AI and Its Effects on Autonomous Vehicle Storage

The volume and velocity of data on our roadways globally have never been higher, and the ability to leverage and transform this massive amount of data into real-time intelligence and value is critical.
By Martin Booth
Aug 02, 2017

While today's cars typically implement about 16 to 64 gigabytes of internal data storage, on average, mostly to accommodate map and infotainment functions, tomorrow's autonomous vehicles are expected to require even more capacity. Internal research leads us to believe that autonomous vehicles may soon need more than one terabyte of storage to support a broader list of advanced capabilities that include intelligent driver assistants, voice and gesture recognition, eye-tracking, driver monitoring, black box recording, cognitive capabilities (that learn and analyze driver preferences to improve on them), and connectivity with other vehicles and traffic infrastructures. The volume and velocity of data on our roadways globally have never been higher, and the ability to leverage and transform this massive amount of data into real-time intelligence and value is critical.

More computing power is coming to the car to process data from a myriad of sensors, algorithms and connections to the outside world, resulting in more and more data being captured and analyzed. The data needs to be processed, and some of it will need to be stored locally or uploaded to cloud storage, as discussed in the following three areas: autonomous driving, digital assistants and data center connections.

While these areas promise to have dramatic impact on automotive storage themselves, they become particularly compelling when you factor in one of the most exciting trends in automotive today: artificial intelligence (AI). A computer-based technology that enables system applications to perform human-like tasks, AI not only promises to literally drive autonomous vehicles of the future, but has already been leveraged in many areas by auto manufacturers to automate and improve driving experiences. From assisted driving and digital voice assistants to deep-learning capabilities and connections with data centers and infotainment systems, AI-supported vehicle applications collect massive amounts of data, requiring new strategies to store and manage that information, both locally and in the cloud.

Autonomous Driving
Autonomous vehicles can collect 750 megabytes of data per second from their surrounding environment through a variety of sensors, such as cameras, radars and LiDARs (light detections and ranges), that help them to steer, brake and accelerate through traffic. In-vehicle sensors read, compare and physically map data to its environment so the vehicle can recognize and respond to obstacles that may come in its path. This generates massive amounts of data to successfully maneuver the vehicle—all of which requires a lot of additional storage capacity.

The compressed and processed data is then compared to a high-definition (HD) map in order to derive an accurate vehicle position. Such maps reside on top of the standard map data and contain information such as lane markings, curbs and signs that can easily double the map size. This information is used to produce real-time, actionable insights that determine how the car will navigate through traffic.

Some data, such as the vehicle's "drive" data, may need to be saved for a number of days or months, depending on regulatory, operator or original equipment manufacturer (OEM) requirements. The drive data recordings can range from seconds, for black-box accident recording, to days, relating to the monitoring of fleet vehicles for insurance, predictive maintenance, and other purposes, resulting in a wide disparity of storage requirements. Even if the drive data is uploaded to cloud-based storage, a local copy needs to be available. All of this contribute to greater on-board storage capacity.

It is expected that most autonomous cars of the future will be equipped with the latest in Wi-Fi connectivity and vehicular communications enabling passengers to browse the Internet, send and receive emails, and even watch a downloaded movie. Data requiring long-term storage will eventually be uploaded to the cloud. However, for moving vehicles, strong connections within an automobile will not always be guaranteed—plus, data must be stored locally, which adds to the storage density requirements.

Digital Assistants
Extending autonomous driving to new levels, digital assistants perform AI functions through software algorithms that generate an incredible amount of data. Unlike intelligent personal assistants that provide voice services for mobile devices, digital assistants enable the vehicle to learn about drivers' personal preferences, interests, driving style and more. This enables the system to not only provide a driving experience based on personalized information, but also continually increase its knowledge, imitate human behavior by analyzing behavioral patterns, and interpret real-life driving scenarios just like a human—even taking over the wheel when required.

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