There are tens of millions of roads for autonomous driving to land. This company’s road is worthy of attention.

In 2018, when the investment outlet disappeared, autonomous driving was almost the only industry track that survived until the end of the year. The earlier fanatical pursuit of autonomous driving technology has gradually become rational, and several safety accidents that have occurred have made people start to calmly think about when autonomous driving can be truly commercialized.

In this context, the investment giants have come out to tell the public with real money that the future of autonomous driving is still worth looking forward to:

Since 2019, Aurora and, known as the “Dream Team” of autonomous driving in North America, have received huge financings of up to US$530 million and US$940 million respectively. Subsequently, TuSimple also completed a US$95 million Series D financing in the future.

Although most of the companies aiming at L4/L5 level (fully autonomous driving) autonomous driving have a relatively long timetable, it is an industry consensus that autonomous driving that cannot achieve the “door-to-door” function in a short period of time. However, such a situation does not mean that self-driving technology has no application value in the short term, and can only wait until the dawn of true full automation.

Take Nuro.AI, which has recently received a huge investment, as an example. This is an autonomous driving company focusing on unmanned delivery vehicles, aiming at typical vertical scenarios. It is worth mentioning that this round of financing came from the SoftBank Vision Fund.

Autonomous driving in vertical scenarios can be better implemented in various specific use environments, such as expressway freight logistics, port mining areas, etc.

The application of autonomous driving technology can help these industries significantly reduce costs, improve operational efficiency and increase safety and security. At the same time, the application of vertical scenarios can also reduce the objective risks caused by technical limitations, killing two birds with one stone.

Solving pain points is the key, and intercity expressways have become the first large-scale implementation of autonomous driving.

There are tens of millions of roads for autonomous driving to land. This company’s road is worthy of attention.

There is no doubt that the three blockbuster investments at the beginning of the year gave a clear signal that the freight scene will be the home of autonomous driving in 2019. Among all logistics vertical application scenarios, highway autonomous driving is the direction with the greatest demand and is considered to be the most likely to achieve large-scale profits.

Strictly speaking, highways are semi-closed scenarios for autonomous driving. Whether in China or the United States, highway autonomous driving shows an urgent “just need”. Especially for trunk logistics, the route and operation mode are fixed: after the goods are loaded, the driver drives the car into the nearest expressway, and then gets off the expressway at the exit closest to the destination.

In terms of passenger cars, the Nav on ap function that Tesla has opened in the United States is an automatic driving assistance function for high-speed usage scenarios, which can help users drive near full-automatic state after entering high-speed, and realize automatic change. Routes, on and off ramps, and changing high-speed routes. Only in this state, the driver still needs to hold the steering wheel at all times, ready to take over at any time in an emergency.

For freight companies, the most direct benefit of applying autonomous driving technology on highways is to avoid truck accidents and even casualties caused by drivers fatigued driving, and also greatly reduce the economic losses caused by accidents.

In China, there are about 7 million intercity heavy trucks and 30 million truck drivers, with an average of 50,700 traffic accidents per year, and an average of one casualty accident per 1,000 vehicles per year. Data from Ping An Claims shows that among freight accidents in China, expressways account for the highest proportion of cases and losses, close to 50%.

There are tens of millions of roads for autonomous driving to land. This company’s road is worthy of attention.

Driver shortages and rising trucking costs are also important factors in the popularity of self-driving delivery vehicles. Compared with ordinary consumers, freight companies are more willing to evaluate the efficiency improvements and returns brought by new technologies.

According to an October 2017 report from the American Trucking Association (ATA), the shortfall in demand for truck drivers in the United States is around 90,000. In the current situation of lower and lower profits in the transportation industry, the labor expenditure of drivers accounts for 45% of the total cost of road transportation.

