How cloud computing contributes to autonomous driving – a thought experiment.

How cloud computing contributes to autonomous driving – a thought experiment.

During his guest lecture at Stanford University, Dean Paron (Microsoft Azure) mentioned a fascinating argument about the importance of cloud computing which stayed present in my mind until now: The amount of data generated by an autonomous car is so high that cloud computing is one of the enablement factors which make autonomous driving in its current fashion possible.

In this context, this blog post aims at creating an understanding of the storage of data required by an autonomous vehicle, how a cloud solution for autonomous driving is in general designed and which challenges of implementation exist for the future.

A thought experiment – the number of laptops an autonomous vehicle needs for data storage

To better understand the data storage requirements of current autonomous driving solutions, let’s imagine a hypothetical autonomous vehicle with a hard drive of the size of your laptop and no access to cloud storage (adapted from Dmitriev, 2017). In this thought experiment, we assume a laptop storage capacity of 500 GB.

To estimate the number of laptops required to store the vehicle data for one day, we need to understand the basic information an autonomous vehicle needs to store. Those kinds of data highly depend on the technology applied by the autonomous vehicle. As the management consulting firm McKinsey&Company (2017) points out, the most recent autonomous driving technology mainly processes three different kinds of data in a so-called hybrid approach: Camera, light detection and ranging (LIDAR) and radar data. All those technologies capture different elements of the environment and result in a combined data pool. 

Read more : https://mse238blog.stanford.edu/2018/07/davidmyr/how-cloud-computing-contributes-to-autonomous-driving-a-thought-experiment/