Together, human experience and AI could make metropolis streets safer, scientists say

  • Scientists in Spain have used synthetic intelligence to determine widespread patterns in highway site visitors accidents.
  • They used machine studying and synthetic neural networks to investigate hours of video footage and hundreds of photos of life in Madrid and Barcelona.
  • The outcomes recommend most accidents happen on metropolis streets cluttered with options that distract drivers.
  • AI can be utilized to course of giant volumes of knowledge and map danger components, making it simpler for metropolis planners to handle them.
  • The absence of agreed worldwide governance for AI raises privateness, bias and moral considerations.

Artificial intelligence (AI) is being utilized in analysis that it’s hoped will assist cut back highway site visitors accidents (RTAs), which declare about 1.35 million lives yearly.

Scientists in Spain have utilized the expertise to determine widespread patterns in RTAs. These might assist information city planners in work to reduce collisions and make the world’s streets safer.

With densely populated urban areas forecast to proceed to draw individuals in search of work and higher residing circumstances lengthy into the longer term, that’s going to be an vital consideration. The World Health Organization (WHO) says greater than half of all deaths on the highway are amongst “vulnerable” highway customers — pedestrians, cyclists and motorcyclists.

Using AI to advertise safer streets

Researchers at Universitat Oberta de Catalunya (UOC), the world’s first on-line college, deployed AI to investigate hours of video footage and hundreds of pictures of life in Spain’s two largest cities.

Although pandemic lockdowns had been in pressure final 12 months, the capital, Madrid, suffered greater than 12,000 site visitors accidents, which triggered 31 fatalities. Barcelona’s 5,700 site visitors collisions resulted in 14 deaths.

The researchers mixed two points of AI — machine studying and synthetic neural networks — to seek out widespread patterns in city areas that undergo from excessive accident numbers. Machine studying adapts when it acknowledges patterns in information, whereas synthetic neural networks mimic the best way the mind is sensible of a number of layers of knowledge.

The want for human experience

The UOC analysis discovered that particular bodily options troubled drivers and that the extra cluttered the atmosphere, the more durable it was for them to pay attention. Street furnishings comparable to benches and public artwork, vibrant promoting near roads and parked automobiles had been unwelcome distractions, motorists stated.

“What appears clear is that the variety of distinct parts in a scene correlates with the variety of accidents which have taken place there,” Javier Borge, one of many examine’s lead researchers, stated of the findings.

The examine, which helps the United Nations’ Sustainable Development Goal 11, to make cities inclusive, protected, resilient and sustainable, was supported by Spain’s National Traffic Authority (DGT) and town councils of Madrid and Barcelona.

While AI supplies essential insights, the researchers believe city streets can only be made safer if the analyses are mixed with the experience of architects, engineers, transport authorities and metropolis planners.

“Artificial intelligence strikes us as a really highly effective software for locating out the place issues would possibly happen, however it’s not going to resolve them by itself,” Borge stated.

Sustainable Development Goals

The researchers say their examine helps Sustainable Development Goal 11 – to make cities inclusive, protected, resilient and sustainable.

Image: United Nations

AI fixing real-world issues

The UOC analysis is only one of many examples of how machine studying and AI are helping decision makers sort out advanced real-world issues.

In most cancers care, the expertise has been used to precisely display screen, determine and forecast the event of the illness. Scientists use AI algorithms to crunch giant quantities of information to disclose traits and share details about the potential impacts of local weather change.

And makes an attempt to stop world starvation have been energized by AI’s skill to deliver collectively sources of information that assist communities make knowledgeable predictions about disasters, comparable to crop failures or drought.

Governance and moral points

Despite AI’s undoubted problem-solving potential, there’s concern {that a} lack of coordinated worldwide governance over its utility might result in abuse of the expertise. Unethical use of private information, cybersecurity assaults and identification theft are among the many most urgent worries.

The World Economic Forum’s Global Technology Governance Report 2021 cautions that governments and companies must work collectively to deal with these points. It factors to areas of fine follow, such because the New Zealand authorities’s incorporation of privateness, human rights and ethics into AI algorithm design.

The subject will probably be mentioned additional at April’s digital World Economic Forum Global Technology Governance Summit, which hopes to encourage a cooperative public-private method to the alternatives and challenges of AI.


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