3 results about "Seating capacity" patented technology

The application provides a seat protection method, device, electronic equipment and computer readable medium. The method receives a seat protection request. If the trigger cause of the seat protection request is to change the passenger reservation record of a specific passenger, the method reads flight data, passenger reservation record data, seat protection rule data and seat map data in response to the seat protection request. Then, according to the original seat data corresponding to the original seat of the specific passenger in the passenger reservation record and the seat protection rule data, the specific passenger is allocated a new seat on the target flight. Since the new seat map of the source flight and the new seat map of the target flight are not regenerated when the passenger reservation record of a single specific passenger is changed, the seat protection process is simpler than the existing seat protection process, and the change of the seats booked by the passengers except the specific passenger due to the regeneration of the new seat map is avoided, thereby improving the processing efficiency of the seat protection request and the passenger experience.

This invention relates to a dynamic matching method and system for ride-hailing, belonging to the field of dynamic matching technology. It utilizes a ride-hailing request clustering algorithm to rationally divide dispersed ride-hailing request sets based on the starting location and destination of the requests, effectively reducing the scale of subsequent processing and thus improving matching efficiency. By employing a vehicle selection algorithm, based on the clustering results and considering constraints such as vehicle seating capacity, driving direction, and passenger waiting time, it selects a set of vehicles nearby that can provide services for each request set, avoiding invalid matching. Based on master-slave pricing matching, driver-passenger matching is constructed as a multi-round iterative dynamic process. In each iteration, the ride-hailing service adjusts its pricing based on the matching status, and passengers reselect vehicles based on the new price and service information. This continuous adjustment of strategies gradually approaches the optimal matching state, ultimately maximizing passenger utility while ensuring that the driver's revenue demands are reasonably met, achieving an optimal balance of interests between the driver and passenger.