From autonomous vehicles to smart highways, AI in transportation and logistics is becoming an essential factor to consider.
Smart cities and smart highways are developing wider use of AI in transportation and infrastructure. Along with collating traffic data to reduce congestion and improve the scheduling of public transport, AI applications have been put into place in some cities which enable users to share vehicles; with ride-sharing lanes designated accordingly.
While fully autonomous passenger cars and, to a lesser degree, freight trucks are still in their infancy as a functioning technology, an increasing number of new vehicles are being produced which include elements of AI in transportation. Sensors can let the driver know if they are approaching an obstacle, course correct to keep a moving car in its lane and even stop the car entirely if it appears to be approaching a crash. Prototypes have been built of autonomous larger vehicles such as snow ploughs and refuse collection vehicles; and Sweden and Germany have piloted driverless buses.
The Autonomous Rail Rapid Transit, launched in Zhuzhou, China in 2017, is a train system that runs without rails; operating instead on a virtual painted track which the train’s computer system detects and follows. Meanwhile fully autonomous trains, using machine learning and AI in transportation of freight and passengers, have been trialled in a number of countries.
AI in transportation is not just limited to land: Rolls-Royce expects to launch remote controlled ships, currently in development, by 2020. The ships’ crews will be entirely land-based, meaning a reduced risk of harm to employees and more room on the vessels for freight. The primary challenge faced by developers, as identified in Rolls-Royce’s white paper outlining their plans, is the risk of the software being hacked and ships diverted.
The European Commission’s Urban Air Mobility initiative aims to introduce unmanned air vehicles, or drones, as a solution to the provision of civic services, operating in the as yet untapped third dimension to deliver goods and – eventually, theoretically – passengers. AI in transportation by drone has been mooted as a solution to potential human error. Dr Vassilis Agouridas, leader of the Urban Air Mobility initiative, said: “In all modes of transport, including aviation which is the safest mode of transport, there is advanced work on further boosting safety levels by removing the human factor errors by leveraging new technologies, such as artificial intelligence, machine learning and advanced sensors. By further automating systems, and eventually making them autonomous, we can repeatedly do things correctly, thus eliminating the human factor error.”
Education in AI in transportation and beyond
In 2018 Finland introduced a free educational scheme aimed at providing at least one per cent of the country’s 5.5 million residents with education and training in the basics of AI. The “AI challenge”, supported by universities and businesses hoping to boost their employees’ skills, began as a free online course in 2017 and gained traction as its creators worked to promote AI training to a wider audience. Finland, which intends to become a world leader in practical applications of AI, plans to partner with its neighbours Estonia and Sweden to run test trials on the use of AI in transportation, cross-border shipping and infrastructure.