Summer Heat, Asphalt and Optical Tricks: Does a Modern Car Believe in Mirages?

Most of us have faced it in the peak of July heat: a shimmering “puddle” on the road ahead. We know it’s an illusion. Hot asphalt and layered air bend light so that our eyes see water where there is none. The human brain eventually makes sense of it—but what about cars whose “eyes” are cameras and sensors?

Unlike drivers, machine vision algorithms experience no illusions. Cameras capture light as it falls, which means they, too, record a bright patch glimmering on the asphalt. Whether that patch is read as a hazard, however, depends on the artificial intelligence behind the system. Machine learning models are trained to distinguish the reflections of a water surface from the grain of dry pavement by analysing color, contrast, and symmetry. They also compare sequential frames: real puddles remain fixed, while a mirage tends to recede or distort as the car approaches.

Even more decisive is sensor comparison. Radar and LiDAR do not “see” a mirage, since there is no physical object. That allows the system to confirm quickly that nothing on the road requires an emergency stop.

At higher levels of autonomous driving, the decision becomes more complex. Should the system slow down, alert the driver, or simply proceed through the phantom puddle? Context comes into play: how other cars behave, whether spray appears, what kind of reflection pattern is formed. It becomes a game of probabilities, with the system gauging its confidence in the diagnosis and adjusting its response accordingly.

In the end, mirages on hot roads are no fatal trap for autonomous systems, but they serve as a sharp reminder that even the most advanced car does not see the world as we do. It merely calculates probabilities and hopes the equation holds true.