In today's artificial intelligence outbreak, what effect will happen when artificial intelligence and autopilot integration? It is optimistic about the application of artificial intelligence in autonomous driving. More and more manufacturers have begun to invest a lot of resources for in-depth layout. .
Artificial intelligence, which is currently the “windowâ€, is being integrated with another market focus “autopilot technologyâ€. It is pointed out that autonomous driving is the ultimate scene of artificial intelligence, and there is no one.
Toyota Motor Corp. recently said that it will begin testing its own self-driving electric vehicles around 2020. This electric vehicle will use artificial intelligence technology (AI) to interact and communicate with drivers. Artificial intelligence, which is currently the “windowâ€, is being integrated with another market focus “autopilot technologyâ€. It is pointed out that autonomous driving is the ultimate scene of artificial intelligence, and there is no one.
Automatic driving is inseparable from artificial intelligenceAccording to the forecast data released by the Institute of Electrical and Electronics Engineers (IEEE), the era of autonomous vehicles will arrive around 2040, when the proportion of self-driving cars in the total number of cars will reach more than 75%. Encouraged by good market prospects, from Internet companies such as Google and Baidu, new and old car brands such as Tesla and Toyota, to semiconductor companies such as Intel, Qualcomm and NXP, they have invested heavily in autonomous driving technology. "Autopilot, interconnect and electrification are becoming the three major trends in the global automotive industry," said NXP's global vice president Ross McOuat in an interview.
However, true autonomous driving still has a long way to go. From a technical point of view, the main problem facing autonomous driving is that the sensing and decision-making algorithms themselves are still unreliable. Once practical, the environment faced by autonomous driving will be completely open, and problems such as weather, light, and sudden road conditions will all be challenged. Therefore, true autonomous driving must rely on powerful computing power, massive data, algorithms and decisions, and sensor data collection.
The realization of artificial intelligence is also highly dependent on these four basic elements. Therefore, the combination of artificial intelligence and autonomous driving has a unique advantage. Cars will become the main application areas of artificial intelligence. Aart de Geus, chairman and co-chief executive of Synopsys, said that adding AI to traditional cars would subvert the perception of travel and mobility over the past few thousand years, and the human-computer interaction of vehicles will be strengthened. Ross also said that artificial intelligence, including autonomous driving, will undoubtedly be a very important component of the future automotive industry, and artificial intelligence is very important to improve the safety of autonomous driving.
International manufacturers in-depth layout "artificial intelligence + automatic driving"It is optimistic about the application of artificial intelligence in autonomous driving. More and more manufacturers have begun to invest a lot of resources for in-depth layout, and have introduced some practical products. In the face of competitive pressure from traditional automakers and high-tech competitors in the field of autonomous driving and smart cars, Toyota Motor Co., Ltd. promises to invest $1 billion to develop advanced autonomous driving technology and artificial intelligence technology by 2020. . Okabe Sho, general manager of Toyota Electric Vehicle Business Planning Department, said: "With the application of artificial intelligence technology, we hope to expand and enhance the driving experience of the car, so that the car can become a secondary object of people's emotional communication."
In terms of chip makers, on October 10, artificial intelligence chip manufacturer Nvidia released the world's first artificial intelligence computing system designed to drive self-driving taxis. The new system, called Drive PX Pegasus, will be designed for Level 5 autopilots, which can be completely controlled by sensors and computers without the intervention of the driver. According to Nvidia, the entire Pegasus is only the size of a license plate, and its performance is more than 10 times higher than the existing system. On October 17, NXP, the world's largest auto electronics manufacturer, also unveiled the new control and computing platform S32 for connected cars, electric cars and self-driving cars. Ross said that the S32 platform provides a unified architecture for microcontrollers/microprocessors (MCU/MPU) and is the world's first fully scalable automotive computing architecture to be adopted by high-end and general-production automotive brands. As for earlier, Intel bought Mobileye for $15.3 billion, pushing the peak of "artificial intelligence + autopilot" to its peak.
China also attaches great importance to this development trend. The "New Generation Artificial Intelligence Development Plan" issued by the State Council (hereinafter referred to as "Planning") has repeatedly mentioned the need to focus on the development of autonomous driving technology in the automotive industry, and to build intelligent transportation. Breakthroughs with independent autonomous technology platforms. For the first time in the "Planning", artificial intelligence has been upgraded to the height of the national strategy, providing a clear development path for the intelligent process of the automotive industry.
Li Deyi, an academician of the Chinese Academy of Engineering, pointed out in the "2017 China Automotive Industry Development (TEDA) International Forum" held recently that the automakers have achieved the ultimate in automatic control in the car and also touched the automated ceiling. With artificial intelligence to complete, it is necessary to research the driver, learn the driver, analyze the driver behavior big data, and then replace the driver through a smart agent that materializes the driver's online cognition—“driving the brainâ€.
Achieving automatic driving requires "strong artificial intelligence"Although the trend of “artificial intelligence + autopilot†is optimistic, there is still a long way to go before it matures. Some consulting agencies estimate that the current automakers only install artificial intelligence in the high-end models to partially assist the driver. In 2015, the AI ​​system installation rate of the new models was only 8%.
Gao Tianqi, vice president of Lenovo Star Investment, pointed out that the innovation and application of most related technologies are still in the category of weak artificial intelligence. As the ultimate scene of artificial intelligence, automatic driving, like the implementation of strong artificial intelligence, is a process that needs long-term development. Complete, open autopilot may not be what you can think of at the moment, and even the carrier that ultimately achieves autonomous driving will not be a "car" or it may be difficult to define it as a "car."
In response to chip support in this area, Ross pointed out that chips and software are becoming the core force that dominates a car, driving the car toward electronic, networked and automated driving development. “This will result in huge data processing capacity for the car. In the next five years, the software complexity of the car will be further enhanced, which puts higher demands on the future car in the following aspects: greater bandwidth Ethernet support, Stronger environmental cognition and higher computing power,†Ross said. These require the cooperation of hardware and software to achieve, which also indicates that the application of "artificial intelligence + automatic driving" will be a long-term process.
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