Brief

Smart Cities can prepare for future advances in transportation automation and connectivity by investing in and integrating market-ready artificial intelligence solutions, write transportation experts Pierluigi Coppola and Federico Cheli. Cities must also prioritize inclusion by reimagining mobility systems and investing in capacity-building and training,

 

Insignt

Artificial intelligence (AI) applications in the transport sector are stimulating innovations for better and more targeted use of vehicles and infrastructure. This could optimise network performances, support the monitoring and management of traffic, and create the base for solutions that pave the way to future mobility, particularly in cities.

Infrastructure management and vehicle design are evolving thanks to the opportunities offered by the widespread use of devices, such as smartphones and in-vehicle localisation sensors, for processing, gathering and exchanging information among users and service providers, as well as for monitoring and detecting the performance of vehicles and behaviour of people.

Altogether these create a huge amount of data (big data), which is the primary source for using AI in transport, allowing computers to perform activities for humans, such as driving.

Levels of Automation

The most advanced and revolutionary AI application in transport today is the automation of vehicles. The classification most used to describe the degree of automation is defined by standards from the International Society of Automotive Engineers (SAE). This provides six levels of automation (including Level 0, which means there is no automation), identified according to who (i.e. human driver or system) performs the operation and at what time.

Today’s cars are generally equipped with SAE level 1 and 2 features, commonly referred to as Advanced Driver Assistance Systems (ADAS), such as park assist, cruise control, adaptive front lights and lane keeping assist (see figure 1). These devices support drivers in terms of providing aid, warning and assistance, rather than replacing them in driving activities (full automation).

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