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Land Transport Authority Of Singapore
Artificial Intelligence And Urban Mobility
Chris Leck
Today, AI is helping to improve urban mobility in many ways. Ride-hailing/sharing platforms such as Uber and Grab use AI to match riders and drivers and plot the most optimal route to be taken, while journey planner apps like Moovit and City Mapper Tap on AI to integrate and suggest mobility options to users. Intelligent traffic light algorithms also help to keep traffic on our roads flowing through optimising traffic light timings. In these instances, AI is helping to make journeys smoother and more effortless.
Tapping on big data, AI can also make our transport systems more reliable and efficient. To enable predictive maintenance for transport assets like train systems and buses, AI algorithms can be applied to data from sensors to conduct trend analysis and detect potential faults before they even occur.
AI can also be applied to enhance the situational awareness of authorities and transport operators and provide them with decision support tools. In Singapore, for example, the Land Transport Authority has developed a fusion analytics for public transport (FASTER) system that can ingest and analyse data from various sources such as CCTV, wifi/ telco, ticketing and traffic data to help us visualise commuting patterns to improve transport planning, trigger early alerts of any incidents and model the impact of transport delays.
Perhaps the most widely known use case for AI in mobility is that of autonomous vehicles (AVs), not least due to the help of pop culture. Remember the autonomous cars in I, Robot or Minority Report? Today, while AVs are still some years away from widespread deployment, many cities are testing them on public roads, from passenger cars to trucks to even electric scooters. Here in Singapore, AVs have been trialled on our public roads since 2015 by companies such as Aptiv and ST Engineering and local universities like the National University of Singapore and Nanyang Technological University. We are now working towards town-scale pilot deployments of autonomous buses and shuttles in three of our towns by the early 2020s.
When mature, AV technology can positively transform the mobility landscape, opening up new and more convenient mobility options for commuters, allowing mobility services to be delivered more efficiently, and reducing the number of traffic accidents due to human error. We may soon even see autonomous mobility taking to the skies, with companies like Volocopter and Airbus conducting trials of autonomous aerial vehicles.
However, even as AI brings about transformational change to mobility, we have to be mindful that it can potentially pose some challenges. Much has been made, for example, of the disruption that AI would bring for some jobs. But AI will also lead to the creation of new and potentially better jobs. What is important is that workers that are displaced have the opportunities to be reskilled to take on new jobs that become available. Yet another example is how existing regulatory and liability frameworks may struggle to deal with the implications of AI. Here, governments will have to ensure that these frameworks are regularly updated to safeguard the public interest, while still encouraging innovation.
Perhaps the most widely known use case for AI in mobility is that of autonomous vehicles (AVs), not least due to the help of pop culture. Remember the autonomous cars in I, Robot or Minority Report? Today, while AVs are still some years away from widespread deployment, many cities are testing them on public roads, from passenger cars to trucks to even electric scooters. Here in Singapore, AVs have been trialled on our public roads since 2015 by companies such as Aptiv and ST Engineering and local universities like the National University of Singapore and Nanyang Technological University. We are now working towards town-scale pilot deployments of autonomous buses and shuttles in three of our towns by the early 2020s.
When mature, AV technology can positively transform the mobility landscape, opening up new and more convenient mobility options for commuters, allowing mobility services to be delivered more efficiently, and reducing the number of traffic accidents due to human error. We may soon even see autonomous mobility taking to the skies, with companies like Volocopter and Airbus conducting trials of autonomous aerial vehicles.
However, even as AI brings about transformational change to mobility, we have to be mindful that it can potentially pose some challenges. Much has been made, for example, of the disruption that AI would bring for some jobs. But AI will also lead to the creation of new and potentially better jobs. What is important is that workers that are displaced have the opportunities to be reskilled to take on new jobs that become available. Yet another example is how existing regulatory and liability frameworks may struggle to deal with the implications of AI. Here, governments will have to ensure that these frameworks are regularly updated to safeguard the public interest, while still encouraging innovation.
The articles from these contributors are based on their personal expertise and viewpoints, and do not necessarily reflect the opinions of their employers or affiliated organizations.
