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Driverless Temsa ‘in production by 2022’


Turkish manufacturer Temsa has unveiled a prototype driverless electric midibus, the MD9 electriCITY, and says it plans to have it in serial production in 2022. It showed the protototype at the Nvidia Europe GTC exhibition in Munich.


Temsa began intensive autonomous vehicle technology development two years ago at its Adana plant, working in cooperation with Galatasaray University and Infotech company and supported by the Scientific and Research Council of Turkey (TÜBİTAK).


Chief executive officer Hasan Yıldırım says that competition in the automotive industry is essentially about technology. “The rapid developments in technology are actually redesigning the economic trends in the world. Chief among them are smart transport and smart cities. And the most important part of the smart city vision is electric and autonomous vehicles.


“In this sense, we view Temsa now more as a technology company than an automotive company. We are pouring significant investment into electric and autonomous vehicles. We take big pride in supporting our country’s economy with vehicles produced in Adana, which are entirely the work of Turkish engineering. Annually, we allocate about 5% of our consolidated turnover to research and development efforts with a view to becoming a global brand in our industry.”


To detect nearby objects nearby, the 9m electric MD9 electriCITY is equipped with three Lidar (laser imaging detection and ranging) radars and cameras. There is one Lidar on each side and one on top. This system fires laser pulses to measure the distance of nearby objects and surfaces.


The vehicle is also equipped with an infrared stereo camera to detect other vehicles and people around. Additionally, two cameras on top of the vehicle confirm the presence of objects in the area. Moreover, the vehicle’s radar detects the other vehicles around and calculates the distance between them and the bus.


Temsa says the desired level to be achieved in autonomous vehicle technology is for the vehicle to stay in the lane and to approach and leave stops after collecting passengers.


In the first phase of the three-phase project, the vehicle is expected to warn the driver about possible accidents. In the second phase, the vehicle is to slow down as soon as it detects a possible accident, and if the slower speed is not enough to avoid collision, brakes will kick in. In the third phase, the vehicle will gain enough autonomy to approach stops, pick up passengers, and stay in the lane.

The autonomous system uses the Nvidia PX2 computing system for data analytics and deep learning.

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