Waymo announces 50,000 paid robotaxi rides per week

50,000 times/week, 300 times/hour, 5 times/minute... Do you know what these numbers mean?

Recently, self-driving technology company Waymo announced that its robot taxi service Waymo One currently completes more than 50,000 paid trips per week in three cities in the United States, Phoenix, San Francisco and Los Angeles. This service has been implemented in some areas of the above cities around the clock. This shows that the public's acceptance of self-driving taxi services is constantly increasing, from a simple novel experience to a practical travel solution.

50,000 weekly rides means about 300 bookings per hour, 5 per minute, which is a considerable scale of operation. It is foreseeable that as more cities launch autonomous driving fleets and public recognition continues to increase, the scale of operation will further expand.

In 2009, Google spent hundreds of millions of dollars to set up a dedicated team in the field of autonomous driving, which later developed into today's Waymo. Soon after, Silicon Valley technology giants such as Microsoft also launched autonomous driving projects, and traditional car companies such as General Motors, Ford, and Toyota also joined the battle. Various investors have invested heavily in this trillion-dollar track.

There have been radical and optimistic comments that we may see groups of driverless cars on the streets around 2020. However, the reality has not developed in this direction, and the commercialization of driverless cars has been much slower than expected.

The main reason why the progress of autonomous driving lags behind expectations is that the technical challenges are far more severe than imagined. To achieve truly fully autonomous driving, it is necessary to meet extremely high safety and reliability requirements, which requires overcoming multiple complex technical problems including environmental perception, decision-making planning, and behavior control.

For example, teaching a car to recognize traffic lights and drive properly may seem simple, but it actually requires dealing with a variety of abnormal scenarios, including light changes, occlusion, and damaged lights. Furthermore, if there are extreme situations such as construction, accidents, and bad weather, the decision-making system will face even greater challenges. To ensure the safe and reliable operation of the unmanned driving system, it is necessary to repeatedly test various possible extreme situations and accumulate a large amount of real road data in order to gradually improve the system.

Therefore, although autonomous driving has been implemented in specific areas and scenarios at this stage, it still faces huge challenges in order to operate stably in a wider range of complex environments. We are still some distance away from the true autonomous driving era.