How big data could transform the roads of the future

While big data is fast becoming an integral tool in the business world, its potential impact is far more wide-reaching and has the capacity to impact the day-to-day life of people all over the world.

For example, big data is playing a key role in the development of so-called smart cities, where almost every aspect of life, from waste disposal to law enforcement, will be managed by integrated technology solutions that are dependent on big data to function.

Key to the development of true smart cities will be the evolution of more efficient transport systems, which make getting from A to B quicker and easier. Big data will be vital to making this future a reality and great strides have already been made.

Intelligent traffic

Traffic congestion is one of the biggest problems in cities across the world. Time-consuming and pollution-generating, it has a negative impact on both the environment and city residents’ quality of life. There is an economic effect too, with a study from the INRIX and the Centre for Economics and Business Research forecasting congestion will cost the UK economy £307 billion between 2013 and 2030.

The growth of the internet of things and machine-to-machine technology presents solutions to these problems. According to Statista, more than one in ten (12 per cent) of cars on the road now possess connected technology and this figure is expected to reach 22 per cent by 2020. With such technology in place, it is possible for vehicles to share and receive real-time data on road and traffic conditions. This can then be processed to provide information that can be used to manage traffic more effectively.

Theoretically, the exchange of data will make it possible to monitor the number of cars in a certain area and divert approaching motorists towards a different route when capacity is reached. Trails to this effect have already taken place in the US and China.

However, progress is still required before this vision of truly smart traffic can be achieved. Hussein Dia, associate professor at Swinburne University of Technology, Melbourne, recently discussed the issue with Raconteur.

“While decision-makers and city leaders are recognising the role of data analytics in ‘sweating of assets’ and providing innovative solutions to meet demand, deployment at a global scale is still in its infancy,” he stated.

“As the amount of data about current and future travel demands increases in the connected world, so the possibility of better analytics increases. In order to have real benefit, though, predictive analytics for transport as a whole is required,” Prof Dia added.

Self-driving cars

Should data-driven traffic management become a reality, the next step in the development of truly smart cities will be autonomous vehicles. Progress has already been made in this area, with Google having covered close to 2.5 million miles in test drives through its self-driving car project. Tesla, meanwhile, has adopted more of a piecemeal approach and has already released the ‘autopilot’ software update, which allows its vehicles to drive, change lanes and adjust speed autonomously. However, the car must already be moving at a consistent speed and have maps data of the surrounding area before these features can be engaged.

If genuinely autonomous cars are to become a reality, big data will be crucial, providing the real-time information these vehicles will require to navigate the roads in the safest and most efficient manner possible.

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