Autonomous Vehicle Hopes Hinge on Crash Avoidance Technology
Kirkpatrick said this common belief in taking a multiple-technology approach to collision avoidance renders the whole technology debate moot, at least for now. “That’s why when you see Elon Musk talking about lidar and crapping all over it, it’s important to understand we are not going to see autonomous vehicle systems, whether you’re talking about cars or trucks or buses, rely on a single system for crash avoidance,” he said. “It just doesn’t make any sense because each technology has specific strengths and limitations.”
The need for multiple crash avoidance schemes and robust computing architectures to handle large volumes and varieties of sensor data may raise other challenges for the autonomous driving sector. It could increase the number of sensors that need to be deployed on a vehicle, or require sensors capable of leveraging multiple technologies, either of which could add cost. Also, collecting and processing more data from different sources also could tax in-vehicle computing power, meaning that some processing — perhaps pertaining to vehicle functions that don’t require zero latency — could be off-loaded to nearby edge computing location outside the vehicle.
Given the critical importance of crash avoidance capabilities to the future success of autonomous driving, companies in the sector just may have to navigate their way around these obstacles.