Trajectory Classification for Road Closure Detection Using Bayesian and Deep Learning Approaches

This article investigates how to dynamically identify road closures by classifying vehicle, bicycle, and pedestrian trajectories, addressing sample imbalance and noisy labels with a label‑probability mixture Bayesian model and a deep‑learning image‑encoding pipeline, and compares their experimental results.

Artificial IntelligenceBayesian modelDeep Learning

0 likes · 12 min read

Trajectory Classification for Road Closure Detection Using Bayesian and Deep Learning Approaches

Amap Tech

Oct 16, 2020 · Artificial Intelligence

Trajectory Classification for Road Closure Detection Using Bayesian and Deep Learning Approaches

The paper proposes classifying vehicle, bicycle, and pedestrian trajectories to detect road closures, introducing a probability‑mixture Bayesian model that mitigates label noise and class imbalance through joint feature densities, and a dual‑stream deep‑learning approach encoding trajectories as images, with experiments showing the Bayesian method outperforming the neural network on limited labeled data.

Bayesian modelDeep LearningGPS data

0 likes · 13 min read

Alibaba Cloud Developer

Sep 24, 2019 · Artificial Intelligence

How Semi‑Supervised Deep Learning Detects Road Closures in Real‑Time

Gaode’s engineering team presents a semi‑supervised deep‑learning framework that models road networks, extracts traffic, routing, deviation and heatmap features, and combines LSTM with ResNet to accurately identify dynamic road‑closure events, enabling both offline and real‑time detection with high confidence and business‑aligned validation.

Big DataLSTMResNetSemi-supervised Learning

0 likes · 12 min read

How Semi‑Supervised Deep Learning Detects Road Closures in Real‑Time

Amap Tech

Sep 4, 2019 · Artificial Intelligence

Semi-supervised Deep Learning Solution for Detecting Road Closure Events

Gaode’s semi‑supervised deep‑learning framework combines LSTM and ResNet to analyze 28‑day sequences of 39‑dimensional traffic and planning features, automatically discovering and verifying road‑closure events through a three‑layer pipeline, boosting detection confidence and top‑N accuracy by about ten percent and improving user routing.

LSTMResNetSemi-supervised LearningTraffic analysis

0 likes · 11 min read

Semi-supervised Deep Learning Solution for Detecting Road Closure Events