To better match drivers to riders in our ridesharing application, we revised
Lyft's core matching algorithm. We use a novel online reinforcement learning
approach that estimates the future earnings of drivers in real time and use
this information to find more efficient matches. This change was the first
documented implementation of a ridesharing matching algorithm that can learn
and improve in real time. We evaluated the new approach during weeks of
switchback experimentation in most Lyft markets, and estimated how it benefited
drivers, riders, and the platform. In particular, it enabled our drivers to
serve millions of additional riders each year, leading to more than $30 million
per year in incremental revenue. Lyft rolled out the algorithm globally in
2021.

为了更好地匹配驾驶员和乘客，我们改进了 Lyft 的核心匹配算法，使用在线强化学习方法实时估计驾驶员的未来收益，以寻找更高效的匹配。这是首个能够实时学习和改进的拼车匹配算法的记录实施，通过数周的实验评估，它使得我们的驾驶员能够每年为数百万额外的乘客提供服务，从而获得每年超过 3000 万美元的增量收入。Lyft 在 2021 年全球推广了这种算法。