Industry Voices: ADAS and Mobility Need Consistent Metrics for LiDAR

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Aravind Ratnam leads product at Sense Photonics. He is a technology and business strategy leader with a deep market expertise in automotive LiDAR. His career has spanned R&D/engineering, management consulting, and startups — with specific focus in strategic product leadership and value creation.

When safety matters, you need a LiDAR performance metric that you have confidence in. Traditionally, an individual performance metric such as range, resolution, field-of-view (FoV) or refresh rate have been used to define a LiDAR system’s overall performance in the market. These metrics alone provide an incomplete look at a system’s true capabilities because a system designed to maximize performance in one dimension has often come at the expense of others.

Range is the most common performance metric for a LiDAR system because it is critically important to be able to detect objects in front of a vehicle, especially travelling at high speeds, with enough lead time to brake or maneuver safely. Autonomous vehicles must be able to detect and identify objects at long range and in a variety of adverse or specific conditions. Vehicles need to be able to detect and identify an object with enough time to safely plan and execute a maneuver. Taking all of this into consideration, just over 200 meters of range for a normally oriented 10 percent reflectivity object under bright daylight conditions is generally considered as sufficient to fulfill long range requirements for L2+/ L3 ADAS applications. For AV applications, the actual range depends on the scope of the operational design domain (ODD), with a combination of short, mid and long-range sensing usually required.

With the array of LiDAR systems available, automakers look for a sensor that is able to see a specific minimum distance, across a large FoV, refreshes the scene often, and achieves high resolution – all at the same time. An industry-wide, comprehensive and impartial metric/ figure of merit is needed that can be applied broadly to evaluate and compare system performance, such as Points per Second (PPS).

PPS = (FoV x Refresh Rate x Number of Returns)/(Horizontal Resolution x Vertical Resolution)

Let’s explore each of the factors that are considered within the PPS metric:

Field-of-View (FoV)

In the past, long-range LiDAR customers have typically set the vertical FoV to match the largest road slopes and highest objects (e.g. vertical overhangs) that need to be detected and navigated while setting the horizontal FoV for the number of lanes that need to be seen. For a short-range LiDAR, FoV requirements are typically tailored to the desired form-factor for the vehicle with 360 degrees of coverage as possible to achieve a cocooning effect, preventing blind spots around the vehicle drip line to ensure pedestrian safety.


Resolution is a difficult metric to compare across systems since it is not uniformly reported. With most scanning technologies LiDAR returns start to diverge at a long distance, so achieving and maintaining resolution at range becomes difficult. To overcome this, some systems promote ‘regions of interest’ (ROIs) where overlapping beams of light are diverted into a small region and spatial resolution enhancement techniques are used to obtain temporarily higher resolution within the ROI. The reality is that this increase comes with a severe tradeoff in performance parameters in the rest of the FoV, endangering safety which should never be compromised. We advocate for high angular resolution that can be maintained uniformly and consistently across the required FoV, while being power efficient.

Refresh Rate

The industry, especially for automotive series production programs, is converging on higher refresh rates as standard, based on first-hand experience from driving data collected over the past few years and facing challenges with the previous 10 hertz standard set by rotating LiDARs. Higher refresh rates of 20 hertz or more are becoming the norm for both ADAS and AV applications, as ODDs (operational design domains) expand enabling operation at higher speeds.

Why is Points Per Second the right metric?  Data in the form of returned ‘points’ translate to richness of the sensor output, which in turn translates to the level of confidence that the perception systems require in order to maneuver safely. For a given range, PPS encompasses the tradeoffs between FoV, refresh rate and resolution at a given range elegantly and can be used to compare similar systems. PPS will lead to other derived utility metrics such as PPS/Dollar and PPS/Watt that will represent better ways for customers to holistically compare product performance.

The advantages of LiDAR that utilizes global shutter flash technology – such as the system under development at Sense Photonics – will always deliver superior 3D data over systems using scanning technology.

While any sensor selected for an automotive production program will also need to meet the customer’s requirements for size, weight, power, cost, cooling and compliance (SwaP-C3), the LiDAR industry’s first priority should be establishing a consistent metric for performance.

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