Traffic forecasting in complex urban networks: Leveraging big data and machine learning
Accurate network-wide real time traffic forecasting is essential for next generation smart
cities. In this context, we study a novel and complex traffic data set and explore the potential …
cities. In this context, we study a novel and complex traffic data set and explore the potential …
Topology-regularized universal vector autoregression for traffic forecasting in large urban areas
Autonomous vehicles are soon to become ubiquitous in large urban areas, encompassing
cities, suburbs and vast highway networks. In turn, this will bring new challenges to the …
cities, suburbs and vast highway networks. In turn, this will bring new challenges to the …
A Superposition Assessment Framework of Multi-Source Traffic Risks for Mega-Events Using Risk Field Model and Time-Series Generative Adversarial Networks
In this study, a novel traffic risk assessment framework of mega-events that integrate risk
field and deep learning is proposed. Considering the inherent difference of different traffic …
field and deep learning is proposed. Considering the inherent difference of different traffic …
[HTML][HTML] Travel time estimation using freeway point detector data based on evolving fuzzy neural inference system
Travel time is an important measurement used to evaluate the extent of congestion within
road networks. This paper presents a new method to estimate the travel time based on an …
road networks. This paper presents a new method to estimate the travel time based on an …
A stochastic microscopic based freeway traffic state and spatial-temporal pattern prediction in a connected vehicle environment
Traffic state prediction forms the basis for effective and efficient traffic control and
management strategies. A model-based traffic state prediction approach based on a …
management strategies. A model-based traffic state prediction approach based on a …
[HTML][HTML] Predicting subway passenger flows under different traffic conditions
Passenger flow prediction is important for the operation, management, efficiency, and
reliability of urban rail transit (subway) system. Here, we employ the large-scale subway …
reliability of urban rail transit (subway) system. Here, we employ the large-scale subway …
Evolution regularity mining and gating control method of urban recurrent traffic congestion: a literature review
C Ma, J Zhou, X Xu, J Xu - Journal of Advanced Transportation, 2020 - Wiley Online Library
To understand the status quo of urban recurrent traffic congestion, the current results of
recurrent traffic congestion, and gating control are reviewed from three aspects: traffic …
recurrent traffic congestion, and gating control are reviewed from three aspects: traffic …
Compact modeling and corner analysis of spintronic memristor
Y Chen, X Wang - 2009 IEEE/ACM International Symposium on …, 2009 - ieeexplore.ieee.org
The 4 th fundamental circuit elements-memristor received significant attentions after a real
device was recently demonstrated for the first time. Besides the solid-state thin film …
device was recently demonstrated for the first time. Besides the solid-state thin film …
Bayesian traffic state estimation using extended floating car data
Traffic state estimation is a challenging task due to the collection of sparse and noisy
measurements from specific points of the traffic network. The emergence of Connected and …
measurements from specific points of the traffic network. The emergence of Connected and …
Towards real-time density estimation using vehicle-to-vehicle communications
Traffic state estimation is a fundamental task of Intelligent Transportation Systems (ITS).
Recent advances in sensor technology and emerging computer and vehicular …
Recent advances in sensor technology and emerging computer and vehicular …