IDTechEx: LiDAR's Uncertain Path in Autonomous Vehicle Tech
The road to fully-autonomous vehicles is paved with challenges, innovations and tough decisions regarding the technology that will lead the way.
Among these, LiDAR (light detection and ranging) technology is often heralded as a critical enabler of safer, driverless cars. However, questions about its adoption and role in the broader automotive industry linger.
Dr James Jeffs, Principal Technology Analyst at IDTechEx, raises some important questions: "After a decade of development, testing, trials, funding, partnerships, acquisitions, mergers, etc., where is it? Why are there not more cars on the road running LiDAR?"
Key insights from IDTechEx Report
IDTechEx's recent report, 'Autonomous Vehicles Market 2025-2045: Robotaxis, Autonomous Cars, Sensors', explores the adoption of LiDAR and its competition with other sensor technologies, such as cameras and radar. It highlights key trends shaping the autonomous vehicle market and examines why LiDAR uptake has not met initial expectations—particularly outside China.
One reason for the slower adoption rate of LiDAR lies in advancements in competing technologies. Cameras, supported by AI and radar, are increasingly meeting the needs of original equipment manufacturers (OEMs).
"The automotive industry hasn't been a particular pioneer of camera technologies, with sensor technologies lagging behind other industries," says James.
While cameras in the automotive sector may trail behind those in smartphones and digital cameras, they excel in dynamic range, which is critical for handling large brightness differences in real-time video data
The capability, combined with the increasing power of automotive processors from companies like Nvidia, Mobileye and Qualcomm, enables vehicles to process multiple high-resolution camera feeds.
"They can fuse multiple feeds and generate a detailed 360° representation of the vehicle's surroundings," James explains.
Tesla's approach exemplifies the trend. The automaker has famously opted for a vision-only system, eschewing LiDAR and radar.
James asks: "If humans can drive using red, green, and blue, why shouldn't cars?"
Radar vs. LiDAR: The battle for dominance
While Tesla may be an outlier, most automakers favour radar combined with cameras.
Radar operates effectively in adverse conditions like snow, heavy rain and fog, while providing velocity and distance information, making it a reliable tool for automated systems.
"Radar's Achilles' heel has been its resolution," notes James.
However, improvements in radar technology are closing the gap. Innovations from suppliers and startups offer radar systems rivalling LiDAR's angular resolution, diminishing the latter's competitive edge.
LiDAR's unique success in China
The story of LiDAR is markedly different in China.
"China has not quite reached the same milestones as Europe and the US in terms of deployments of higher levels of autonomous vehicles for general public use," James shares.
Yet, many Chinese automakers include advanced sensor suites featuring LiDAR, flagship Nvidia chips and high-resolution cameras in their vehicles.
Notably, the vehicles are competitively priced, often costing around US$40,000 less than similar models in Western markets. James identifies three reasons for this trend:
- Chinese LiDAR companies like RoboSense have scaled production rapidly, reducing costs.
- Vehicles are being prepared for future regulatory changes that may permit Level 3 autonomy, allowing upgrades via over-the-air updates.
- LiDAR has been marketed as a symbol of safety, resonating with Chinese consumers.
In contrast, Western markets have been slower in embracing LiDAR. The high cost and lack of consumer perception linking LiDAR to safety diminish its appeal. For most Level 2+ vehicles, radar and camera systems are considered sufficient, making LiDAR an expensive addition with limited value.
Looking ahead
IDTechEx's report provides a detailed analysis of available technologies, their applications across key markets and predictions for the autonomous vehicle sector over the next 20 years.
James concludes: "It details the growing robotaxi market, predicting future deployments and the industry's size over a 20-year forecast period."
While LiDAR's role in the autonomous driving landscape remains uncertain in the West, its adoption in China offers a glimpse into what might be possible under different market dynamics and regulatory environments. For now, the automotive industry's journey toward full autonomy will continue to rely on diverse technologies, each vying for dominance in this transformative space.
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