A comparison between PARAMICS and VISSIM in estimating automated field‐measured traffic conflicts at signalized intersections

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 timeto-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

Comparison between Surrogate Safety Assessment Model and Real-Time Safety Models in Predicting Field-Measured Conflicts at Signalized Intersections

“…Although the two calibration steps improved the SSAM results, the first step is shown to have the most significant impact. This is similar to recent findings from previous studies (6,20,24).…”

“…Although high correlation values between simulated and field-observed conflicts was obtained in previous studies, systematic overestimation or underestimation of the real number of conflicts was also found. Furthermore, major differences between simulated and field-observed conflicts in spatial distribution were detected (6,9,20,24). These discrepancies suggest that the high correlation between simulated and field-observed conflicts/crashes might come from the exposure dependency (i.e., both simulated and fieldobserved conflicts/crashes are correlated with traffic volume), not from the ability of simulation models to capture the real driving behavior and the actual conflict mechanism.…”

Studying the Safety Impact of Autonomous Vehicles Using Simulation-Based Surrogate Safety Measures

“…Surrogate safety measures, such as time to collision (TTC), postencroachment time (PET), deceleration rate (DR), gap time (GT), and proportion of stopping distance (PSD), are useful measurements of the safety implications [30][31][32][33]. TTC, defined as the expected time for two vehicles to collide if they remain on the same path and at the same speed, is a widely used surrogate safety measure.…”

Evaluation of Microsimulation Models for Roadway Segments with Different Functional Classifications in Northern Iran

“…Essa and Sayed [25] performed a comparative analysis of the PARAMICS and VISSIM microsimulation models. The numerical experiments showed that the default model parameters gave poor correlation with the field-measured data.…”