There are approximately 40,000 deaths and 2.4 million injuries in the U.S. every year on the roads. Car crashes are the leading cause of death for teens and young adults, and remain among the leading causes of death across much of the lifespan. We accept these numbers in a way we would never tolerate from any other form of transportation. Speeding, alcohol impairment and distracted driving are the largest contributors. We want to make that number zero, and Autonomous Vehicles (AVs) are part of that plan. AVs never drive distracted and are designed to obey speed limits and traffic laws.

But not all AV technology is created equal. Sensors are the eyes and ears of a self-driving system, and providers have taken sharply divergent approaches.

As we’ve evaluated various systems, we’ve come to a conclusion: To meet our safety standards, autonomous vehicles must have a multi-sensor approach before we allow them on the Lyft platform.

To be clear, this policy applies to fully driverless vehicles operating on the Lyft platform, not to driver-assistance features used by human drivers. If you drive on Lyft and use a driver-assist technology in your own vehicle, this policy does not affect you.

Today, we’re updating our AV Partner Safety Evaluation Framework to reflect this, requiring any autonomous vehicle operating on the Lyft platform to implement a multi-modal redundant perception system with sensor diversity. Some AV systems use multiple, overlapping sensor types — including cameras, radar and LiDAR — so that if one fails or is temporarily impaired, the vehicle can continue to operate safely.

Other sensor architectures rely on a single sensor type, and each has limitations specific to that technology. For instance, cameras can be blinded by glare, fog, and lens occlusion. Radar struggles with stationary objects. LiDAR can be degraded by heavy precipitation. If the vehicle encounters environmental conditions that affect that single type of sensor, all sensors could be impaired at the same time, leaving the AV without adequate perception.

Much of the industry knows redundancy across multiple dimensions is critical, and we believe sensors that perceive the world in different ways are central to that. The safety net only works if the systems aren’t vulnerable to the same problems at the same time. We also recognize that more sensors alone aren’t enough — the software integrating that data has to work well, too. The good news is that the neural networks processing multi-sensor inputs are improving faster than the failure points of any single sensor type are being resolved. That’s what makes multi-modal perception the right standard today.

This isn’t a permanent verdict on a single-sensor approach. It reflects where the technology stands today and where the engineering and safety evidence currently points. AI and sensor technology are advancing fast, and we will revisit this policy as the landscape evolves, which may include:

• When safety data shows single-sensor systems perform comparably to established multi-modal architectures.
• When the single-sensor AV system being considered meets a standard set by a credible authority, such as NHTSA, for fully driverless operations.

We understand that an autonomous vehicle is an incredible feat of engineering, and the industry is moving fast. Based on what we’re seeing so far, we’re optimistic that single-sensor systems will improve and be helpful for bringing down costs, improving speed to market, and advancing technological innovation. As autonomous vehicle technology evolves, our standards will evolve with it, and we will continue to publish these updates openly.

AVs, done right, have the potential to be extraordinarily safe. That’s a big reason why we’re adding them to our platform. As we do so, we have a responsibility to carefully select and onboard the best technology available—and to be transparent about the bar we’re setting. And AVs are just one part of our relentless commitment to safety. From features built into the Lyft app to programs like Lyft Teen, we’re working on every front to make roads safer for drivers and riders alike.

The next time you get in a vehicle on the Lyft network, you can rest assured our focus on safety continues, no matter what the vehicle or mode of transportation.

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