Research on travel time prediction model of freeway based on gradient boosting decision tree
To improve the prediction accuracy of traffic flow, a travel time prediction model based on
gradient boosting decision tree (GBDT) is proposed. In order to test the applicability of …
gradient boosting decision tree (GBDT) is proposed. In order to test the applicability of …
Travel time forecasting and dynamic origin-destination estimation for freeways based on bluetooth traffic monitoring
Traditional technologies, such as inductive loop detectors, do not usually produce
measurements of the quality required by real-time applications. Therefore, one wonders …
measurements of the quality required by real-time applications. Therefore, one wonders …
Vehicle classification and speed estimation using combined passive infrared/ultrasonic sensors
In this paper, a new sensing device that can simultaneously monitor traffic congestion and
urban flash floods is presented. This sensing device is based on the combination of passive …
urban flash floods is presented. This sensing device is based on the combination of passive …
Virtual trip lines for distributed privacy-preserving traffic monitoring
Automotive traffic monitoring using probe vehicles with Global Positioning System receivers
promises significant improvements in cost, coverage, and accuracy. Current approaches …
promises significant improvements in cost, coverage, and accuracy. Current approaches …
Incorporation of Lagrangian measurements in freeway traffic state estimation
JC Herrera, AM Bayen - Transportation Research Part B: Methodological, 2010 - Elsevier
Cell-phones equipped with a global positioning system (GPS) provide new opportunities for
location-based services and traffic estimation. When traveling on-board vehicles, these …
location-based services and traffic estimation. When traveling on-board vehicles, these …
New Bayesian combination method for short-term traffic flow forecasting
The Bayesian combination method (BCM) proposed by Petridis et al.(2001) is an integrated
method that can effectively improve the predictions of single predictors. However, research …
method that can effectively improve the predictions of single predictors. However, research …
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 …
Real-time joint traffic state and model parameter estimation on freeways with fixed sensors and connected vehicles: State-of-the-art overview, methods, and case …
Y Wang, M Zhao, X Yu, Y Hu, P Zheng, W Hua… - … Research Part C …, 2022 - Elsevier
This paper addresses real-time joint traffic state and model parameter estimation on
freeways using data from fixed sensors and connected vehicles. It investigates how the …
freeways using data from fixed sensors and connected vehicles. It investigates how the …
Traffic congestion and travel time prediction based on historical congestion maps and identification of consensual days
N Chiabaut, R Faitout - Transportation Research Part C: Emerging …, 2021 - Elsevier
In this paper, a new practice-ready method for the real-time estimation of traffic conditions
and travel times on highways is introduced. First, after a principal component analysis …
and travel times on highways is introduced. First, after a principal component analysis …
Traffic signal optimization for partially observable traffic system and low penetration rate of connected vehicles
Observability and controllability are two critical requirements for a partially observable
transportation system. This paper proposes a stepwise signal optimization framework with …
transportation system. This paper proposes a stepwise signal optimization framework with …