Why experts believe cheaper, better lidar (for self-driving cars) is right around the corner
Today, most self-driving cars rely on a trio of sensor types: cameras, radar, and lidar. Each has its own strengths and weaknesses. Cameras capture high-resolution color images, but they can't measure distances with any precision, and they're even worse at estimating the velocity of distant objects.
Radar can measure both distance and velocity, and automotive radars have gotten a lot more affordable in recent years. "Radar is good when you're close to the vehicle," says Craig Glennie, a lidar expert at the University of Houston. "But because radar uses radio waves, they're not good at mapping fine details at large distances."
Lidar offers the best of both worlds. Like radar, lidar scanners can measure distances with high accuracy. Some lidar sensors can even measure velocity. Lidar also offers higher resolution than radar. That makes lidar better at detecting smaller objects and at figuring out whether an object on the side of the road is a pedestrian, a motorcycle, or a stray pile of garbage.
And unlike cameras, lidar works about as well in any lighting condition.
The big downside of lidar is that it's expensive. Velodyne's original 64-laser lidar cost a whopping $75,000. More recently, Velodyne has begun offering smaller and cheaper models with 32 and 16 lasers. Velodyne is advertising a $7,999 price for a 16-laser model introduced in 2014. Velodyne recently announced a new 128-laser unit, though it has been tight-lipped about pricing.
Velodyne can't afford to rest on its laurels. The company is about to face a lot of competition from rivals building lidar systems with very different designs.
Read about three possible alternatives at http://bit.ly/2Cufckj
