With the rapid advancement of artificial intelligence, a wide range of AI chips and software algorithms have seen significant progress, and the vision of self-driving cars is becoming more tangible. At the recent Mobile World Congress in Barcelona, Huawei surprised many by not unveiling a new smartphone. Instead, it showcased its flagship Mate10 Pro, which was used to control a Porsche, highlighting the integration of AI into automotive technology.
The Huawei Mate10 Pro, equipped with its own Neural Processing Unit (NPU), can intelligently identify and analyze road conditions, providing real-time feedback to the car's autopilot system. During a demonstration, three obstacles—bicycles, dogs, and a football—were placed on the road. The NPU's image recognition capabilities enabled the device to detect these objects accurately, ensuring safe driving.
This demonstration is just one example of how AI is being applied in the field of autonomous driving. It suggests that Huawei could be preparing to enter the self-driving market. In fact, global efforts in autopilot technology have made remarkable progress over the years. Tesla introduced Autopilot 2.0 in 2016, claiming it had reached the fifth level of full automation.
Car manufacturers are now entering the autonomous driving arena. Tesla has been collaborating with Nvidia to develop the next-generation computing platform for self-driving vehicles. Recently, Elon Musk announced that Tesla is testing a major update to its Autopilot software, which is nearing the final stage of testing.
The new system will feature an NVIDIA DrivePX2 chip, along with eight cameras, twelve ultrasonic sensors, and an upgraded front radar, enabling a 360-degree perception of the vehicle’s surroundings. Tesla claims to have some of the most advanced AI neural networks for consumer products, and Autopilot 2.0 is expected to be integrated into the new Model 3.
In California, a recent announcement allowed automakers and tech companies to test their self-driving vehicles on public roads without a human driver. This marks a significant step toward legalizing autonomous systems. Companies like General Motors and Waymo have already begun testing self-driving cars.
As a subsidiary of Google, Waymo has partnered with Fiat Chrysler, Lyft, and Avis, allowing its autonomous vehicles to be tested across different automotive platforms. Waymo has also filed a patent for motion sickness prevention, aiming to adjust driving patterns to reduce stops and avoid discomfort for passengers.
Ford, after acquiring ArgoAI, has plans to launch an autonomous vehicle model by 2021. Recently, Ford acquired a patent for driverless police car technology, which would allow the vehicle to track illegal activity, record violations, and issue penalties automatically.
Ford is also planning to test its latest self-driving cars in Miami, with the goal of implementing a driverless delivery service. Urban autonomous delivery is a complex challenge, but in the future, we may see more smart cars on the streets, offering automated pick-up services and cargo transportation.
Despite the progress, power consumption remains a major obstacle. Electric vehicles are gaining popularity due to their zero emissions and quiet operation, but smart cars require energy for everything from motors to sensors, communication systems, and entertainment. Future smart cars must address two key issues: increasing battery capacity and reducing power consumption.
Advanced AI and deep learning are essential for smart cars, but running AI chips consumes a lot of energy. While NVIDIA is becoming an industry standard, Intel and Qualcomm are also developing low-power solutions. Tesla is working on its own next-generation autopilot chips. Although these innovations show promise, current autopilot systems still use around 2500 watts per second.
According to a University of Michigan project, computers in autonomous driving systems account for 41% of energy loss. Adding rooftop sensors, like those used in Waymo’s self-driving cars, increases air resistance and weight, further affecting energy efficiency. However, fully autonomous vehicles are getting closer, as Waymo has managed to reduce sensor costs by 90%.
With rising traffic accidents and carbon dioxide emissions, new energy vehicles and autonomous driving may soon become mainstream. Although affordable and energy-efficient autonomous transportation is still a long way off, limited autonomous driving under specific conditions is already feasible.
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