Safety critical event prediction through unified analysis of driver and vehicle volatilities: Application of deep learning methods
Transportation safety is highly correlated with driving behavior, especially human error
playing a key role in a large portion of crashes. Modern instrumentation and computational …
playing a key role in a large portion of crashes. Modern instrumentation and computational …
Traffic congestion-aware graph-based vehicle rerouting framework from aerial imagery
In digital era, being stranded from very basic telecommunication protocols and internet
makes vehicle rerouting-like crucial tools more difficult or even impossible, especially in …
makes vehicle rerouting-like crucial tools more difficult or even impossible, especially in …
MF-TCPV: a machine learning and fuzzy comprehensive evaluation-based framework for traffic congestion prediction and visualization
L Li, H Lin, J Wan, Z Ma, H Wang - IEEE Access, 2020 - ieeexplore.ieee.org
A framework for traffic congestion prediction and visualization based on machine learning
and Fuzzy Comprehensive Evaluation named MF-TCPV is proposed in this paper. The …
and Fuzzy Comprehensive Evaluation named MF-TCPV is proposed in this paper. The …
Recognition of lane-changing behaviour with machine learning methods at freeway off-ramps
T Xu, Z Zhang, X Wu, L Qi, Y Han - Physica A: Statistical Mechanics and its …, 2021 - Elsevier
Crashes are occurred frequently at freeway off-ramps due to improper lane-changing (LC)
behaviours. The LC behaviour is the main cause of freeway off-ramp crashes. It is important …
behaviours. The LC behaviour is the main cause of freeway off-ramp crashes. It is important …
Traffic congestion classification using GAN-Based synthetic data augmentation and a novel 5-layer convolutional neural network model
Private automobiles are still a widely prevalent mode of transportation. Subsequently, traffic
congestion on the roads has been more frequent and severe with the continuous rise in the …
congestion on the roads has been more frequent and severe with the continuous rise in the …
PFFN: Periodic feature-folding deep neural network for traffic condition forecasting
T Wang, Z Zhang, KL Tsui - IEEE Internet of Things Journal, 2023 - ieeexplore.ieee.org
Accurate forecasting of traffic conditions is critical for improving urban transportation safety,
stability, and efficiency. It is challenging to produce explicit traffic forecasts due to complex …
stability, and efficiency. It is challenging to produce explicit traffic forecasts due to complex …
Performance of fine-tuning convolutional neural networks for HEP-2 image classification
The search for anti-nucleus antibodies (ANA) represents a fundamental step in the
diagnosis of autoimmune diseases. The test considered the gold standard for ANA research …
diagnosis of autoimmune diseases. The test considered the gold standard for ANA research …
A study on autonomous intersection management: planning-based strategy improved by convolutional neural network
The development and application of autonomous vehicles bring great changes to urban
traffic management and control. As one of the bottlenecks to improve transportation …
traffic management and control. As one of the bottlenecks to improve transportation …
Highway traffic congestion detection and evaluation based on deep learning techniques
Y Liu, Z Cai, H Dou - Soft Computing, 2023 - Springer
The rapid development of urbanization in China has contributed to traffic events, such as
traffic accidents and delays. It is difficult to detect and resolve highway traffic congestion in a …
traffic accidents and delays. It is difficult to detect and resolve highway traffic congestion in a …
Traffic behavior recognition from traffic videos under occlusion condition: a Kalman filter approach
Real-time traffic data at intersections is significant for development of adaptive traffic light
control systems. Sensors such as infrared radiation and GPS are not capable of providing …
control systems. Sensors such as infrared radiation and GPS are not capable of providing …