AI makes money by pulling goods and has already circled the earth 2,500 times

Yun Zhongfa comes from Ao Fei Si
Qubit | Public account QbitAI

The AI ​​​​pulling goods has already circled the earth 2,500 times .

From the Beijing-Tianjin-Hebei region to the Pearl River Delta, smart heavy trucks carrying express delivery, food, beverages, clothing, and even auto parts shuttle on the highways connecting the country's seven major economic zones .

Maybe the things you eat and wear recently were brought by AI from other cities.

Who is this domestic player?

Inceptio Technology . The NOA commercial mileage of its trucks has exceeded 100 million kilometers .

And with the help of AI, logistics companies can save up to half of labor costs per vehicle and 3-5 liters of fuel per 100 kilometers . Individual drivers can also increase safe driving mileage by 20% and increase their monthly income by more than 2,500 yuan.

It took a year and a half for Inceptio Trucks' NOA safe operating mileage to go from 0 kilometers to 50 million kilometers; but from 50 million kilometers to 100 million kilometers, the time was shortened to 8 months, doubling the commercialization process.

At the same time, it achieves comprehensive coverage of the entire trunk logistics industry, and customers in various subdivisions such as express delivery, less-than-truckload lines, and contract logistics also realize truck NOA.

The commercialization process of passenger car autonomous driving is still unclear, but commercial vehicles are already ahead of the curve—smart heavy trucks equipped with Inceptio Trucks NOA are accelerating in the commercialization process?

Inceptio’s secret: find the core of commercialization

Commercialization has always been the most difficult level in the field of autonomous driving technology. It requires not only the maturity of the technology, but also involves safety, cost control, user experience and other aspects.

In addition, there is an essential difference between the commercial vehicles represented by smart heavy trucks and the passenger car track, and that is the difference in user value .

Passenger cars are aimed at C-end users, and there are various product and feature highlights. User purchases are not completely rational, but user stickiness can be high or low. According to industry insiders, the actual use scenarios of passenger car smart driving may only account for 10% .

Commercial vehicles are essentially oriented to the B-end logistics field. They need to accurately calculate costs and benefits. What they pursue is commercial value and solve pain points in production and operations. This requires in-depth insights into the industry and deep integration with the same industry. arrive.

This is also the general logic for the entire commercialization of AI and even B-side business.

Let’s look at B-end users in the field of trunk logistics. What do they consider?

It is safety, timeliness, labor cost, fuel consumption, car purchase cost and other refined requirements . Among them, the full life cycle cost (TCO) of heavy trucks has become a key consideration, including driver and fuel costs, which account for about 50%. The rest also includes maintenance, accident insurance, etc. Only when the "economic" accounts are clearly calculated can real money be spent on purchases.

Logistics customers currently using Inceptio intelligent driving heavy-duty trucks value the multiple user values ​​of Inceptio Truck NOA’s “safety, labor saving, labor saving, and fuel saving”, which in turn bring about “safety, cost reduction, efficiency improvement, and revenue increase”. commercial value.

Have you ever thought that the express package from the Pearl River Delta to Beijing, which takes more than 2,000 kilometers and 30 hours of driving, can be safely delivered by a truck driver alone?

For example, Inceptio's express delivery customers , including leading companies such as ZTO, YTO, STO, JD.com, and SF Express, have implemented dual-driver to single-driver on a large scale on road sections of 500 kilometers to 1,200 kilometers, reducing the labor cost per vehicle by 40- 50% .

On many traditional dual-driving routes ranging from 1,300 kilometers to 2,500 kilometers or even longer, the express delivery industry has also implemented smart heavy-duty trucks and successfully achieved safe single-driving throughout the entire journey by setting up relay-type relay points.

The driver staffing requirement for the same line has been reduced from 3 cars with 6-8 drivers to 3 cars with 5 drivers, from 4 cars with 8-10 drivers to 4 cars with 6 drivers, etc., which greatly reduces labor costs. At the same time, the driver's rest time is guaranteed, and the queue is improved. Class satisfaction has increased significantly.

In the more than ten hours a day of single-driving transportation operations for heavy-duty truck drivers who use Inceptio intelligent driving, intelligent driving can reduce core indicators such as forward collision warning, lane departure warning, and sudden deceleration for 100 kilometers by more than 75% compared to manual driving. ; Compared with traditional truck drivers, the physical fatigue of smart truck drivers is reduced by about 35%, and the psychological fatigue is reduced by about 11%; the smart fuel saving can be reduced by up to 2%-10%.

The proportion of mileage using Inceptio's intelligent driving system has reached 90%-95% , indicating extremely strong user stickiness.

这也是一亿公里背后展现出来的实际意义，嬴彻卡车NOA正通过自动驾驶技术带来的显著价值变革着干线物流这个领域，成为了深度融入到干线物流中不可或缺的新型生产工具。

Breaking into the “mainstream” market

Express Express represents the leading enterprise with the highest timeliness requirements and the highest management level in trunk logistics. Their recognition of the value of smart heavy trucks has a strong demonstration effect on the trunk logistics market with a larger scale and richer scenarios.

