Interview: Goose Q organizes trucks on a road to save fuel
Fuel is the biggest cost for truck drivers in China. Slight price increase can even cause social protests as it happened few years ago. The biggest share of trucking in China is done by individuals, that’s why Chinese truck drivers have to find ways to make maximum out of their trips. Goose Q is developing a solution that can save 9%-25% of fuel and thus substantially decrease cost of logistics. To present “Fellow Team” technology in detail we did a brief interview with Goose Q CTO Tyreal Min.
Dimitry: Hello, everyone, we are interviewing Goose Q CTO Tyreal Min again today.
Tyreal: Hello everyone!
Dimitry: This interview we want to discuss one interesting Goose Q tech called “Fellow Team”. This technology can help drivers save gasoline. Why is this so important? Because gasoline is the biggest cost for drivers, so we are discussing this matter. Could you briefly introduce “Fellow Team” tech?
Tyreal: “Fellow Team” tech is a combination of communication technology, geo-positioning, and some of our dynamic algorithms. Drivers can be dynamically organized during the driving process, so that they form a team. In this formation front car is breaking the wind for the following cars, so driving in a line, it is possible to reduce fuel consumption, in a same manner as a flock of flying geese.
Dimitry: When did Goose Q team start developing this technology?
Tyreal: We actually paid attention to this set of theories for a long time, but the research started in the beginning of 2017. At that time, we also referenced to a variety of materials in the industry and started development of the prototype in 2018. Then we did some small-scale internal tests in 2019.
Dimitry: What is the progress up to now?
Tyreal: Now we are testing the technology on a small scale for a short-distance operations and it is going well.
Dimitry: Is this thing particularly complicated?
Tyreal: Actually, this is a very complicated thing. It is a real-time organization and communication of vehicles in a completely dynamic environment. Cars are moving towards different destinations. Then new cars can join any time, or some might leave anytime, so in this process, you need to apply technology to guide everyone efficiently, let everyone form teams as much as possible, and then, the longer you are with a team, the more fuel you will save.
Dimitry: So this algorithm is constantly computing where a car goes, can they go together, etc?
Tyreal: Yes, in addition to sending you a message about match, there is also a process of continuous dynamic guidance. It will keep reminding you to catch up with a front car or let you wait for a car behind. In this way, a team can be formed. It won’t be possible to form a team otherwise.
Dimitry: Now big companies like Alibaba or Uber are all researching unmanned cars. I think Fellow Team technology will be particularly interesting for this kind of company.
Tyreal: Right, the unmanned car research is about autonomous driving. Our Goose Q Fellow Team is about many cars are organized flexibly. In fact, the complementarity between the two is very strong. Very good point of cooperation.
Dimitry: Very good, then there are no other questions on my side. What else do you want to say here?
Tyreal: Actually, in the whole implementation process of this technology, a lot of practical work is required, that is, you have to carry out a lot of tests, and roads in China are complicated.
Dimitry: Oh, wait a minute, I forgot the most important question, how do you plan to use blockchain technology?
Tyreal: Because in the process of team formation, the head car is the first car, it bears a very important role, the role to break the wind resistance, it has to spent relatively more fuel, so say this time, the vehicles behind should pay a certain amount of compensation for the contribution of the front vehicle. The front car plays hard, so that behind cars can save fuel, so the behind cars have to pay token for the person in front. This motivates the front car to contribute to the entire team, and its contribution is recorded.
Dimitry: So the algorithm of Fellow Team calculates how much tokens behind cars should pay, isn’t it?
Tyreal: Right, it records everyone’s contributions.
Dimitry: I have no questions here, then if you have any questions, please leave a message in the community.
Goose Q is the biggest in China road data computation engine with more than 10 years of development history. Goose Q’s main purpose is to provide a visual, verifiable, credible, traceable, anti-fraud, immutable data of the logistics industry in order to enhance its efficiency and transparency as well as to improve truck drivers’ financial and psychological wellbeing.
Webpage: http://www.gooseq.com
Telegram group: https://t.me/gooseQ
