Research shows automakers' vision is in LiDAR for autonomous vehicles
A new study by Ptolemus Consulting Group found that most OEMs will use a "cocktail" of technologies, with LiDAR being key, to achieve full vehicle automation. This is instead of relying entirely on radars and cameras for vision, which is an approach championed by companies such as Tesla.
Ptolemus predicts that, despite significant decreases, the cost for OEMs to achieve safe operation of full autonomy (SAE Level 4) will still exceed $10,000 per vehicle in 2022, making it near impossible to launch fully autonomous private cars below the $100,000 price tag and prohibiting mass roll-out.
Robotaxis are expected to be launched in 2021, as their 24/7 driverless operation capability will allow ride-hailing operators such as Waymo to recoup the investment. Then, the mass market will see the introduction of L4 tech such as automated valet parking and highway drive in premium models.
Frederic Bruneteau, Ptolemus' Managing Director, stated, "Two years ago, most OEMs were adamant that sensors and AI would suffice. But high-profile accidents have pushed the safety imperative, requiring extra layers of redundancy. We predict that a 'good enough' approach to automation will never be authorized by regulators worldwide."
Another finding of the research is that the U.S. will be the first country to deploy Level 4 autonomous vehicles, winning the race of deployment vs. Europe and China.
In terms of cost of AV technology, long-range LiDAR for Level 4 are expected to come down by 40% by 2022. As a result, Ptolemus forecasts 100% growth in the market as the technology becomes more accessible for OEMs. Vision sensors are projected to contribute to 60% of the total costs of Level 4 AV systems; computing units to 30% of the total costs; and HD maps, HA GNSS, and AI to 10%.
Some OEMs, such as Tesla and Waymo, are developing in-house processors for their computing units to create tailored applications and improve power efficiency. This trend is giving rise to centralized computing units as OEMs look to simplify processing systems.
Artificial intelligence is another critical technology for autonomous vehicles, according to the study. Machine learning (ML) will be required from Level 3 in prediction and planning routes. Most OEMs are using ML for computer vision; however, applying ML to prediction and planning is only at an experimental stage. According to the research, Waymo is the only player currently experimenting with machine learning in the prediction and planning of routes.
Ptolemus’ research reveals that 5G technology is not essential for the roll-out of L4 vehicles.
Ptolemus’ "Autonomous Vehicle Technology & Supplier's Global Study" is a cross-technology, cross-supplier assessment of the AV industry. It leverages research of 80 tech companies and provides interviews with more than 20 vendors.