A novel assistive on-ramp merging control system for dense traffic management

On-ramps are area of frequent traffic congestion. Proper traffic guidance around on-ramp merging areas exerts a positive effect on the relief of traffic congestion. The objective of this paper is to design an assistive ramp-merging control (ARMCON) system. It utilizes knowledge about professional driver behavior and the dynamical relationship among the on-ramp vehicles, to produce timely information so as to guide the on-ramp drivers when merging with the main traffic flow. Under the guidance of ARMCON, disruption of the main traffic on the express way is minimized while a certain merging rate is maintained.

[1]  Yang Zhang,et al.  Traffic forecasting using least squares support vector machines , 2009 .

[2]  Wanli Min,et al.  Real-time road traffic prediction with spatio-temporal correlations , 2011 .

[3]  Lei Zhang,et al.  Freeway Travel-Time Estimation Based on Temporal–Spatial Queueing Model , 2013, IEEE Transactions on Intelligent Transportation Systems.

[4]  Michael J Demetsky,et al.  TRAFFIC FLOW FORECASTING: COMPARISON OF MODELING APPROACHES , 1997 .

[5]  Moshe Levin,et al.  ON FORECASTING FREEWAY OCCUPANCIES AND VOLUMES (ABRIDGMENT) , 1980 .

[6]  Juraj Spalek,et al.  Cellular automaton traffic flow model with vehicle type and number of persons , 2015 .

[7]  Mu-Chen Chen,et al.  Forecasting the short-term metro passenger flow with empirical mode decomposition and neural networks , 2012 .

[8]  I Okutani,et al.  Dynamic prediction of traffic volume through Kalman Filtering , 1984 .

[9]  A. R. Cook,et al.  ANALYSIS OF FREEWAY TRAFFIC TIME-SERIES DATA BY USING BOX-JENKINS TECHNIQUES , 1979 .

[10]  Peter C. Y. Chen,et al.  LSTM network: a deep learning approach for short-term traffic forecast , 2017 .

[11]  Jaume Barceló,et al.  Modelling Advanced Transport Telematic Applications with Microscopic Simulators: The Case of AIMSUN2 , 1999 .

[12]  Roberto Horowitz,et al.  Congested Freeway Microsimulation Model Using VISSIM , 2004 .

[13]  Mascha C. van der Voort,et al.  Combining kohonen maps with arima time series models to forecast traffic flow , 1996 .

[14]  Ali Haghani,et al.  Evaluating Moving Average Techniques in Short-Term Travel Time Prediction Using an AVI Data Set , 2010 .

[15]  Zhong Liu,et al.  Vehicle-Following Model Using Virtual Piecewise Spline Tow Bar , 2016 .

[16]  Gordon D. B. Cameron,et al.  PARAMICS—Parallel microscopic simulation of road traffic , 1996, The Journal of Supercomputing.

[17]  L. A. Pipes.  An Operational Analysis of Traffic Dynamics , 1953 .

[18]  C. Gallagher.  Extending the Linear Model With R: Generalized Linear, Mixed Effects and Nonparametric Regression Models , 2007 .

[19]  Chung-Cheng Lu,et al.  A bayesian dynamic linear model approach for real-time short-term freeway travel time prediction , 2011 .

[20]  Michael Schreckenberg,et al.  Effect of driver over-acceleration on traffic breakdown in three-phase cellular automaton traffic flow models , 2013 .

[21]  Wilhelm Leutzbach,et al.  Introduction to the Theory of Traffic Flow , 1987 .

[22]  Michael Schreckenberg,et al.  A cellular automaton model for freeway traffic , 1992 .

[23]  Piet H. L. Bovy,et al.  Car-Following Under Congested Conditions: Empirical Findings , 1998 .

[24]  Xiaoyan Zhang,et al.  Short-term travel time prediction , 2003 .