Naiwei Lu^1,*, Honghao Wang¹, Kai Wang¹, Yang Liu²

CMES-Computer Modeling in Engineering & Sciences, Vol.127, No.1, pp. 345-360, 2021, DOI:10.32604/cmes.2021.013792 - 30 March 2021

Abstract The steadily growing traffic load has resulted in lots of bridge collapse events over the past decades, especially for short-to-medium span bridges. This study investigated probabilistic and dynamic traffic load effects on short-to-medium span bridges using practical heavy traffic data in China. Mathematical formulations for traffic-bridge coupled vibration and probabilistic extrapolation were derived. A framework for extrapolating probabilistic and dynamic traffic load effect was presented to conduct an efficient and accurate extrapolation. An equivalent dynamic wheel load model was demonstrated to be feasible for short-to-medium span bridges. Numerical studies of two types of simply-supported bridges… More >

Xijun Zhang^*, Qirui Zhang

CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 95-109, 2020, DOI:10.32604/cmes.2020.011013 - 18 September 2020

Abstract According to the time series characteristics of the trajectory history data, we predicted and analyzed the traffic flow. This paper proposed a LSTMXGBoost model based urban road short-term traffic flow prediction in order to analyze and solve the problems of periodicity, stationary and abnormality of time series. It can improve the traffic flow prediction effect, achieve efficient traffic guidance and traffic control. The model combined the characteristics of LSTM (Long Short-Term Memory) network and XGBoost (Extreme Gradient Boosting) algorithms. First, we used the LSTM model that increases dropout layer to train the data set after… More >

Jinyuan Li¹, Hao Li¹, Guorong Cui¹, Yan Kang^{1, *}, Yang Hu¹, Yingnan Zhou²

CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 925-940, 2020, DOI:10.32604/cmc.2020.09903 - 10 June 2020

Abstract With continuous urbanization, cities are undergoing a sharp expansion within the regional space. Due to the high cost, the prediction of regional traffic flow is more difficult to extend to entire urban areas. To address this challenging problem, we present a new deep learning architecture for regional epitaxial traffic flow prediction called GACNet, which predicts traffic flow of surrounding areas based on inflow and outflow information in central area. The method is data-driven, and the spatial relationship of traffic flow is characterized by dynamically transforming traffic information into images through a two-dimensional matrix. We introduce… More >

Yonghua Zhou¹, Xun Yang¹, Chao Mi¹

CMES-Computer Modeling in Engineering & Sciences, Vol.89, No.6, pp. 497-512, 2012, DOI:10.3970/cmes.2012.089.497

Abstract The movements of vehicles equipped with various positioning systems such as global and wireless positioning ones have provided beneficial channels to acquire abundant traffic flow information for total road network. However, not all vehicles are mounted with positioning systems and not all equipped positioning facilities are always active. This paper will address how to estimate the number and the states of unequipped vehicles through a series of observations on equipped ones. The proposed estimation process initiates employing the non-analytical microscopic traffic model for particle filter to estimate the number, positions and speeds of unequipped vehicles… More >

Yonghua Zhou¹, Chao Mi¹, Xun Yang¹

CMES-Computer Modeling in Engineering & Sciences, Vol.86, No.6, pp. 533-550, 2012, DOI:10.3970/cmes.2012.086.533

Abstract The cellular automaton (CA) model for traffic flow describes the restrictive vehicle movements using the distance headway (gap) between two adjacent vehicles. However, the autonomous and synergistic behaviors also exist in the vehicle movements. This paper makes an attempt to propose a microscopic traffic simulation model such that the feedback control behavior during the driving process is incorporated into the CA model. The acceleration, speed holding and deceleration are manipulated by the difference between the gap and the braking reference distance the driver perceives, which is generally observed in the realistic traffic. The braking reference… More >

Yonghua Zhou¹, Chao Mi¹

CMES-Computer Modeling in Engineering & Sciences, Vol.83, No.1, pp. 1-22, 2012, DOI:10.3970/cmes.2012.083.001

Abstract Cellular automata (CAs), model the dynamics of complex systems as the state update of cells restricted from their own neighbors. This paper regards the tempo-spatial constraints as dummy neighborhoods of cells for train movement, such as scheduled movement authority and speed restriction, equivalent to the maximum displacements during the future certain time steps and each time step, respectively. Under the framework of CA modeling, this paper attempts to propose an improved CA model for moving-block railway network which incorporates the tempo-spatial constraints to capture the restrictive, synergistic and autonomous dynamics. We divide the one-dimensional cell More >

Durgesh Vikram¹, Sanjay Mittal², Partha Chakroborty¹

CMES-Computer Modeling in Engineering & Sciences, Vol.79, No.3&4, pp. 237-260, 2011, DOI:10.3970/cmes.2011.079.237

Abstract A stabilized finite element formulation is presented to solve the governing equations for traffic flow. The flow is assumed to be one-dimensional. Both, PW-type (Payne-Whitham) 2-equation models and the LWR-type (Lighthill-Whitham-Richards) 1-equation models are considered. The SUPG (Streamline-Upwind/Petrov-Galerkin) and shock capturing stabilizations are utilized. These stabilizations are sufficient for the 1-equation models. However, an additional stabilization is necessary for the 2-equation models. For the first time, such a stabilization is proposed. It arises from the coupling between the two equations and is termed as IEPG (Inter-Equation/Petrov-Galerkin) stabilization. Two behavioral models are studied: Greenshields' (GS) and Greenberg's… More >