Maneuvering a vehicle in any type of weather

can come with its own set of challenges and limitations.

Maneuvering a vehicle through conditions

that limit visibility, such as mist or fog,

can be even more challenging or even dangerous.

But now, thanks to a team of researchers out of MIT

and their newly developed system,

there may be a solution to this problem.

MIT researchers have developed a novel imaging system that

can gauge the distance of objects

shrouded by fog so thick that human vision can't penetrate

it.

An inability to handle misty driving conditions

has been one of the main obstacles

to the development of reliable autonomous vehicular navigation

systems.

So the MIT system could be a crucial step

toward self-driving cars.

To test their system, the team placed objects

in an enclosed box approximately one meter long

and then gradually filled the space with thick fog.

Outside, pointing into the box, there

is a laser which fires pulses of light

into the foggy scene and then a camera that

measures the time it takes their reflections to return.

What they found was their system was able to image objects

even when they were indiscernible to the naked eye.

More specifically, in fog so dense

that human vision could only penetrate 36 centimeters,

their system was able to resolve images of objects

and gauge their depth at a range of 57 centimeters.

57 centimeters is not a great distance,

but the fog produced for the study is far denser than any

that a human driver would have to contend

with in the real world.

The vital point is that the system performed far better

than human vision, whereas previous systems have performed

worse.

The system is designed to get around

the issue of light reflecting off water droplets in fog,

which confuses most imaging systems, making

it almost impossible to discern objects ahead.

The MIT researchers developed an algorithm

that uses statistics about the way fog

typically scatters light to separate

the raw data from the camera into two parts,

the light reflected from the shrouded object

and the light reflected from the fog.

The light reflected from the object

is then used to image the scene and calculate the object's

distance.

Of course, visibility is not a well-defined concept,

since objects with different colors and/or textures

are visible through fog at different distances.

So to assess the system's performance,

the team used a more rigorous metric

called "optical depth," which describes the amount of light

that penetrates the fog.

Optical depth is independent of distance,

so the performance of the system on fog

that has a particular optical depth at a range of one meter

should be the same as its performance on fog

that has the same optical depth at a range of, say, 50 meters.

In fact, the system may even fare better

at longer distances, as the difference

between light particles' arrival times

will be greater, which could make for more accurate images.