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  • 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.

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B1 中級 美國腔

看透霧(Seeing through fog)

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    joey joey 發佈於 2021 年 02 月 23 日
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