This article is originally published in Express Mobility on Financial Express. It was authored by Mr. Rajiv Tandon, a Subject Matter Expert at KPIT Technologies on Cloud and Big Data. This article speaks about the significant impact of Cloud computing and Data management on development costs and timelines.

In Autonomous Driving and ADAS development, Cloud computing and Data plays a crucial role, where its management, re-use, and analytics can lay massive impact on development cost and timelines.

The automotive industry is going through a ‘Tech-Tonic’ change, mainly focusing on Autonomous Driving (AD) development in Cloud.

An autonomous vehicle (AV) processes the inputs (Data) from various sensors to make the driving decision. A typical autonomous vehicle (AV) generates upwards of 40 terabytes of data in a single day, and for autonomous driving (AD) development, this Data is ‘Gold’!

The data generated while testing AVs must be stored and re-used to train & refine the AD software and various Artificial Intelligence, Machine Learning, and Deep Learning software components.

With increasing complexity in the development cycle of a vehicle, there is a keen focus on data management and dynamic-distributed computation, as it can have a critical impact and costs can rise exponentially if computation and data are inefficiently managed.

Figure 1 : Autonomous Vehicles Generate up to 40 TB of data per day

Essentially, all the generated data must be classified as useful – not useful so that it can be re- used for the development process to save time and cost. Additional data (Petabytes) is generated during the development process, e.g., when one executes validation processes like Software in Loop (SIL), Model in Loop (MIL) Hardware in Loop (HIL), and Processor in Loop (PIL). Each version of these validation tests must be stored and made accessible to the engineers so that the algorithms can be evaluated and fine-tuned. And this activity must be done at ‘Hyper-Scale,’ e.g., an AV has to be tested in the virtual world (simulation) against millions of scenarios. If one virtual scenario is 2 minutes long, it will take 1000 days to execute, but at ‘Hyper-Scale,’ one can achieve this in 10 days.

The automotive industry is in the initial phase of adopting Cloud technology & techniques, and there is a lot that can be done in terms of application and innovations.

This article covers three key topics in-depth about Cloud; they are

  • What can be done with Cloud?
  • What are the typical challenges faced while implementing?
  • How can one overcome these challenges?

Read about these topics from the link mentioned above.

Cloud technology is truly a game-changer for the automotive industry. With the potential, it brings in data management, hyper-scale computation, tremendous analytics. Cloud will help develop unique features, provide faster validations, and save enormous costs and time in the development cycle.

At KPIT over the past decades, we have built a strong practice for Autonomous Driving development. We are strategic software development and integration partners to global Vehicle Manufacturers (OEMs) and their suppliers (Tier 1s). Our team has developed unique applications that can run across infrastructure (Cloud & On-premise) and is already executing millions of scenarios for virtual validation of Level 2,3, and 4 autonomous vehicles. KPIT has built strategic partnerships with leading players like Microsoft and Amazon to bring this Enterprise 2 Enterprise (E2E) technology to help clients scale efficiently and significantly reduce the time to market on this solution.

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