The ADAS software development team
Linh is one of the youngest engineers of the ADAS (Advanced Driver Assistance Systems) software development team, which belongs to FPT Global Automotive, a subsidiary of FPT, the Vietnamese largest IT technology group.
ADAS helps drivers regulate vehicles more safely and conveniently, as conventional ADAS technology can detect objects, do basic classification, alert the driver of dangerous road conditions, and in some cases, slow or stop vehicles.
At first, the team had 10 members, which then increased to 12. All of them focus on developing software. Each member is in charge of creating one module which will be assembled with the others to create a complete system.
ADAS helps drivers regulate vehicles more safely and conveniently, as conventional ADAS technology can detect objects, do basic classification, alert the driver of dangerous road conditions, and in some cases, slow or stop vehicles. |
Linh is in charge of designing control systems and microcontrollers to ensure the proper operation of vehicles.
After one year of work, in October 2017, the software for self-propelled vehicles was put in a trial run on 4-seater cars at the speed of 25 kilometers per hour.
During the driving process, the car could automatically align to road lanes, turn right/left according to the road marking, identify objects on the roads, and automatically brake and avoid barriers.
With these capabilities, FPT’s self-propelled technology is approaching the second level out of five levels set by SAE (Society of Automotive Engineers).
At present, Linh and his teammates are renewing the steering system and designing the new version which is expected to be shown to the public in several months. They hope that the upgrade will make it run more smoothly. It will also be controlled by voice.
More than half of the members joined the research and development project soon after they finished university.
Linh said before he began working on software development for self-propelled vehicles, he mostly carried out IoT projects and had no understanding about self-propelled vehicles.
He had to spend a lot of time to search for information and consult experts to improve his knowledge.
His team had repeated failures when implementing the project. Only after they discovered the reasons behind the failures, and used new algorithms and ‘deep learning’ instead of ‘computer vision’ did their self-propelled car run smoothly.
He is optimistic about their work and hopes his self-propelled car will be able to travel from HCM City to Hanoi one day.
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