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Lidar Points the Way for Self-Driving

October 31, 2017

Author: Mike Demler

To achieve fully autonomous (Level 4/5) self-driving capabilities, automakers must equip vehicles with an array of sensors that can identify pedestrians, road markings, traffic signs, other vehicles, and miscellaneous objects both day and night as well as under all weather conditions that human drivers can typically navigate. The devices that give a self-driving car its “eyes” include cameras, radar, and lidar (light detection and ranging). Although cameras and radar are becoming common in autonomous emergency braking (AEB) and other low-level advanced driver-assistance systems (ADASs), development of lidar suitable for mass-market self-driving cars remains an unsolved problem that has drawn the attention of numerous companies and startups..

Combined, the different views of a vehicle’s surroundings produced by cameras, lidar, and radar enable range and resolution far exceeding those of human vision. Integrating their outputs into a 360-degree environmental model requires running advanced sensor-fusion algorithms in powerful autonomous-driving processors.

But to enable lidar’s deployment in mass-market vehicles, manufacturers must first reduce its cost. Driven by the race to develop self-driving cars, progress on that front is accelerating. The spinning dome Google used in its first self-driving prototypes cost $70,000. Audi, Ford, Mercedes-Benz, and other automakers are now using newer models that sell for one-tenth of that price. For next-generation lidars, all manufacturers are developing more-highly integrated solid-state devices, which they expect will further reduce cost to just hundreds of dollars.

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