scholarly journals A hybrid model for traffic flow and crowd dynamics with random individual properties

2015 ◽  
Vol 12 (2) ◽  
pp. 393-413 ◽  
Author(s):  
Veronika Schleper ◽  
Keyword(s):  
Traffic Flow ◽  
Hybrid Model ◽  
Crowd Dynamics ◽  
Random Individual

scholarly journals SHORT-TERM TRAFFIC FLOW PREDICTION USING A METHODOLOGY BASED ON AUTOREGRESSIVE INTEGRATED MOVING AVERAGE AND GENETIC PROGRAMMING

Transport ◽  
2016 ◽  
Vol 31 (3) ◽  
pp. 343-358 ◽  
Author(s):  
Chengcheng Xu ◽  
Zhibin Li ◽  
Wei Wang
Keyword(s):  
Genetic Programming ◽  
Traffic Flow ◽  
Hybrid Model ◽  
Moving Average ◽  
Arima Model ◽  
Predictive Performance ◽  
Hybrid Models ◽  
Short Term ◽  
Time Intervals ◽  
Autoregressive Integrated Moving Average

The accurate short-term traffic flow forecasting is fundamental to both theoretical and empirical aspects of intelligent transportation systems deployment. This study aimed to develop a simple and effective hybrid model for forecasting traffic volume that combines the AutoRegressive Integrated Moving Average (ARIMA) and the Genetic Programming (GP) models. By combining different models, different aspects of the underlying patterns of traffic flow could be captured. The ARIMA model was used to model the linear component of the traffic flow time series. Then the GP model was applied to capture the nonlinear component by modelling the residuals from the ARIMA model. The hybrid models were fitted for four different time-aggregations: 5, 10, 15, and 20 min. The validations of the proposed hybrid methodology were performed by using traffic data under both typical and atypical conditions from multiple locations on the I-880N freeway in the United States. The results indicated that the hybrid models had better predictive performance than utilizing only ARIMA model for different aggregation time intervals under typical conditions. The Mean Relative Error (MRE) of the hybrid models was found to be from 4.1 to 6.9% for different aggregation time intervals under typical conditions. The predictive performance of the hybrid method was improved with an increase in the aggregation time interval. In addition, the validation results showed that the predictive performance of the hybrid model was also better than that of the ARIMA model under atypical conditions.

scholarly journals A Macro-kinetic Hybrid Model for Traffic Flow on Road Networks

2009 ◽  
Vol 9 (3) ◽  
pp. 238-252 ◽  
Author(s):  
M. Herty ◽  
S. Moutari
Keyword(s):  
Kinetic Model ◽  
Traffic Flow ◽  
Hybrid Model ◽  
Road Network ◽  
Heterogeneous Traffic ◽  
Macroscopic Model ◽  
Priority Rule ◽  
Macroscopic Description ◽  
Flow Through ◽  
Capacity Drop

Abstract We have developed a new hybrid model for an heterogeneous traffic flow, based on a coupling of the Lighthill — Whitham and Richards (LWR) macroscopic model and the kinetic model. On the highways of a road network, we consider the macroscopic description of the traffic flow and switch to the kinetic model to compute the mass flux through a junction. This new model reproduces the capacity drop phenomenon at a merge junction, for instance, without imposing any priority rule. We present some numerical simulations in which we compare the results of the hybrid model with those given by the fully macroscopic model. Furthermore, we illustrate the consequences of the velocity distribution on the flow through a merging junction.

Short-Term Traffic Flow Prediction Based on Hybrid Model

2020 ◽  
pp. 135-143
Author(s):  
Yong Hu ◽  
Meng Yu ◽  
Guanxiang Yin ◽  
Fei Du ◽  
Meng Wang ◽  
...  
Keyword(s):  
Traffic Flow ◽  
Hybrid Model ◽  
Short Term ◽  
Traffic Flow Prediction ◽  
Flow Prediction

Hybrid model for prediction of real-time traffic flow

2016 ◽  
Vol 169 (2) ◽  
pp. 88-96 ◽  
Author(s):  
Baozhen Yao ◽  
Zhe Wang ◽  
Mingheng Zhang ◽  
Ping Hu ◽  
Xinxin Yan
Keyword(s):  
Real Time ◽  
Traffic Flow ◽  
Hybrid Model ◽  
Real Time Traffic

scholarly journals Traffic Multiresolution Modeling and Consistency Analysis of Urban Expressway Based on Asynchronous Integration Strategy

2017 ◽  
Vol 2017 ◽  
pp. 1-19
Author(s):  
Liyan Zhang ◽  
Jian Ma ◽  
Bin Ran ◽  
Lixin Yan
Keyword(s):  
Simulation Model ◽  
Traffic Flow ◽  
Hybrid Model ◽  
Traffic Simulation ◽  
Flow Simulation ◽  
Traffic Density ◽  
Simulation Accuracy ◽  
Integration Strategy ◽  
Urban Expressway ◽  
Simulation Scenario

The paper studies multiresolution traffic flow simulation model of urban expressway. Firstly, compared with two-level hybrid model, three-level multiresolution hybrid model has been chosen. Then, multiresolution simulation framework and integration strategies are introduced. Thirdly, the paper proposes an urban expressway multiresolution traffic simulation model by asynchronous integration strategy based on Set Theory, which includes three submodels: macromodel, mesomodel, and micromodel. After that, the applicable conditions and derivation process of the three submodels are discussed in detail. In addition, in order to simulate and evaluate the multiresolution model, “simple simulation scenario” of North-South Elevated Expressway in Shanghai has been established. The simulation results showed the following.(1)Volume-density relationships of three submodels are unanimous with detector data.(2)When traffic density is high, macromodel has a high precision and smaller error and the dispersion of results is smaller. Compared with macromodel, simulation accuracies of micromodel and mesomodel are lower but errors are bigger.(3)Multiresolution model can simulate characteristics of traffic flow, capture traffic wave, and keep the consistency of traffic state transition. Finally, the results showed that the novel multiresolution model can have higher simulation accuracy and it is feasible and effective in the real traffic simulation scenario.

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