Self-Driving Car POC

Computer Vision, Deep Learning, Robotics
Wuhan, China
Automotive Industry
Open Source Udacity Dataset, Python, Tensorflow

Self Driving Car POC

Making Wuhan’s transportation more reliable

Self-driving cars are set to change the way we live with technology on the cutting-edge of robotics, machine learning, computer vision, and mechanical engineering.

China’s economy is a hypergrowth environment; therefore the need for smart transportation networks is necessary to make megacities move faster and more innovative.


Hui Chen, owner of an 8000 employees supplier company for the automotive industry in Wuhan, China, had an awakening moment in San Francisco. He took an Uber from the airport and his Uber driver picked him up with a brand new Tesla Model X.

The driver was showing Mr. Chen the power of autonomous vehicles, when they were driving from San Francisco International Airport to Los Altos, California. - 26,2 miles - 90% on autopilot.

Chen saw his opportunity to bring self-driving cars to China. Being a leading suppliers for automotive propulsion technology, he wanted to start building his own self-driving car.

“I wanted to have my own self-driving car, a proof of concept. Back in China software developers told me that it’s not possible to build my own self-driving car.” His entire life, Mr. Chen never accepted a No. That’s why he built one of the leading companies in Wuhan.

Chen did reach out to his network in Silicon Valley and one of his friends recommended him to Hackerbay. Mr. Chen: “It was luck. My friend told me, you need to talk to the hackers. They can build everything.” Hackerbay never built a self-driving car before, but friends from University of Oxford reminded Hackerbay that the online-learning university Udacity recently published an open-source data set of self-driving cars with real data. This was the breakthrough insight, which gave Mr. Chen confidence.

“My entire life I never accepted a No. I like the Hackers. Hackers don’t give up. The breakthrough was an open source data set.”

Prior to meeting Hackerbay, Mr. Chen and his team were discouraged about how hard it would be to build a self-driving car themselves. But Hackerbay gave confidence to Mr. Chen and his company to really build a first proof of concept of a self-driving car themselves.

“Alyssa and I went through the pretty standard Hackerbay process,” Chen said. “She showed me a tanglible mockup, the Hackerbay ZX1 only 24 hours after our first contact. I was like: Those guys move fast and they really care about design and speed.”

The Hack Effect

The project started with expectation management. Since decades engingeering teams did work on self-driving car and autonomous vehicles all around the world. Mr. Chen and Hackerbay wanted to strart, where others did stop. Udacity and Mercedes Benz released a 240GB data set to the public with real street data. This open source data is a major breakthrough, because self-driving car projects can start without collecting the data and without wrangling the data, but start with analysisation and action plans to build the software straight away. Obviously streets in Wuhan, China are different than streets in California. But Mr. Chen’s self-driving car will learn over time. The deep learning algorithm just needs to start with a training set and is after this improving itself and self-perfecting.


The POC of Mr. Chen’s self-driving car was delivered in a lightning speed. Hackerbay worked round around the clock with an international, global team of 28 hackers to deliver results.

“It was impressive. 2 months after the project launch, I could sit in a customized Toyota Prius and drive the first 100 meters in my own self-driving car.”, said Mr. Chen. Hackerbay is improving the algorithm with computer vision and deep learning neural networks ever since. In addition, the Hackerbay Technology Center is training an elite team of the best software developers in Wuhan to continously improve the self-driving car and transfer knowledge towards their employees”

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