## 4 Review of Current Methodologies against the Background of Calibration Challenges
### Synthetically Designed Cycles Based on (Regionally) Relevant Driving Behavior  
In addition to the testing of real routes and the purely emissions-motivated simulative development of worst-case test cycles, it is also possible to create test scenarios that process empirical findings from previous measurements into fictitious routes [67; 71; 72; 73; 74; 95; 96]. The database must sufficiently represent the criteria to be checked. Possible input data for this process can be collected in fixed geographical areas, for example, if a driving cycle is to be created for a specific region. An example for this procedure is the development of the WLTC. It is based on a database containing a representative amount of data on typical driving behavior in Europe [67; 68]. This background information is used to parameterize transition matrices for Markov chains. These Markov chains [97] determine probable implications for characteristic values, such as vehicle speeds and accelerations, and thus enable the creation of a driving profile that is characterized by an average typical European speed and acceleration pattern. However, the emission behavior of a vehicle is not considered in these methods. Based on adjusted boundary conditions, an extension of the geographical areas might be required (e.g., typical driving behavior in high altitudes outside of the current EU6d legislative restrictions). The layout of these cycles can in general remain on the current approaches with existing databases and generation algorithms. Modifications of the input parameters for controlling the dynamics and distance shares will have to be carried out based on upcoming changes. Implementation of Solutions and Presentation of a Suitable RDE Development and Validation Methodology  
As previously presented, a suitable solution to support the RDE development for existing and future legislative requirements needs to combine different aspects. A laboratory environment is required, to be able to measure all relevant pollutants in an accurate manner. The focus on cycles used for these measurements must be able to be placed on all different exhaust gas components. For a high flexibility and thus low efforts to adjust the approach for new legislations, the process for the test profile definition must be built to easily control the boundary conditions with regard to driving dynamics and track characteristics. Especially when referring the test profile to a statistical relevance for the typical usage of the vehicle, these statistical data have to be considered already during the generation of the profiles. Adjustment of existing models must not be necessary, or at most only to a minor extend. These requirements are combined in an approach of statistically supported RDE cycle generation [65]. With measurement data being collected from all available sources (Figure 8 \"Measurement Data\"), such as on-road robustness recordings or PEMS measurements, chassis dynamometer and X-in-the-Loop test benches as described in [98; 95; 96; 99; 100; 101; 102; 103; 104; 105; 106; 107], the methodology is highly flexible towards the consideration of additional new pollutants. Furthermore, specifications of exhaust gas components that require a highly sophisticated measurement equipment can easily be evaluated using the laboratory measurement equipment. An automatic evaluation of these measurement data (Figure 8 \"Event Detection\") not only allows a more efficient analysis of data than a manual evaluation by an engineer, but also considers any data input identifying potentially critical sequences in these, regardless of the absolute intensity of the total test result. In this way, data are included in the consideration of emission robustness and calibration potentials, even if they are not critical on first sight. In the context of emission optimization, the event detection identifies critical sequences with regard to their individual emission intensity by analyzing the emission formation in a certain sequence.