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

Amap Tech

Sep 24, 2020 · Artificial Intelligence

Hybrid Spatio‑Temporal Graph Convolutional Network for Precise Traffic Prediction

At the 2020 Yunqi Conference, Amap’s senior algorithm expert presented the Hybrid Spatio‑Temporal Graph Convolutional Network, which leverages massive real‑time navigation data to estimate future traffic flow, transform it into travel‑time features, and outperform prior models, enabling proactive congestion avoidance and dynamic traffic‑scheduling for millions of users.

AIHSTGCNSmart Mobility

0 likes · 11 min read

Hybrid Spatio‑Temporal Graph Convolutional Network for Precise Traffic Prediction