System and method for recommending bidding bundle options in bidding-based ridesharing

A system comprising one or more processors and one or more non-transitory computer-readable memories coupled to the one or more processors, the one or more non-transitory computer-readable memories storing instructions that, when executed by the one or more processors, cause the system to perform operations comprising:

• obtaining a price range of a trip request for a rider;
• determining a plurality of trip setting candidates based on the trip request, and a plurality of price candidates based on the price range;
• generating a plurality of bidding bundle option candidates based on a plurality of combinations of the plurality of trip setting candidates and the plurality of price candidates;
• determining, based on a trained machine-learning classifier, a selection probability for the rider to select each of the plurality of bidding bundle option candidates, wherein
• for each of the plurality of bidding bundle option candidates, the trained machine-learning classifier accepts input comprising information of the rider, the bidding bundle option candidate, trip attributes of a hypothetical trip configured based on the bidding bundle option candidate and generates output comprising the selection probability for the rider to select the bidding bundle option candidate;
• and
• ranking the plurality of bidding bundle option candidates based on corresponding probabilities;
• and
• transmitting one or more of the plurality of bidding bundle option candidates with top selection probabilities to a terminal device associated with the rider.

A non-transitory computer-readable storage medium storing instructions that, when executed by one or more processors, cause the one or more processors to perform operations comprising:

• obtaining a price range of a trip request for a rider;
• determining a plurality of trip setting candidates based on the trip request, and a plurality of price candidates based on the price range;
• generating a plurality of bidding bundle option candidates based on a plurality of combinations of the plurality of trip setting candidates and the plurality of price candidates;
• determining, based on a trained machine-learning classifier, a selection probability for the rider to select each of the plurality of bidding bundle option candidates, wherein
• for each of the plurality of bidding bundle option candidates, the trained machine-learning classifier accepts input comprising information of the rider, the bidding bundle option candidate, trip attributes of a hypothetical trip configured based on the bidding bundle option candidate and generates output comprising the selection probability for the rider to select the bidding bundle option candidate;
• and
• ranking the plurality of bidding bundle option candidates based on corresponding probabilities;
• and
• transmitting one or more of the plurality of bidding bundle option candidates with top selection probabilities to a terminal device associated with the rider.