Calibration of a microscopic traffic simulator

A systematic calibration study was performed on a microscopic traffic simulatorMITSIM. An optimization based framework was developed for calibration. CarFollowing model parameters were identified for calibration and experimental design methodology was used to determine the set of sensitive parameters. Calibration was performed by minimizing the deviation between the simulated and observed values of speed. Two different objective function forms were formulated for quantifying the deviation between the simulated and observed values. The search space and the optimum parameter values for the two objective function forms were compared. The effect of stochasticity in calibrating the parameter values was also studied. Stochasticity was found to have a significant impact on the optimal parameter values. It was found that though calibration is an intricate process, the performance of the simulator can be substantially improved by an appropriate calibration study. Thesis Supervisor: Moshe E. Ben-Akiva Title: Edmund K. Turner Professor of Civil and Environmental Engineering Thesis Supervisor: Mithilesh K. Jha Title: Research Associate, Center for Transportation Studies Thesis Supervisor: Didier M. Burton Title: Research Associate, Center for Transportation Studies

[1]  Martha A. Centeno,et al.  So you have your model: what to do next. A tutorial on simulation output analysis , 1998, 1998 Winter Simulation Conference. Proceedings (Cat. No.98CH36274).

[2]  D. Rubinfeld,et al.  Econometric models and economic forecasts , 2002 .

[3]  Margaret J. Robertson,et al.  Design and Analysis of Experiments , 2006, Handbook of statistics.

[4]  Susan Xiujuan Wang.  Validation and calibration needs of MITSIM , 1997 .

[5]  Stephen G. Ritchie,et al.  CALIBRATION OF INTRAS FOR SIMULATION OF 30-SEC LOOP DETECTOR OUTPUT , 1994 .

[6]  K. Ahmed.  Modeling drivers' acceleration and lane changing behavior , 1999 .

[7]  Gordon M. Clark,et al.  Use of common random numbers in comparing alternatives , 1990, 1990 Winter Simulation Conference Proceedings.

[8]  D. Gazis,et al.  Nonlinear Follow-the-Leader Models of Traffic Flow , 1961 .

[9]  A. May,et al.  NON-INTEGER CAR-FOLLOWING MODELS , 1967 .

[10]  W. David Kelton.  Statistical analysis of simulation output , 1997, WSC '97.

[11]  Qi Yang,et al.  A SIMULATION LABORATORY FOR EVALUATION OF DYNAMIC TRAFFIC MANAGEMENT SYSTEM , 1997 .

[12]  Averill M. Law,et al.  Simulation Modeling and Analysis , 1982 .

[13]  Xin Jin,et al.  CALIBRATION OF FRESIM FOR SINGAPORE EXPRESSWAY USING GENETIC ALGORITHM , 1998 .

[14]  Sigrún Andradóttir,et al.  A review of simulation optimization techniques , 1998, 1998 Winter Simulation Conference. Proceedings (Cat. No.98CH36274).

[15]  Peter D. Welch,et al.  The application of experimental design to the analysis of semiconductor manufacturing lines , 1990, 1990 Winter Simulation Conference Proceedings.

[16]  Christos Alexopoulos,et al.  Advanced methods for simulation output analysis , 1998, 1998 Winter Simulation Conference. Proceedings (Cat. No.98CH36274).

[17]  David Goldsman,et al.  Single-replication simulation , 1990, 1990 Winter Simulation Conference Proceedings.

[18]  R. B. Potts,et al.  Car-Following Theory of Steady-State Traffic Flow , 1959 .

[19]  Haris N. Koutsopoulos,et al.  Simulation Laboratory for Evaluating Dynamic Traffic Management Systems , 1997 .

[20]  M.A.P. Taylor,et al.  Evaluating the performance of a simulation model , 1979 .

[21]  A. Maria,et al.  Simulation Optimization: Methods And Applications , 1997, Winter Simulation Conference Proceedings,.

[22]  Moshe Ben-Akiva,et al.  Discrete Choice Analysis: Theory and Application to Travel Demand , 1985 .

[23]  Hariharan Subramanian,et al.  Estimation of car-following models , 1996 .