“…The traditional procedure to validate a traffic flow model contains two steps: first, the model parameters are calibrated using the collected field data (i.e., find the best fitting parameters), and then the quality of the model with these parameters is tested on another data set, which is the validation step (Treiber and Kesting 2012, Daamen, Buisson, and Hoogendoorn 2014, Spiliopoulou et al 2014, Treiber and Kesting 2014, Punzo and Montanino 2016, Mariotte et al 2020. In calibration and validation, the macroscopic performance indicators are commonly used to measure the overall performance of the system, such as the traffic flow (Xie, Nie, andLiu 2017, Tang et al 2020), flow rate (Jiang et al 2017, Yuan, Knoop, and, speed (Chiu, Zhou, andSong 2010, Tian et al 2017), density (Ma, Dong, andZhang 2007, Sayegh, Connors, andTate 2018), queue length (Zhang et al 2020), travel times (Hollander and Liu 2008), and their combinations (Kim and Mahmassani 2011, Ni et al 2016, Han et al 2017, Kontorinaki et al 2017. One may notice that, although calibration of the model can involve finding individual vehicle parameters (Treiber and Kesting 2013), in validation often aggregate variables are used (Treiber and Kesting 2012).…”