[PDF] Top 20 Freeway traffic estimation within particle filtering framework
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Freeway traffic estimation within particle filtering framework
... for traffic flow estimation, the Unscented Kalman filter (UKF) (Julier and Uhlmann, 2004; Wan and van der Merwe, ...derivative-free estimation method, that has proven to outperform the ...the ... See full document
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Brief paper: Freeway traffic estimation within particle filtering framework
... the freeway traffic flow estimation within Bayesian recursive ...A particle filter is developed using traffic and observation models with aggregated ...The traffic is ... See full document
8
Autonomous crowds tracking with box particle filtering and convolution particle filtering
... CPF framework is that it implicitly resolves the data association ...the estimation of the clutter and measurement rates when only the kinematic states and extent parameters are of ... See full document
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Vehicle density estimation of freeway traffic with unknown boundary demand-supply : an IMM approach
... of freeway traffic with filtering have been extensively studied in the past two ...macroscopic traffic flow model, METANET. A particle filter (PF) is developed in [2] using the extended ... See full document
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Probabilty hypothesis density filtering for real-time traffic state estimation and prediction
... the Particle Filter (PF), especially in the way the measurement origin uncertainty is dealt ...PHD filtering equation, with the state estimate (and its covariance) easily ...general framework for the ... See full document
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Number of Vehicles and Travel Time Estimation on Urban Traffic Network using Bayesian Network Model and Particle Filtering
... to separate the EEG signal from the estimation of the overlapping artifact projection in the EEG electrode placed on the scalp with assumption that the statistical source signal is independent. The ICA retains ... See full document
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The Development of Maximum Likelihood Estimation Approaches for Adaptive Estimation of Free Speed and Critical Density in Vehicle Freeways
... used particle methods for the filter derivatives is quadratic in the number of ...varying traffic parameters in different conditions and the invariant distribution of the missing ...two traffic field ... See full document
12
Modelling freeway networks by hybrid stochastic models
... aggregated traffic: flow, speed, and density (for recent surveys, see [3], [5], [6], [7], [4], ...the traffic dynamics, less for traffic state estimation and ...of traffic states with ... See full document
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Audiovisual Head Orientation Estimation with Particle Filtering in Multisensor Scenarios
... pose estimation of individuals in environments equipped with multiple cameras and microphones, such as SmartRooms or automatic video ...of particle filters as a unified framework for the ... See full document
12
Hybrid stochastic framework for freeway traffic flow modelling
... lanes, traffic modes (free flow, synchronized, congested, jammed) and external conditions like ...The traffic dynamics is described in this model by macroscopic variables, ...the traffic as a fluid ... See full document
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An unscented Kalman filter for freeway traffic estimation
... the freeway traffic flow estimation and com- pares its performance with respect to a parti- cle ...Kalman filtering is a promising method for traffic flow estimation, re- quiring ... See full document
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Parallelized particle filtering for freeway traffic state tracking
... parallelized particle filters for state tracking (estimation) of freeway traffic ...networks. Particle filters can accurately solve the state estimation problem for general ... See full document
8
A particle filter for freeway traffic estimation
... flow estimation problem for the purposes of on-line traffic prediction, mode detection and ramp-metering ...the estimation problem is given within the Bayesian recursive ...A particle filter (PF) ... See full document
6
Traffic State Estimation via a Particle Filter with Compressive Sensing and Historical Traffic Data
... Bayesian framework, deriving the a posterior distributions and marginal likelihood that are optimised using an RVM type ...state estimation accuracy without a significant increase in computation ... See full document
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Sequential estimation of intrinsic activity and synaptic input in single neurons by particle filtering with optimal importance density
... Kalman filtering) have been used in other recent contributions to similar problems; see ...the estimation accuracy for a given budget of ...fits within the framework of our PF-based ... See full document
22
Urban traffic state estimation & prediction
... urban traffic network and yield both traffic state estimations and ...INRIX Traffic (2016), in which data from adjacent links are considered informative for the current and future state of other ... See full document
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Data- and expert-driven rule induction and filtering framework for functional interpretation and description of gene sets
... the framework presented in this ...without filtering procedure applied, set S02 is a standard method with applied filtering, set S03 applies fil- tering using UTA approach, and set S04 proposes the ... See full document
14
Genetic Algorithm Sequential Monte Carlo Methods For Stochastic Volatility And Parameter Estimation
... We propose a state and parameter estimating particle filter that has a real coded genetic algorithm (RGA) layer. The RGA layer replaces the resampling method in the particle filter. Park, Hwang, Rou and Kim ... See full document
6
Adaptive Blind Multiuser Detection over Flat Fast Fading Channels Using Particle Filtering
... of particle filtering, the adopted importance function is known as optimum in the sense that minimizes the variance of the ...above particle fil- tering procedure suffers from particle ... See full document
12
A Practical Target Tracking Technique in Sensor Network Using Clustering Algorithm
... weightings. Particle filter- ing can be arranged to process the nonlinear and non- Gaussian systems, and it has become an important alter- native to the extended Kalman filter (EKF) ...initialization, ... See full document
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