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spatio-temporal graph convolution

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Jul 6, 2023 · Artificial Intelligence

How Gaode’s ETA System Predicts Arrival Times with Hybrid Spatio‑Temporal GCN

This article explains the architecture, data layers, prediction modules, and deep‑learning framework behind Gaode’s driving ETA service, detailing how static speed profiles, linear models, and the H‑STGCN model combine to forecast travel times and evaluate their accuracy.

ETAGaodedeep learning

0 likes · 12 min read

How Gaode’s ETA System Predicts Arrival Times with Hybrid Spatio‑Temporal GCN

DataFunTalk

Oct 11, 2020 · Artificial Intelligence

Spatio‑Temporal Graph Convolution Networks for Traffic Forecasting: Gaode's HSTGCN Approach

The presentation by Gaode senior algorithm expert Ji Chenguang details a hybrid spatio‑temporal graph convolution network (HSTGCN) that predicts future traffic conditions from massive navigation data, dramatically improving congestion forecasting accuracy and enabling proactive traffic dispatch.

AIETA estimationHSTGCN

0 likes · 10 min read

Spatio‑Temporal Graph Convolution Networks for Traffic Forecasting: Gaode's HSTGCN Approach