For self-driving cars to navigate without hindrances, it is important for technology developers to map the world’s roads as a blueprint. In a special guest feature with Telematics Wire, Siddhartha Bal, Director of Autonomous Mobility at iMerit, discusses the importance of building high-definition maps for better navigation by autonomous vehicles, and the current status of mapping capabilities.
Here are 5 key takeaways from the article:
- For an autonomous vehicle, our traditional maps are insufficient. For a self-driving car, a map has to give a lot more detail – for example, the height of a speed breaker, the distance of the pavement from the driving lane, the width of the road, the exact location of a traffic light, etc. This needs a completely different way of mapping cities, and it requires a lot of data collection to make it into a meaningful piece of information for the autonomous system.
- Our roads are ever-changing and thus self-driving cars need the ability to recognize real-time conditions and adjust accordingly. To keep these maps updated, self-driving cars can send automatic reports of their journey to the mapping teams and feed in new elements or changes on the roads. These can be quickly updated on the system maps and the information can be shared with the autonomous fleet which is on the road.
- Platforms like Nvidia’s Drive map and Mapbox proposing high-definition maps offer more ready-to-use solutions, but customers cannot self-edit or update the data as the maps are owned by the mapping companies. Furthermore, it is also a time-consuming process to update maps as customers depend on and wait for vendors to cover newer regions. For lack of a viable readymade option, many companies prefer to build their own maps.
- Most of the mapping is terrestrial but with new technologies such as drone mapping, the techniques are being extended to the skies. These drones are capable of capturing ground data (geospatial data) to build maps of the ground below. However, a sky full of unmanned objects could pose a challenge. So, the need is to bring order and regulation up above.
- Technologies like self-driving cars, and drones, coupled with AI systems, are carrying out the mammoth task of collecting data and feeding intelligent systems to build maps for autonomous mobility. But they still need human assistance to learn and deploy functions efficiently. Humans are needed also to monitor and track processes such that the data is expertly processed, and edge cases are identified and solved quickly.
Read the complete article here: Mapping Cities to Power Autonomous Mobility