In China, the driver’s salary accounts for about 35% of the total freight cost, and more than half of the drivers only take 1 to 2 days off each month. Overwork and fatigue driving have resulted in a high accident rate, forming a vicious circle. Implementing autonomous driving technology to supplement freight drivers and reduce work intensity will bring huge economic value.

Capital also quickly sensed business opportunities. In addition to important players in the field of autonomous driving such as Uber, Waymo, and Tesla, which are in full swing in the field of freight autonomous driving, domestic and foreign startups such as Embark, Starksy Robotics, Zhijia Technology, Inceptio Technology , TuSimple Future, and Zhuying Technology have also focused their attention on the field of autonomous driving freight logistics on intercity roads.

Among these start-up companies, Inceptio is different from most autonomous driving companies that seek to completely replace drivers from the very beginning. The L3 autonomous driving they envision in high-speed scenarios is to liberate drivers from the stressful and tiring work environment. Come out and transform into a vehicle administrator. Only in a few cases preparations are made in advance to intervene in the vehicle, thereby greatly reducing the workload and vehicle operating expenses.

In addition, L3 can also avoid a series of problems caused by complete unmanned driving that cannot be clearly defined by regulations in the short term, and is closer to mass production applications. Therefore, reducing the driving intensity of drivers, reducing energy consumption and safety hazards during driving is also one of the efficient paths to alleviate the contradiction between supply and demand and improve operational efficiency.

The dual innovation model of technology + operation will become a hard-core model for accelerating the commercialization of autonomous driving technology

Since 2018, the coordinated acceleration of the industrial chain of high-speed logistics automation for trunk lines has been launched, and Inceptio was born under this wave of synergy.

In April 2018, China’s leading IoT technology company G7, together with GLP and NIO Capital, jointly funded the establishment of Inceptio Technology, with Ma Zheren, president of G7, serving as CEO.

Ma Zheren believes that autonomous driving technology is not to deprive people of their livelihoods, but to improve their work and life. “It will bring 5% to 10% cost reduction and efficiency improvement for operators, thus generating huge economic benefits. benefits and social value”.

“The more boundaries of passenger cars are ‘manned’ and ‘unmanned’; in commercial use, especially in the application of intercity heavy trucks, the primary goal is not to change the car from ‘manned’ to ‘unmanned’, but Turn two drivers into one driver, turn a difficult and high-intensity job into an easy-to-use, chauffeur-driven job, and turn the driver into a vehicle administrator.”

In the view of the Inceptio team, no matter how the technology develops and changes, its ultimate purpose is to provide value to users. In the scenario of mainline logistics, the “value” provided by Inceptio Technology lies in reducing the cost and risk of truck freight, reducing energy consumption, and improving transportation safety.

At present, Inceptio Technology has R&D centers in China and the United States, independently developed L3/L4 autonomous driving technology, and cooperates with domestic first-tier commercial vehicle manufacturing companies and tier-1 suppliers to customize vehicles. It obtained the first trunk logistics test license in April, and has launched a comprehensive test to accelerate the mass production of L3 diesel heavy trucks.

At the same time, Inceptio pioneered the “pay by traffic (km)” smart truck rental operation service model. Under this model, Inceptio will provide full-stack service solutions around vehicle leasing, build an Asset As a Service operation platform, and improve logistics efficiency.

The first year of commercialization of self-driving freight is about to begin

Ma Zheren said that Inceptio currently has two clear development goals: first, to launch the first-generation mass-produced L3 smart-driving intercity heavy truck in cooperation with OEMs for the inter-city public roads; second, to operate a nationwide smart card Vehicle freight network, build autonomous operating system and central computing platform to handle all scenarios, not just the integration of functions between OEMs and Tier 1 suppliers.

Ma Zheren’s personal leadership has also accelerated the company’s R&D and operation to a certain extent. In November last year, only half a year after its establishment, Inceptio obtained the country’s first self-driving heavy truck test license for trunk logistics scenarios. certificate.

In addition, relying on shareholder re

Published on 10/28/2022