Inceptio Trucks NOA has successfully expanded into many subdivisions of trunk logistics, including less-than-truckload lines and contract logistics, covering multiple types such as cold chain, auto parts, alcohol, and FMCG. There are both large carriers, small, medium and micro fleets and individual drivers. This group of people is actually the "mainstream" buying heavy trucks.

Trunk logistics essentially makes money based on transportation mileage. Under the core premise of "safety", only by "reducing costs", "doing more" and "running faster" can you make more money.

比如为新能源汽车提供零部件物流运输的 华太物流 ，线路平均里程数约为1500公里，在批量投用智能重卡后，每百公里智能驾驶油耗比人工驾驶油耗可降低3-5升，部分线路人车比从2降至1，每公里TCO降低7-15%。因为智能重卡优秀的安全表现与省力舒适的驾驶体验，车辆出勤率显著提升，月均单车运营里程可提升10%。

Individual drivers’ concerns are more practical:

How can I save a few more liters of fuel? How to avoid fatigue driving and safely run hundreds of kilometers more? How to reassure the family and allow Kasao to return to the family?

Because of the revolutionary improvements in safety and labor saving of smart heavy trucks, the average monthly safe driving mileage of some individual drivers has increased by 10-20% , and the monthly net income can increase by 2,500-5,500 yuan . At the same time, the advantages of smart trucks being more fuel-efficient are very obvious to individual driver groups.

These figures provide a real "safety" and "economic" account, which is why Inceptio's commercialization process has been accelerated so quickly, and its customers in the entire trunk logistics field have also been fully expanded.

Data-driven technology and R&D

Customer needs and product value must ultimately be realized through technology and R&D.

Autonomous driving is essentially artificial intelligence. It is undeniable that the algorithm architecture has been basically determined, and innovation in computing power will still be limited in the short term. The data side has become a key indicator for improving technical capabilities.

Inceptio Technology’s “technology + operations” strategy and leading commercial closed-loop have accumulated 100 million kilometers of real data assets. Having such a volume of operational data is extremely rare at home and abroad.

Through accurate and efficient data collection on the vehicle side, high-performance, automated data processing on the cloud, and leadership in core technologies such as scene mining and automatic annotation, Inceptio Technology has established the most mature data-driven R&D system in the commercial vehicle field.

The scale and quality advantages of Inceptio's data assets accelerate the iterative update of Inceptio's autonomous driving algorithms, continuously improve truck NOA capabilities, and bring significant experience improvements to users, attracting customers from more fields and in more scenarios. Data is generated in operations, forming a unique data closed loop, further amplifying Inceptio’s leading edge in autonomous driving technology.

At the same time, some key internal measures of Inceptio have also strengthened the insight into the needs of users and the industry, further enhancing the user experience of Inceptio Trucks NOA.

For example, the “Make Friends with Drivers” activity .

It is mainly aimed at R&D personnel. Through "train following" (real long-distance freight transportation) and other forms, engineers can understand both the needs and the scenarios, and then continue to optimize the algorithm.

Commercial vehicle driving requires specialized licenses and qualifications. Unlike passenger cars, it is difficult for developers of commercial vehicles to drive their products and feel the real performance.

The CEO of Inceptio Technology once stated in a public interview that R&D personnel must understand users’ usage scenarios and understand user value .

Being in front of a computer every day, or just looking at background data, actually cannot replace every engineer's direct experience of user scenarios, driver behavior, including the actual operation of the product on the road.

It is precisely because the product design that directly addresses the pain points has strengthened the implementation advantages of Inceptio smart trucks that truck autonomous driving technology has also ushered in its "Inceptio moment."

Self-driving trucks usher in a “moment of qualitative change”

"Can autonomous driving still be a success?" and "Is there still hope for its implementation?" are the most frequently asked questions after the autonomous driving industry entered a "trough period ."

The market is no longer willing to look at PPTs and demos, but rather wants to see answers to more practical questions such as "How many self-driving vehicles are on the road?", "How much cost can be reduced and how much revenue can this technology bring?"

Behind this, a group of companies came out.

As technology research continues to deepen, the industry has reached a basic consensus: to discuss whether autonomous driving can be commercialized is to discuss whether it can be mass-produced and deployed on a large scale, so that it can be truly recognized by the mainstream market .

In terms of passenger cars, although Tesla , the world's number one autonomous driving player, finally launched FSD v12 in full this year, it still has to prove its value to users through free trials and test drives.

Now in the field of commercial vehicles, Inceptio has used 100 million kilometers to take the lead. It has proven its value among mainstream customer groups through cooperation partners and covered fields, and has gained high user stickiness.

These 100 million kilometers of commercial mileage are the best proof that the commercialization of self-driving truck technology has emerged from the trough and is moving towards a high-speed growth cycle.

The moment of qualitative change in autonomous driving may first occur in freight transportation and Inceptio.

This time, Chinese players will lead the way.

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