How big data will transform the ways people travel

How big data will transform the ways people travel

Getting from A to B has been one of humanity’s great preoccupations throughout history. New methods of transport are constantly being developed to get people to their destinations faster, from horse-drawn carriages and boats, to cars and planes. But still these innovations never seem fast enough.

While teleporters are still far off, transportation is facing something of a revolution. Intelligent systems are being built that can recognise and respond to traffic flows without human intervention, which have the potential to significantly improve our transportation experience. And the key to this revolution is big data.

Starting with even the humble traffic light, big data has the potential to make journeys more efficient. This essential infrastructure not only keeps us safe, but also ensures that the traffic flow is being directed in an orderly fashion.

However, as any driver has experienced, people aren’t quite so orderly. Many traffic light systems are programmed in isolation, based on an engineer’s expectation of what constitutes ‘normal’ traffic, so a big sporting event or concert can massively disrupt traffic flow, leaving fans inching along in traffic.

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Such headaches could be eradicated by incorporating big data into the traffic light system. Monitoring the traffic flow in real time could allow for adjustments to be made based on actual events.

For instance, standard timings could be used in light traffic, while in heavier traffic the system could be manipulated to keen the green light on for longer in the congested direction.

This sort of synchronised traffic light system is already used in Los Angeles to reduce congestion and improve traffic flow. Whereas behind the scenes in Boston, city officials are working to combine street camera footage with Waze and Uber’s data sources to ease traffic congestion.

The automotive industry is rapidly changing, with 90% of cars predicted to be connected to the internet in 2020, compared to just 10% in 2012.

This phenomenal number of cars will provide a stream of data on both vehicle and engine behaviour. This data is then sent on to mechanics directly as part of the auto manufacturer’s preventative maintenance program.

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