of traffic volumes from manual traffic counts with a set of volumes done at the same locations using automation (e.g. a pneumatic tube traffic counter is used to check the total entering volumes at an intersection to affirm the work done by technicians doing a manual count of the turn volumes). Comparing the traffic volumes obtained from this year's traffic counts with a group of counts done at the same locations in a previous year. Comparing the traffic volumes obtained from a travel demand forecasting model (for the "base year" scenario) with the real-world traffic volumes. Adjusting traffic volume data collected at different times to create a mathematically consistent data set that can be used as input for travel demand forecasting models or traffic simulation models (as discussed in NCHRP 765). Common criticism about GEH statistic The GEH statistic depends on the magnitude of the values. Thus, the GEH statistic of two counts of different duration (e.g., daily vs. hourly values) cannot be directly compared. Therefore, GEH statistic is not suitable for evaluating other indicators, e.g., trip distance. Deviations are evaluated differently upward or downward, so the calculation is not symmetrical. Moreover, the GEH statistic is not without a unit, but has the unit . The GEH statistic does not fall within a range of values between 0 (no match) and 1 (perfect match). Thus, the range of values can only be interpreted with sufficient experience (= non-intuitively). Furthermore it is criticized that the value does not have a well-founded statistical derivation. Development of the SQV statistic An alternative measure to the GEH statistic is the Scalable Quality Value (SQV), which solves the above-mentioned problems: It is applicable to various indicators, it is symmetric, it has no units, and it has a range of values between 0 and 1. Moreover, Friedrich et al. derive the relationship between GEH statistic and normal distribution, and thus the relationship between SQV statistic and normal distribution. The SQV statistic is calculated using an empirical formula with a scaling factor : Fields of application By introducing a scaling factor , the SQV statistic can be used to evaluate other mobility indicators. The scaling factor is based on the typical magnitude of the mobility indicator (taking into account the corresponding unit). According to Friedrich et al., the SQV statistic value is suitable for assessing: Traffic volumes (if necessary, differentiation can be made not only by time