There might be more glamorous marques attached to other autonomous vehicle projects, but Ford’s unflashy version has a skill that its rivals cannot currently match: the ability to drive itself on roads covered with snow and ice.

Its automaton uses what Ford describes as LiDAR (which stands for light detection and ranging) sensors to collate data during journeys taken in good conditions, mapping not only the road but also key landmarks and other information that it can use to determine its location. It accumulates a vast repository of useful data – in the region of 600GB per hour – which it can then make use of to keep itself on track even when the road is obscured or hidden from its cameras.

Ford claims that this method is far more accurate than using GPS tracking; while the latter can be off by as much as 9m, the manufacturer states that its radar and camera method is accurate to the nearest centimetre.

It’s not yet truly ready for real-life use just yet, however. While it is able to successfully navigate difficult conditions in a test environment, it has not yet been taught to account for the increased challenges that such terrain creates and how it should alter its performance accordingly.

Clearly, environmental threats such as flooding, heavy fog and high winds will all need to be factored into smart vehicle intelligence before we have a fleet of road-worthy self-driving cars on our streets. Still, the evidence suggests that Ford is well on its way towards devising a solution to meet these challenges.