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Moving towards the Internet of Transportation

The future of transport that we’ve been promised for decades is closer than we think, says John Frazer, CCO at DAV, a blockchain-based transportation platform.

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The Internet of Things (IoT) has promised to revolutionise every aspect of life, and the transport sector is proving to be no exception. The last couple of years alone have delivered an onslaught of apps that hail cabs, know when the next bus is coming, helps us plan train trips, and advise us on routes to avoid traffic.

 

On an infrastructural level, traffic lights, cameras and data sensors all form part of the IoT landscape. This so-called ’Internet of Transportation’ is ensuring that the roads and railways in major cities are capable of meeting demand.

 

Smartening up city transportation

It’s one thing to hear optimistic predictions from car-makers and entrepreneurs, but it’s another matter to see concrete steps toward autonomous transportation taken by cautious municipal planners.

 

Nowhere has the real-world implementation of smart transport been more prevalent in the UK than in Exeter.

 

The Exeter Engaged Smart Transport project is a collaboration with Exeter City Council and Devon County Council. It uses real-time data from traffic and weather sensors, combining that with eyewitness and behavioural information to reveal where there is congestion, work out why it is occurring and take action to solve the problems.

 

The Exeter Engaged Smart Transport project is a collaboration with Exeter City Council and Devon County Council. It uses real-time data from traffic and weather sensors, combining that with eyewitness and behavioural information to reveal where there is congestion, work out why it is occurring and take action to solve the problems.

Exeter aims to deliver 12,000 new homes and 60 hectares of new business land by 2026, which will put additional pressure on the city’s infrastructure and public transport. Using existing roads and public transport services such as buses more effectively will be essential to achieving that aim.

 

Sensing traffic and demand


Most major cities are experiencing a boom in construction in order to cope with growth in population. More homes and more people mean increasing pressure on everything from motorways to urban rail.

 

Congestion impacts the daily lives of commuters and the local economy, disrupting businesses and visitors to the city. To meet this challenge, many city planners are looking to smart transport solutions to reduce congestion and to optimise the use of city public transport.

 

For example, the combination of smart sensors in road surfaces, motion sensors on lampposts, and data from CCTV cameras, can all be used to monitor increases in the number of road users and decreases in average traffic speeds. They can pinpoint accident locations through voids in traffic flows and even identify the location of parking spaces.

 

Meanwhile, bicycle hire service Ofo has expanded from China to the UK, using GPS data from trackers on its bikes to offer a decentralised, city-wide cycle hire service without the need for expensive and fixed cycle docking stations. Anywhere can become a pick-up and drop-off location for a bike, and logistics staff can redeploy stock to areas reporting the most demand for them.

When temporary surges occur, such as a public transport failure, an event or the advent of good weather, smart transport data can be used to facilitate maximum accessibility and minimise unused capacity.

 

Even outside of cities, smart motorway projects for the M3 and M4 motorways are already making use of surface sensors and dynamic lane and speed reassignment, providing temporary increases in capacity and better flow management at peak times.

 

Connecting the dots

By taking a sensor approach, not only can slowing traffic be spotted faster, but countermeasures can be implemented automatically and more efficiently. Measures include repurposing hard shoulders as temporary extra lanes to clear congestion, rephasing traffic lights, and automatic adjustment of variable road speed signs.

 

Automate lane closures are another option, rather than waiting for a human with cones to block off lanes if a car has broken down. Further, smart street lighting ensures that money is not wasted on excessive lighting that’s not needed on empty roads.

 

This is in addition to the most obvious function – feeding data to mobile apps, display screens at bus and train stops and cycle hire locations, as well as to vehicles themselves to better inform individual users.

 

Data can also be collected from decentralised sources such as the vehicles themselves. As we move closer to unmanned vehicles, autonomy will rely on a regular, decentralised and localised data feed in order to fully anticipate road conditions and incidents. The same decentralised network of vehicles can also feed data back to smart city interfaces and databases, as well as to other vehicles, to GPS device networks and so on.

 

Of course, there are a few issues to overcome before autonomous rides and drone deliveries become an expected or even demanded thing.

 

Along with technical hurdles, there are legislative barriers, insurance and liability questions, and even cybersecurity concerns. But we’re so much closer than we have ever been to seeing the future of transport that we’ve been promised for decades.

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