Traffic state estimation on highway: A comprehensive survey
Traffic state estimation (TSE) refers to the process of the inference of traffic state variables
(ie, flow, density, speed and other equivalent variables) on road segments using partially …
(ie, flow, density, speed and other equivalent variables) on road segments using partially …
Traffic state estimation and uncertainty quantification based on heterogeneous data sources: A three detector approach
W Deng, H Lei, X Zhou - Transportation Research Part B: Methodological, 2013 - Elsevier
This study focuses on how to use multiple data sources, including loop detector counts, AVI
Bluetooth travel time readings and GPS location samples, to estimate macroscopic traffic …
Bluetooth travel time readings and GPS location samples, to estimate macroscopic traffic …
Traffic signal control with connected vehicles
The operation of traffic signals is currently limited by the data available from traditional point
sensors. Point detectors can provide only limited vehicle information at a fixed location. The …
sensors. Point detectors can provide only limited vehicle information at a fixed location. The …
Hybrid machine learning algorithm and statistical time series model for network-wide traffic forecast
T Ma, C Antoniou, T Toledo - Transportation Research Part C: Emerging …, 2020 - Elsevier
We propose a novel approach for network-wide traffic state prediction where the statistical
time series model ARIMA is used to postprocess the residuals out of the fundamental …
time series model ARIMA is used to postprocess the residuals out of the fundamental …
Smartphone-based vehicle telematics: A ten-year anniversary
Just as it has irrevocably reshaped social life, the fast growth of smartphone ownership is
now beginning to revolutionize the driving experience and change how we think about …
now beginning to revolutionize the driving experience and change how we think about …
PAMSCOD: Platoon-based arterial multi-modal signal control with online data
A unified platoon-based mathematical formulation called PAMSCOD is presented to perform
arterial (network) traffic signal control while considering multiple travel modes in a vehicle-to …
arterial (network) traffic signal control while considering multiple travel modes in a vehicle-to …
Real time queue length estimation for signalized intersections using travel times from mobile sensors
We study how to estimate real time queue lengths at signalized intersections using
intersection travel times collected from mobile traffic sensors. The estimation is based on the …
intersection travel times collected from mobile traffic sensors. The estimation is based on the …
Short-term speed predictions exploiting big data on large urban road networks
Big data from floating cars supply a frequent, ubiquitous sampling of traffic conditions on the
road network and provide great opportunities for enhanced short-term traffic predictions …
road network and provide great opportunities for enhanced short-term traffic predictions …
Physics-informed deep learning for traffic state estimation: Illustrations with LWR and CTM models
We present a physics-informed deep learning (PIDL) approach to tackle the challenge of
data sparsity and sensor noise in traffic state estimation (TSE). PIDL strengthens a deep …
data sparsity and sensor noise in traffic state estimation (TSE). PIDL strengthens a deep …
Real-time Lagrangian traffic state estimator for freeways
Y Yuan, JWC Van Lint, RE Wilson… - IEEE Transactions …, 2012 - ieeexplore.ieee.org
Freeway traffic state estimation and prediction are central components in real-time traffic
management and information applications. Model-based traffic state estimators consist of a …
management and information applications. Model-based traffic state estimators consist of a …