Ride-sharing apps like Uber or Lyft optimize driver routing using algorithms and real-time data. These systems analyze various factors, including current traffic conditions, geographical locations, and user demand, to determine the most efficient routes for drivers. Additionally, the apps leverage geolocation technology to match passengers with nearby drivers swiftly. Machine learning techniques continuously improve the routing accuracy based on historical ride data, ensuring quicker pick-ups and reduced wait times for users, thus enhancing overall customer satisfaction.