As we’ve seen over the past two articles in our series on intelligent transportation systems (part 1, part 2), the way in which we travel, and the systems guiding and protecting us, are becoming increasingly intelligent and complex, which in turn has enabled us to devise and develop even more applications for the technologies that now make up ITS systems around the world.
Big Data, automation, and artificial intelligence has brought us closer than ever before to realizing ideas that as little as fifty years ago would have been considered pure science fiction. In this article, the third and final in our three-part series on intelligent transportation systems, we’ll peer into the not-so-distant future and take a look at some of the incoming developments that will soon begin to integrate themselves into our ITS systems.
As the intelligence and complexity of our intelligent transportation systems and their component technologies continues to grow, so too will their thirst for data. As with a large number of technological innovations occurring within the Fourth Industrial Revolution, data seems to be the driving force behind many of the technologies applied within intelligent transportation systems.
With an increase in the number of sensors, gauges, cameras and other connected devices and technologies within ITS systems showing no signs of slowing down, the amount of data being produced along our railways and highways looks set to increase indefinitely as we continue to incorporate new systems and technologies into our transport infrastructure.
In order to precisely monitor traffic conditions, warn drivers of environmental or weather hazards, monitor road wear and tear or attempt to reduce the amount of time a vehicle spends idle at traffic lights, ITS systems need a healthy diet of data. As we move into the future, vehicles will begin to share more and more data with each other, as well as the ITS infrastructure around them.
The ability to share vast amounts of data among vehicles in as close to real-time as possible would enable not only more efficient intelligent transportation systems, but also safer journeys for drivers. It is also not unreasonable to assume that more efficient ITS systems could also lead to more environmentally friendly and sustainable transportation systems.
Machine Vision in ITS Systems
While not nearly as widely or as excitedly discussed as autonomous vehicles or the sea of vehicular data being produced by the integration of smart and IoT devices, the introduction of machine vision into intelligent transportation systems has the potential to further optimize and future proof ITS infrastructure in a significant way.
Cameras are utilized for many different applications within ITS systems such as traffic monitoring or security, however, up until fairly recently there had been substantial limitations to what they were able to provide a system in terms of analytical data. This is no longer the case thanks to advances in both machine vision and learning.
Now, ITS cameras are able to do their usual duties such as traffic monitoring, license plate recognition, traffic violation detection, and toll management, but are now also enhanced by more advanced abilities such as facial recognition systems that are able to run faces of those involved in accidents against police or traffic databases.
While full, widespread integration is currently a little way off, these systems will likely become much more prevalent in intelligent transportation systems of the not too distant future. Additions like machine vision will no doubt help to enable ITS systems to become more responsive, efficient, intelligent, and safe.
Autonomous Vehicles and AI Drivers
Autonomous vehicles and driverless cars have been engrained in our collective conscious for many decades now and, over the past few years, we’ve come as close as we’ve ever been to realizing what so many science fiction authors and enthusiasts over the years helped us dream up.
Intelligent transportation systems will play a hugely significant role in the integration of autonomous vehicles as a when they become feasible for widespread development and deployment and many smart city developers are already building cities and towns around the idea that they will house advanced ITS systems and, someday, fleets of autonomous vehicles.
Artificial intelligence will also likely have a huge role in autonomous vehicles and driverless cars. After all, while it might not be human beings behind the wheel, these vehicles won’t be entirely driverless. AI’s ability to deal with vast amounts of data make it a much better suited driver in the environment it will find itself in. Being bombarded by information from infrastructure, environmental sensors and other vehicles would most likely make driving more difficult for humans, rather than less.