In a special guest feature with Telematics Wire, Radha Basu, Founder and CEO of iMerit, discusses “Data Annotation for Autonomous Vehicle Technology.”
Here are 3 key takeaways from the article:
- Mapping is key. AVs require a mix of directions, roads, traffic conditions, street imagery and other directional characteristics to make good decisions while running the algorithm. And all this is required in real time. We are expecting AV technology to predict and improvise decisions based on what is happening around the car. To achieve valuable data at such a granular level requires intelligent tools and technology.
- Edge cases are a massive deterrent to the mass adoption, safety and efficiency of AVs. Predicting and addressing them is an essential element of success for AVs. With the right workflow, talent, and understanding of a region’s given edge cases, they can be overcome effectively.
- For AVs to become a common reality, data annotation providers and developers must innovate to resolve edge cases and build data-driven systems which are foolproof and perceptive.
To read the full article click here.