Attentive Crowd Flow Machines

09/01/2018
by   Lingbo Liu, et al.
0

Traffic flow prediction is crucial for urban traffic management and public safety. Its key challenges lie in how to adaptively integrate the various factors that affect the flow changes. In this paper, we propose a unified neural network module to address this problem, called Attentive Crowd Flow Machine (ACFM), which is able to infer the evolution of the crowd flow by learning dynamic representations of temporally-varying data with an attention mechanism. Specifically, the ACFM is composed of two progressive ConvLSTM units connected with a convolutional layer for spatial weight prediction. The first LSTM takes the sequential flow density representation as input and generates a hidden state at each time-step for attention map inference, while the second LSTM aims at learning the effective spatial-temporal feature expression from attentionally weighted crowd flow features. Based on the ACFM, we further build a deep architecture with the application to citywide crowd flow prediction, which naturally incorporates the sequential and periodic data as well as other external influences. Extensive experiments on two standard benchmarks (i.e., crowd flow in Beijing and New York City) show that the proposed method achieves significant improvements over the state-of-the-art methods.

READ FULL TEXT
research
09/02/2019

ACFM: A Dynamic Spatial-Temporal Network for Traffic Prediction

As a crucial component in intelligent transportation systems, crowd flow...
research
02/22/2020

Interpretable Crowd Flow Prediction with Spatial-Temporal Self-Attention

Crowd flow prediction has been increasingly investigated in intelligent ...
research
10/01/2016

Deep Spatio-Temporal Residual Networks for Citywide Crowd Flows Prediction

Forecasting the flow of crowds is of great importance to traffic managem...
research
11/16/2019

VLUC: An Empirical Benchmark for Video-Like Urban Computing on Citywide Crowd and Traffic Prediction

Nowadays, massive urban human mobility data are being generated from mob...
research
01/18/2021

Modeling Heterogeneous Relations across Multiple Modes for Potential Crowd Flow Prediction

Potential crowd flow prediction for new planned transportation sites is ...
research
06/07/2023

UCTB: An Urban Computing Tool Box for Spatiotemporal Crowd Flow Prediction

Spatiotemporal crowd flow prediction is one of the key technologies in s...
research
12/08/2021

PRNet: A Periodic Residual Learning Network for Crowd Flow Forecasting

Crowd flow forecasting, e.g., predicting the crowds entering or leaving ...

Please sign up or login with your details

Forgot password? Click here to reset