# Investigating a Toolchain from Trajectory Recording to Resimulation
## 5 Conclusions  
This paper contributes to the efforts of simulating traffic scenarios that go beyond linear traffic, e.g., on highways. An open-source simulation environment is employed, namely openPass. Furthermore, the paper presents a toolchain that integrates the simulation and the comparison to video recordings and laser scans. In this study, a comparison between recorded and simulated traffic flow data was presented. Initially, scenarios on a T-junction involving cars and VRUs demonstrated that the simulation models for vehicles are quite realistic. The scenery, as well as the trajectories recorded in it, could be depicted realistically. Three scenarios were studied, i.e., (1) two cars driving behind each other, (2) one car drives straight and the other turns left, and (3) a pedestrian is crossing the street in front of a car. The 3D geometry of the scenery was captured with a laser scanner, and the recorded video data of the three scenarios could be mapped via transformation on the geo-referenced environment. The extraction of vehicle and pedestrian trajectories was performed using the R-CNN object detector, which was able to successfully track all objects. However, the algorithm had difficulties in estimating the velocity of objects. Further research and a comparison of object detection algorithms are needed. Additionally, a detailed evaluation of the object detection is necessary. Therefore, a geo-referenced data set of vehicle and pedestrian trajectory should be created, e.g., by total station-based object tracking. The open-source simulation environment openPASS was used to simulate the three scenarios. It was able to represent the behavior of cars and pedestrians. However, the idealized type of trajectory formation in the simulation does not allow any fluctuations of the trajectory within the lanes. This was observed as a deviation between recorded and simulated trajectories. However, this property had no significant influence on the course of the scenarios, so this effect can be neglected for the recorded scenarios. Nevertheless, a more realistic movement on the lane is needed for the investigation of other important maneuvers like avoiding obstacles in the lane, overtaking, or scenarios with traffic on both lanes. Additionally, the version of the simulation environment used lacks a realistic parameter for road users' reaction times, resulting in earlier vehicle reactions than what is observed in actual recorded trajectories. However, since reaction times can be assumed, the trajectories could be corrected accordingly afterwards. Turning maneuvers such as an LTAP can only be represented to a limited extent by the included behavioral models. Vehicles do not react to approaching opponents unless they are in front of them (vehicle following model) or beside them (lane change model). This results in critical scenarios (near misses and accidents) and enables an investigation of these critical scenarios resulting from  
Figure 10: Alternative OpenDrive implementation of the investigated intersection to enable the mapping of additional interesting maneuvers in the scenery, independent of the predefined direction of travel established by the OpenDrive standard. The examined T-junction was divided into three sections (grey boxes), each further subdivided into two directions of travel (red and green reference lines). By overlapping the resulting six sections, it becomes possible to represent scenarios such as overtaking maneuvers with traffic on both lanes. missing reactions to approaching vehicles. For more complex, non-linear driving scenarios, the simulation environment needs further enhancements. Finally, behavioral models of pedestrians and other VRUs need to be incorporated in the simulation environment. Conceptualization, F.L., C.K., and A.S. ([PERSON]); methodology, F.L., C.K., and A.S. ([PERSON]); software, F.L. and M.K. ; validation, F.L. ; formal analysis, A.S. ([PERSON]); investigation, F.L., A.S. ([PERSON]) and C.K. ; data curation, A.S. ([PERSON]), and M.K.