Abstract

SummaryThe main objective of this study is to investigate the relationship between field‐measured conflicts and simulated conflicts estimated from microsimulation model (PARAMICS) using the surrogate safety assessment model. An urban signalized intersection was selected for analysis. Automated video‐based computer vision techniques were used to identify field conflicts. The applicability of a two‐step model calibration procedure applied to VISSIM in a recent study was investigated using PARAMICS. In the first calibration step, the PARAMICS model was calibrated to ensure that the simulation gives reasonable results of average delay times. The second calibration step used a genetic algorithm procedure to calibrate PARAMICS parameters to enhance the correlation between simulated and field‐measured conflicts. Finally, the results obtained from PARAMICS were compared with results obtained from VISSIM. The comparison included three aspects: (i) the car‐following model and safety‐related parameters; (ii) the correlation between simulated and field‐measured conflicts; and (iii) the conflict spatial distributions. The results show that the default simulation model parameters give poor correlation with the field‐measured data, and therefore, using simulation models without a proper calibration should be avoided. Overall, good correlation between field‐measured and simulated conflicts was obtained after calibration for both models, especially at higher time‐to‐collision (TTC) values. At TTC threshold of 1.5 s, PARAMICS overestimates the number of conflicts and VISSIM underestimates it. Both models overestimated the number of conflicts at TTC threshold of 3.00 s. There were major differences between field‐measured and simulated conflicts spatial distributions for both simulation models. This indicates that despite the good correlation obtained from the calibration process, both PARAMICS and VISSIM do not capture the actual conflict occurrence mechanism. Copyright © 2016 John Wiley & Sons, Ltd.

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