Beijing Didi Infinity Technology and Development Co., Ltd.

Xinqi Bao

Zheng Wang

Shujuan Sun

The present disclosure relates to methods and systems for determining an estimated time of arrival (ETA). The methods may include obtaining feature data related to an on-demand service order; obtain a parallel computing framework; determining a global ETA model based on the feature data and the parallel computing framework; and determining an ETA for a target route based on the global ETA model.

Systems and methods for determining estimated time of arrival

A method for determining an ETA relating to a target route is provided. The method includes obtaining, a target route associated with a user; determining characteristic data relating to the target route, the characteristic data including first feature data corresponding to at least a portion of the target route; obtaining an estimation model, the estimation model including a first sub-model and a second sub-model; determining first cell state data and first hidden state data based on the first feature data and the first sub-model; determining a first vector based on the first cell state data and the first hidden state data; determining second cell state data and second hidden state data based on the first vector and the second sub-model; and determining an ETA relating to the target route based on the second cell state data and the second hidden state data.

Methods and systems for estimating time of arrival

Systems and methods for processing at least one service request for an on-demand service are provided. The systems may perform the methods to obtain a plurality of example service orders, each example service order of the plurality of example service orders may include a feature associated with a section of a plurality of sections of a measurement; cluster the plurality of example service orders into a plurality of subsets of example service orders, the feature of each example service order in a same subset of example service orders may be associated with a same section of the measurement; for each of the plurality of subsets of example service orders, train a first model of estimated time of arrival (first ETA model) using the subset of example service orders; and store structured data in the at least one storage medium encoding the plurality of first ETA models.

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Beijing, China

Xinqi Bao