The companies related to self-driving cars, Waymo and Drive.ai offer jaunts to public in the regions Arizona, Texas, Frisco and Phoenix. In these areas plenty of people seem interested to use futuristic cars to move. Generally if someone chooses to ride a driver less car, chances are high that they plan a trip in urban areas.
Self-driving cars in rural areas?
But what about running a self-driving cars in the rural areas where there is no detailed, three-dimensional map for the reference, in between natural objects like grass and trees nearby.
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MIT researchers are working on that problem. Their strategy is to skill the cars to drive like humans. MIT team is working in the area of Devon, Massachusetts. Here, even map apps like Google Maps did not provide detailed map. The map only shows the line segment and the connection of the roads and shape roughly. These kinds of maps are different from the maps required by self-driving cars for working.
Detailed maps used by self-driving cars precisely indicate where they are operating in the city, where the curbs are, and what coming ahead like stop signs. As Drive.ai’s cars project in Frisco, Texas, operate by people, who used their sensors to create high-def three dimensional maps, which will later use by the car autonomously. The map used in urban areas does not scale very well to huge portion of the country because these areas are not facing the problem of constantly growing trees and shrubs.
The approach to drive-without-a-detailed-map is LiDAR sensors in the vehicles. The sensors will detect the surroundings of car. The unit consists of 64 lasers spinning around at 10 times per second. The car perceived where the road in front of it and drive to its destination- ‘local goals’. These local goals keep on updating five times per second as the vehicle moves. This is same as when a person maneuvering the car on the road by keeping ultimate destination in mind. This approach is positive to bring the autonomous vehicles out of city.