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AI in smart transportation: The trend continues

AI in smart transportation: The trend continues
Smart transportation has become a major trend. More and more, AI is used to enable smart transportation. This article takes a look at AI in transportation applications, in 2023 and beyond.
Smart transportation has become a major trend. More and more, AI is used to enable smart transportation. This article takes a look at AI in transportation applications, in 2023 and beyond.
Needless to say, smart transportation is a term that we’re hearing more and more of. Smart transportation encompasses a range of applications, from adaptive traffic signal control to electronic collection to advanced high traffic management. All this aims to help city authorities as they deal with a range of complex, sophisticated transportation issues in the wake of urbanization and increased car ownership.

How AI plays a key role

Smart transportation is all about data. Indeed, with a great wealth of data generated from IoT sensors, for example IP cameras, radar, onboard units and other types of sensors, how to process them has becomes key. This is where AI comes in. Analytics that are trained to detect and recognize certain activities/behavior – for example illegal parking and making illegal turns – can help city operators abundantly as they enforce law and make related planning.
Below we look at some examples of AI in smart transportation, based on a blogpost by the PTV Group.

Traffic management

Traffic management can benefit tremendously from AI. A major objective of traffic management is to reduce or eliminate congestion. In this regard, AI with the help of IP cameras can detect foreign objects on the road obstructing traffic, or recognize the volume and types of vehicles passing through certain routes or intersections. This can help alleviate congestion and make future planning more effective.
Meanwhile, AI can also optimize adaptive traffic signal control, whereby each signal cycle is automatically adjusted based on the traffic situation at the time. Here in Taipei for example, adaptive traffic signal control is already deployed at certain intersections where IP cameras process traffic video on the edge. The resulting metadata is then transmitted to the backend, which controls the signal. This has helped reduce congestion effectively.
“AI is being used in traffic management systems to optimize traffic flow and reduce congestion. By analyzing real-time traffic data, AI algorithms can adjust traffic signals and reroute vehicles to less congested roads, reducing travel time and fuel consumption,” the PTV Group post said. “Intelligent traffic management is already implemented successfully. Cities like Taichung, Vienna, York, or Rome already rely on PTV’s real-time solution which combines machine learning techniques with dynamic traffic modeling.”

Shared mobility

For vehicles that are shared, for example buses, they can benefit from AI as well. Taiwan for example already has bus-on-demand, whereby each bus station is equipped with an AI camera monitoring the number of people waiting. Once the number of passengers crosses a threshold, the data will be transmitted to the onboard unit of a bus, which will then be dispatched to the station to pick up the passengers. The energy and cost saved in the process can be huge.
“For mobility-on-demand services, AI can optimize the deployment of shared vehicle fleets and improve the user experience of passengers. By analyzing data on passenger demand and traffic conditions, AI algorithms can predict passenger demand up to one hour ahead. Idle vehicles are then sent to future demand hotspots, just in time to pick up passengers. This reduces waiting times and detours,” the post said.


AI can also work wonders for logistics operators/drivers. AI-enabled onboard IP cameras can monitor not only the road but also fatigue/suspicious behavior by the driver. Analytics onboard or in the cloud can also help plan the most effective route, based on various data.
“By analyzing data on shipping routes, traffic patterns, and weather conditions, AI algorithms can optimize delivery routes, reducing fuel consumption and emissions,” the post said, adding:
“Will logistics companies soon replace their human dispatchers for AI-powered transport planning software? The answer is clearly No. Routing and scheduling software uses algorithms to calculate routes. But not all variables, restrictions and conditions can be mapped by algorithms.”

Indeed, AI can help address various transportation issues facing cities. Already, AI-based smart transportation is deployed in metropolises across the world. In the future, we can expect to see only more of it, as cities strive to make themselves smarter, more efficient and more sustainable.

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