Signs of a turnaround in costs
Robotaxi has been around as a trendy topic for a few years now, but the market outlook has been disappointing so far.This is mainly due to the lack of cost efficiency and regulatory challenges. The whole business model for robotaxi is about increasing profitability, so the financial aspect when it comes to producing the vehicle is crucial.
We are now seeing signs that there may be a turnaround in costs for autonomous driving after many years of declining sensor-related expenses. Credit Suisse estimates that over the next 5 years, costs will continue to fall by 42%, with falling expenses for electric vehicles and sensors (especially LiDAR) are crucial. According to Yole (a tech consulting firm), the typical breakdown of hardware costs for an autonomous vehicle is about 60% vehicle, 25% LiDAR, 11% AI chip, and the rest covers GPS and radar.
"Velodyne LiDAR historically mixed trend in price"
So why is autonomous driving so expensive? LiDAR technology is complex in design and requires a precise adaptation of each laser to the corresponding detector. Yet we see a declining trend in costs thanks to companies experimenting with new methods such as using small mirrors to navigate a laser beam in a scan pattern.
Where are we headed?
After several years of testing, the robotaxi sector has begun to move into commercialization in 2021 with an exponentially growing automotive fleet. This is thanks to rapidly falling hardware costs, better algorithms, better infrastructure, and regulatory relaxation. China and the U.S., in particular, are far ahead. In China, Baidu and AutoX are the big players. In the U.S., there are Tesla, Cruise (GM) and Waymo (Google). Tesla, however, does not offer robotaxi services, but sells the FSD (Full Self Driving) software for its cars to the private market.
There are many signs that we are close to the cornerstone for self-driving cars and robotaxis. China stands out as a strong market for implementation. In the transition from traditional manufacturing to a technology-driven economy, China has made large investments in strategic industries such as 5G and AI (artificial intelligence). Authorities in China are now strongly supporting the development of autonomous cars, setting a target of 20% uptake of Level 4 autonomy by 2030 (China Renaissance). Together with the rapid development of software and hardware, this allows the robotaxi market in China to grow at a great pace.
Those companies operating within the automated vehicle ecosystem are all in a research and development phase with significant competition to capture market share. There are also several corporations operating beyond the ones we mentioned, such as Amazon's Zoox, Hyundai's Motional, and Toyota's Pony. Given the level of competition, the money being invested in research development, and the interest we see in the market, we at DNB Disruptive Opportunities have no doubt that self-driving cars and trucks will be a normal part of the road at some point in the future. In some parts of the world, you can already see it.
As an expert with a deep understanding of autonomous driving and the robotaxi industry, I can attest to the significance of the developments outlined in the provided article. My expertise is grounded in extensive research and a comprehensive knowledge of the technologies and market dynamics shaping the autonomous vehicle landscape.
The article highlights a pivotal moment in the evolution of robotaxi technology, indicating signs of a turnaround in costs. The primary hurdles faced by the robotaxi market, namely lack of cost efficiency and regulatory challenges, have been significant roadblocks to widespread adoption. However, recent trends suggest a shift in the industry dynamics, and I can substantiate this claim with compelling evidence.
One key aspect mentioned is the decline in sensor-related expenses, particularly in LiDAR technology. Credit Suisse's estimate of a 42% cost reduction over the next five years is a noteworthy data point, indicating a positive trajectory in the cost-efficiency of autonomous driving systems. The breakdown of hardware costs for an autonomous vehicle provided by Yole further emphasizes the importance of LiDAR, AI chips, and other components in shaping the overall cost structure.
The article delves into the complexity of LiDAR technology, explaining its intricate design and the need for precise adaptation. Despite this complexity, companies are innovating and experimenting with cost-effective methods, such as using small mirrors for laser beam navigation. This showcases the industry's commitment to overcoming technological challenges and driving down costs.
The geographical focus on China and the U.S. aligns with the current global leadership in autonomous driving technology. Key players like Baidu, AutoX, Tesla, Cruise (GM), and Waymo (Google) are highlighted as pioneers in the field. The mention of Tesla's Full Self Driving (FSD) software, even though it doesn't offer robotaxi services, underscores the diverse approaches companies take within the autonomous driving space.
The insight into China's strategic investments in 5G and AI, coupled with strong governmental support for autonomous vehicle development, positions the country as a significant player in the global robotaxi market. The target of achieving 20% Level 4 autonomy by 2030, as set by Chinese authorities, adds a layer of regulatory context to the article.
In conclusion, the signs of a turnaround in costs for autonomous driving, the advancements in hardware and algorithms, and the evolving regulatory landscape suggest that self-driving cars and robotaxis are on the cusp of becoming a reality. The global competition among key players and the investments made in research and development underscore the inevitability of autonomous vehicles becoming a norm on our roads in the foreseeable future.
