Abstract: Systems and methods for predicting traffic accident location. A method includes: obtaining a plurality of accident records, each accident record is associated with a target user terminal and includes a plurality of locations; determining a plurality of refined accident locations by, for each of the plurality of accident records, operating a first clustering procedure with the corresponding plurality of locations of the target user terminal as inputs of the first clustering procedure and assigning a first result of the first clustering procedure as a refined accident location of the plurality of locations of the target user terminal; and determining at least one accident-prone road section by operating a second clustering procedure with the plurality of refined accident locations corresponding to the plurality of accident records as the inputs of the second clustering procedure.

Abstract: Systems and methods for predicting traffic accident location. A method includes: obtaining a plurality of accident records, each accident record is associated with a target user terminal and includes a plurality of locations; determining a plurality of refined accident locations by, for each of the plurality of accident records, operating a first clustering procedure with the corresponding plurality of locations of the target user terminal as inputs of the first clustering procedure and assigning a first result of the first clustering procedure as a refined accident location of the plurality of locations of the target user terminal; and determining at least one accident-prone road section by operating a second clustering procedure with the plurality of refined accident locations corresponding to the plurality of accident records as the inputs of the second clustering procedure.

Abstract: The present disclosure relates to systems and methods for scheduling service of an on-demand service. The systems may perform the methods to obtain historical service information of the on-demand service associated with a target region; determine a scheduling strategy to schedule service providers to the target region based on the historical service information; determine estimated service information associated with the target region based on the scheduling strategy and the historical service information; determine that the scheduling strategy has a better service providing result than the historical service information; and store the scheduling strategy in at least one storage medium.

Abstract: Systems and methods for predicting traffic accident location. A method includes: obtaining a plurality of accident records, each accident record is associated with a target user terminal and includes a plurality of locations; determining a plurality of refined accident locations by, for each of the plurality of accident records, operating a first clustering procedure with the corresponding plurality of locations of the target user terminal as inputs of the first clustering procedure and assigning a first result of the first clustering procedure as a refined accident location of the plurality of locations of the target user terminal; and determining at least one accident-prone road section by operating a second clustering procedure with the plurality of refined accident locations corresponding to the plurality of accident records as the inputs of the second clustering procedure.

Abstract: Systems and methods for predicting traffic accident location. A method includes: obtaining a plurality of accident records, each accident record is associated with a target user terminal and includes a plurality of locations; determining a plurality of refined accident locations by, for each of the plurality of accident records, operating a first clustering procedure with the corresponding plurality of locations of the target user terminal as inputs of the first clustering procedure and assigning a first result of the first clustering procedure as a refined accident location of the plurality of locations of the target user terminal; and determining at least one accident-prone road section by operating a second clustering procedure with the plurality of refined accident locations corresponding to the plurality of accident records as the inputs of the second clustering procedure.