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In our previous blog we discussed the prospect of new technologies enhancing existing assets to enable smart traffic management. With smart city projects changing traffic as we know it, it’s important to also consider the potential challenges that will arise as we enter the era of autonomous vehicles — and the role technology will play in optimising their deployment.

As more and more self-driving cars and autonomous vehicles take to the roads, governments, local authorities and technology companies alike have been discussing infrastructure changes that may need to take place to safely accommodate their arrival.

One of the biggest issues facing the industry is the challenge of tracking the precise location of autonomous vehicles in transit. At present, much of the tracking relies on GPS to provide location data. But GPS alone is not accurate enough for a self-driving car.

According to recent government research in the US, GPS-enabled smartphones only have an accuracy of five metres under an open sky in dense urban environments. However, cloud cover and tall buildings can significantly interfere with, and affect the clarity of, the signal — minimising the faith authorities can put in the data.

To maximise the safety of autonomous vehicles therefore, the key is for stakeholders to aggregate their data sources. By taking data captured from cameras, traffic lights, over-roadway sensors and inductive loop detectors, and combining it with the data from on-board sensors — which transmit position, acceleration and speed to remote operating systems — a journey can be condensed into a singular viewpoint.

Fotech’s HWI Waterfall interface (right) displaying the movement of ELA along the designated path at the Telus Spark Centre (Calgary). The position and speed of ELA is monitored in real-time by Fotech’s Helios DAS technology – As it moves ELA generates vibrations which are detected by Fotech’s Helios DAS as those vibrations intercept the fibre optic cables buried under the path. (Left) A screen capture of the live-feed display from the paths camera network, with ELA moving in the zone highlighted by the DAS/HWI output.

One additional technology that can add significant value to all of this data is distributed acoustic sensing (DAS). All traffic generates acoustic or seismic data as it passes over roads. DAS essentially ‘plugs in’ to existing fibre optic cable networks — already ubiquitous in major cities and built-up environments — transforming them into sensors that can then capture additional tracking data.

At Fotech, we’ve partnered with the city of Calgary (among other stakeholders) in a world-first trial that deploys DAS technology to enhance the safety of autonomous vehicles. Starting in September, the trial is using our state-of-the-art DAS technology to track a low-speed, autonomous vehicle shuttling passengers along a closed roadway between Calgary Zoo and the Telus Spark Centre, travelling one kilometre each way.

Aside from analysing how different data streams can be combined to provide real-time vehicle information, the trial is gaining fresh insights on DAS’ ability to more accurately track an autonomous vehicle’s location. This is an important trial, offering insight to the future optimisation of smart city infrastructures, and the potential for increasing the safety of passengers, other road users and pedestrians alike. Indeed, the trial has already successfully proven that DAS is able to track the AV consistently, accurately pinpoint the AV on the route, and reliably highlight people/groups of people close to the fibre.

However, with the potential for DAS to be a technology of significant importance to future of smart cities and autonomous vehicles alike, we will be publishing further details of the trial in Calgary when it concludes.

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