Navigating the Route to LiDAR Adoption in Automotive Applications

Abstract

This essay analyzes the adoption of light detection and ranging (LiDAR) technology in the automotive industry. It provides background on LiDAR and its advantages, then examines key factors driving and inhibiting adoption. The current technology landscape is explored, with beam steering techniques and laser wavelengths used as examples of industry preferences shaping innovations. The essay concludes that while performance improvements continue, pragmatic priorities like cost, reliability and integration steer LiDAR’s evolutionary path.

Introduction

LiDAR, a remote sensing method using pulsed laser light to map environments in 3D, is gaining traction in the automotive industry for autonomous driving applications. However, research suggests adoption is driven more by readiness for manufacturing than maximizing performance. This essay will provide an overview of LiDAR and its benefits, delve into beam steering and laser wavelength considerations, and argue that industry priorities guide innovation pathways despite pressures to advance sensor capabilities.

LiDAR complements other perception technologies like cameras and radar with unique 3D spatial sensing abilities. Its precision, range, field of view and direct depth measurement suit it to tasks like obstacle detection, mapping and localization. However, factors beyond performance steer adoption, including cost, reliability, supply chain maturity and integration challenges. Industry preferences direct innovations toward proven solutions rather than cutting-edge but risky options.

Background on LiDAR Technology

LiDAR has roots tracing back to laser developments in the 1960s, but only gained traction in automotive applications in the 2000s with 3D LiDAR’s beam steering capabilities. LiDAR hardware comprises four modules: the transmitter/receiver transceiver, beam steering, and control/processing. The transceiver determines fundamental performance factors while beam steering enables 3D sensing.

LiDAR’s advantages over passive sensors like cameras include:

• Precise 3D point clouds with centimeter accuracy

• Wide field of view up to 360 degrees

• Millions of points per second sampling rate

• 100m+ detection range

• Performance in low light and poor weather

These capabilities improve environmental perception and localization. However, adoption is based more on commercial readiness than maximizing capabilities.

Drivers and Barriers to Adoption

Initial motivations to implement LiDAR included augmenting camera and radar limitations. However, adopted systems often provide limited additional value over existing sensors. Automakers prioritize reliability, cost structure, supply chain maturity and ease of integration over maximizing performance.

LiDAR faces barriers like technology immaturity, high costs and unstable supply chains. The shifting competitive landscape offers many combinations of components and design choices. Adoption favors proven solutions meeting pragmattic industry requirements over chasing theoretical advantages still under development.

Figure 1. Existing and near-future passenger vehicles equipped with LiDAR (Source: IDTechEx)

Beam Steering Techniques

Beam steering techniques make performance-cost-reliability trade-offs influencing industry preferences:

• Mechanical rotors enable 360° but raise reliability concerns.

• MEMS mirrors are lower cost but produce irregular point clouds.

• Optical phased arrays (OPA) eliminate moving parts but are immature.

• Flash illuminates the whole scene but only works short range.

Automakers currently favor rotational approaches like Valeo’s Scala for balancing cost, performance and reliability. MEMS remains attractive but faces challenges. OPA is emerging as the technology matures. Despite pressures for advancement, liability avoidance steers adoption toward proven beam steering methods.

Figure 2: LiDAR components (Source: IDTechEx)

Laser Wavelength Considerations

Laser wavelength selection balances factors like eye safety, water absorption, efficiency, integration difficulty and supply chain maturity:

• 905nm dominates due to adequate performance and supply chain maturity.

• 1550nm infrared offers better range but suffers limitations in key areas.

Claims that 1550nm will dominate seem speculative compared to 905nm’s advantages for mass production. Still, innovations like frequency-modulated continuous wave (FMCW) LiDAR may eventually shift the balance by supporting velocity measurements. Overall, industry adoption dynamics favor established 905nm solutions.

The Path Forward

While revolutionary shifts are unlikely soon, steady innovation continues around optimizing LiDAR transceivers for cost, reliability and integration. Trends include:

• Migration to chip-scale arrays for lower cost and better reliability

• Component sharing between transmitter and receiver

• More lasers and new waveforms to improve performance

• FMCW for velocity measurement and interference rejection

• Faster time-of-flight sensors

• Multi-wavelength capabilities for material recognition

Rather than novel beam steering, enhancements will center on manufacturable solutions using integrated circuit manufacturing and photonics for economies of scale.

Conclusion

This essay has shown how industry priorities guide LiDAR’s evolution for automotive applications despite pressures to maximize performance. Adoption favors proven solutions meeting pragmatic reliability, cost and integration requirements. Beam steering techniques and laser wavelengths reflect preferences for mature options over cutting-edge but risky emerging technologies.

While advances continue, they will target transceiver integration and chip-scale manufacturing to serve commercialization. The path illustrates how practical factors shape technological choices even when capabilities are still advancing.