Are algorithms the future of smart urban transport?

Oscar Huerta Melchor, PhD

Project Manager, Urban Development and Governance OECD Centre for Entrepreneurship, SMEs, Regions and Cities

Artificial intelligence (AI) tools will transform the way we move. AI can make urban mobility systems more sustainable, resilient and human-centric. What can we expect from smart mobility?

Artificial intelligence tools can underpin a revolution in city mobility, providing opportunities for the smarter management of urban traffic and public transport, as well as for autonomous ride-sharing to reduce vehicle numbers. These applications can reduce CO₂ emissions, traffic jams, road accidents, travel costs and travel. It can also improve access to public spaces, jobs, goods and services.

Smart mobility projects across cities

Although AI’s integration with smart city projects is still in the early stages, we can already see promising examples. Phoenix (USA) has introduced the first commercial driverless taxi service to disincentivise car ownership. Singapore and Los Angeles (USA) use AI to reduce traffic congestion and emissions.

Dublin is piloting digital twin projects to allow for citizens’ feedback on areas, such as urban planning, including transport infrastructure. While São Paulo, Brazil uses AI and data analytics to predict air pollution and enable local authorities to take preventative steps and manage traffic flows; Chicago (USA) used them to optimise the management of its bike-sharing programme to support a tripling in its fleet of bikes.

AI and machine learning do not necessarily guarantee better mobility outcomes for all groups. Efforts need to be made to expand the accessibility of new tools.

Ensuring accessibility to smart solutions

However, AI and machine learning do not necessarily guarantee better mobility outcomes for all groups. Efforts need to be made to expand the accessibility of new tools. For example, in the Brussels-Capital Region (Belgium), the main users of car-sharing services tend to be from high-income groups, young (26–39 years old), university graduates (69% of users) and male (77% of users).

Regulations for safety and inclusivity

Greater efforts are also needed to generate robust evidence on the safety record of smart mobility projects to build trust. Regulations need to be adapted to enable the safe use of new technologies and services. Furthermore, cities need to strengthen their data governance capacity and capability.

Ultimately, local political leadership will determine whether and how the opportunities offered by AI are exploited. To make the most of these opportunities, cities need to strengthen digital skills and governance. They must also hard-wire alignment with their social and environmental objectives if they are to deliver on their potential to make our cities smarter and more inclusive.