Change Detection in Partially Observed Large-Scale Traffic Network Data
Intelligent Transportation Systems generate an unprecedented amount of high-dimensional
traffic data. The proper analysis of such data can transform traffic monitoring mechanisms …
traffic data. The proper analysis of such data can transform traffic monitoring mechanisms …
Detecting Traffic Anomalies During Extreme Events via a Temporal Self-Expressive Model
M Nouri, E Konyar, MR Gahrooeri… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Motivated by rapid urbanization and increasing natural hazards, this study aims to develop a
data-driven method for detecting urban traffic anomalies during extreme events. Past …
data-driven method for detecting urban traffic anomalies during extreme events. Past …
SE-MAConvLSTM: A deep learning framework for short-term traffic flow prediction combining Squeeze-and-Excitation Network and Multi-Attention Convolutional …
R Zhu, J Tang, X He, X Zhou, X Huang, F Wu, S Chen - PloS one, 2024 - journals.plos.org
Traffic flow prediction is an important part of transportation management and planning. For
example, accurate demand prediction of taxis and online car-hailing can reduce the waste of …
example, accurate demand prediction of taxis and online car-hailing can reduce the waste of …
Multilevel Monitoring System for Road Networks: Anomaly Detection at the Network and Road-Segment Levels
This study introduces a novel multilevel disruption detection method for road networks. The
proposed monitoring and disruption detection method can detect disruptions at both the …
proposed monitoring and disruption detection method can detect disruptions at both the …
Research on Flight delay Prediction based on Multi-Model Fusion
C Mang, Y Chen - 2020 IEEE 5th Information Technology and …, 2020 - ieeexplore.ieee.org
With the introduction of the concept of “Intelligent Transport”, in order to meet the needs of
high accuracy of flight delay prediction in the transportation industry in the current stage, a …
high accuracy of flight delay prediction in the transportation industry in the current stage, a …
Early Detection of Freeway Traffic Anomalies With a Cycle-Consistent Bidirectional Generative Adversarial Network
M Nouri, M Ilbeigi - Authorea Preprints, 2024 - techrxiv.org
Rapidly identifying anomalous events on freeways can significantly improve emergency
response time and reduce congestion. However, the unpredictable nature of these incidents …
response time and reduce congestion. However, the unpredictable nature of these incidents …
A Self-Imputing Deep Multitask Sequence Model for Traffic Disruption Detection in Extreme Conditions
M Nouri, M Ilbeigi - Authorea Preprints, 2024 - techrxiv.org
Abnormal traffic patterns caused by extreme events have the potential to disrupt traffic flow
on large regions of urban road networks. Timely and reliable detection of such disruptions is …
on large regions of urban road networks. Timely and reliable detection of such disruptions is …
A Review Study of Incident Detection Algorithms with Performance Index Parameter
K Puangnak, S Chivapreecha - 2019 16th International …, 2019 - ieeexplore.ieee.org
This paper proposes a review study of the current incident detection algorithms that can
work with two-position traffic data measurements consisting of upstream and downstream …
work with two-position traffic data measurements consisting of upstream and downstream …