change. Mobility. Artificial Intelligence

How can AI optimize urban mobilities to mitigate and adapt to climate change impacts?

P. Singh -

8 July 2023

As a keynote speaker at the Greenpeace-University of Hamburg 'Climathon 2023', Platform Anthropocene Inc. (#planthro) discussed synergies between climate change, urban mobility and #artificial intelligence (AI) for a #sustainable future. The impacts of climate change, exacerbated by human activities, are not local, linear and gradual but widespread, complex and fast-paced. In this context, AI opens up new possibilities for urban mobilities to mitigate and adapt to climate change at an accelerated pace, through improved innovation, regulation and monitoring.

The transportation sector accounts for about a quarter of energy-related carbon dioxide emissions globally, and could benefit from existing as well as #near-future AI applications. Optimization of the transportation infrastructure relies on improving the efficiency of vehicles, fuel and routes used for the movement of people and goods. A robust intelligent transportation system (ITS) has the potential to seamlessly exchange real-time data between automobiles, passengers, and the road conditions. In urban settings, AI methods such as #machine learning (ML), embedded in ITS, can reduce mobility response time by executing:

  • Real-time data analysis,
  • Predictive modelling and
  • Decision making support

An efficient ITS aids in improving access and viability of alternative fuels, electrification infrastructure, and low-carbon multi-modal mobility options that include rails and public buses. FAIRTIQ app used in many parts of Europe makes it seamless for passengers to check-in and check-out a bus or a train using their smartphones. In this way, AI protocols not only reduce greenhouse gas emissions but also enhance safety measures while promoting sustainable behaviour among passengers.

For instance @Uber, a global mobility platform transporting passengers and freight, harnessed the power of AI tools in India to implement smart options for #urban mobility. This includes introducing

  • A multi modal mobility system in Gurugram,  
  • Leveraging @WhatsApp chatbot for booking a taxi,  
  • Optimizing routes and predicting short-term user demand during peak hours
While AI tools can accelerate global efforts to use less natural resources and optimize the energy efficiency of the existing transportation infrastructure, they face the twin challenge of transparency and protection in data usage. Indeed, AI protocols used in ITS rely heavily on the collection and organization of diverse, multi-dimensional and constantly changing data points scattered across offline and online modes. In this context, it becomes vital to design standards and guidelines that democratize data usage to make more accurate predictions about traffic and climate change, while ensuring the protection of data privacy from malicious use. This means leveraging evidence-based research to inform policy and citizens to strike a sustainable balance between AI ethics, human values and environmental costs.

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