[HTML][HTML] Traffic state estimation from vehicle trajectories with anisotropic Gaussian processes
Accurately monitoring road traffic state is crucial for various applications, including travel
time prediction, traffic control, and traffic safety. However, the lack of sensors often results in …
time prediction, traffic control, and traffic safety. However, the lack of sensors often results in …
Estimating the posterior predictive distribution of the traffic density in multi-lane highways using spacing measurements
Traffic state estimation (TSE) is an important task for traffic management, however it can be
challenging due to the sparse deployment of traffic sensors in the network. The …
challenging due to the sparse deployment of traffic sensors in the network. The …
Traffic State Estimation and Uncertainty Quantification at Signalized Intersections with Low Penetration Rate Vehicle Trajectory Data
This paper studies the traffic state estimation problem at signalized intersections with low
penetration rate vehicle trajectory data. While many existing studies have proposed different …
penetration rate vehicle trajectory data. While many existing studies have proposed different …
Learning traffic flow dynamics using random fields
This paper presents a mesoscopic traffic flow model that explicitly describes the spatio-
temporal evolution of the probability distributions of vehicle trajectories. The dynamics are …
temporal evolution of the probability distributions of vehicle trajectories. The dynamics are …
A streaming-data-driven method for freeway traffic state estimation using probe vehicle trajectory data
Y Han, M Zhang, Y Guo, L Zhang - Physica A: Statistical Mechanics and its …, 2022 - Elsevier
This paper proposes a streaming-data-driven method for freeway traffic state estimation
based on probe vehicle trajectory data, which are represented by a series of timestamps …
based on probe vehicle trajectory data, which are represented by a series of timestamps …
Network-wide traffic state estimation using loop detector and floating car data
Y Yuan, H Van Lint… - Journal of Intelligent …, 2014 - Taylor & Francis
In real-time traffic management and intelligent transportation systems (ITS) applications, an
accurate picture of the prevailing traffic state in terms of speeds and densities is critical, for …
accurate picture of the prevailing traffic state in terms of speeds and densities is critical, for …
Autonomous Vehicles as a Sensor: Simulating Data Collection Process
Urban traffic state estimation is pivotal in furnishing precise and reliable insights into traffic
flow characteristics, thereby enabling efficient traffic management. Traditional traffic …
flow characteristics, thereby enabling efficient traffic management. Traditional traffic …
Probabilistic traffic density estimation using measurements from Unmanned Aerial Vehicles
Y Englezou, S Timotheou… - … on Unmanned Aircraft …, 2022 - ieeexplore.ieee.org
Traffic state estimation (TSE) is an important task for traffic management, however it can be
challenging due to the sparse deployment of traffic sensors in the network. The …
challenging due to the sparse deployment of traffic sensors in the network. The …
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 …
Highway traffic state estimation with mixed connected and conventional vehicles using speed measurements
N Bekiaris-Liberis, C Roncoli… - 2015 IEEE 18th …, 2015 - ieeexplore.ieee.org
We present a macroscopic model-based approach for estimation of the total density and flow
of vehicles, for the case of" mixed" traffic, ie, traffic comprising both ordinary and connected …
of vehicles, for the case of" mixed" traffic, ie, traffic comprising both ordinary and connected …