MIT research combines basic card and sensors for ‘mapless’ autonomous driving

May

7

2018

Researchers from the American MIT, in collaboration with Toyota, have developed a system for self-driving cars that works without detailed maps of an area. They combine basic maps with information from sensors on the car.

In their research, the scientists state that self-driving cars are highly dependent on detailed and annotated maps, indicating for example curves and traffic signs. This becomes a problem as soon as an autonomous car enters an area that has not been charted precisely enough. Their self-developed system, which bears the name MapLite , must offer a solution for this. It uses basal Openstreetmap maps without many details. The car then determines on the basis of various sensors, including lidar and GPS, where exactly it is located. In this way, the car must be able to take a road that has not yet been visited.

Their approach to so-called mapless driving, of which there are several, would have the advantage that it is not necessary to keep detailed maps up-to-date. The researchers state that the dataset on Openstreetmap maps contains the applicable traffic regulations for each part of the road. With the help of the lidar , in this case a HDL-64 from Velodyne, it is possible to watch 35 meters in front of the car. Therefore, according to the researchers, it should be possible to achieve speeds above 107km / h. If the data processing were to take place in parallel on a gpu, the speed could be increased.

One of the researchers, Teddy Ort, told IEEE Spectrum that a global map suitable for their system would fit on a USB drive. A detailed map of a small city, on the other hand, would require several gigabytes of space. One of the disadvantages of their approach would be checking the safety of the road. This would be less difficult on roads where cars have already driven over it. Another limitation is that the system is not yet able to navigate over roads in the mountains, because it can not cope with sharp rises and falls.

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