Yet Another Driving Simulator OpenROUTS3D: The Driving Simulator for Teleoperated Driving Numerous issues on the way to autonomous vehicles have already been solved. Nevertheless, there are further problems preventing the introduction of autonomous driving features of higher SAE levels. Remote control of vehicles by human operators located in dedicated operation centers, Teleoperated Driving, can help to overcome the problems of autonomous driving. To enable functional Teleoperated Driving, existent network technology has to be utilized. These cellular networks suffer from variable performance. However, testing Teleoperated Driving and its algorithms in realworld scenarios is costly and potentially dangerous. Virtual testing is an approach to mitigate these obstacles. This paper introduces OpenROUTS3D, an opensource driving simulator initially developed for Teleoperated Driving, but expandable to various use cases.

Endtoend models for selfdriving cars on UPB campus roads In autonomous driving, making the vehicle trajectory planning a learnable process (so called endtoend driving), given visual input and car motion measurements alone is an idea with longstanding tradition. In a recent project we investigate the potential to incorporate the steering predictions of an endtoend model operating under constraints of a single monocular camera input, into the planning pipeline of existing opensource frameworks for autonomous driving. We describe a process to design and train such a model given a specific geographical area with its own particularities in terms of road network, traffic and driving conditions. We investigate data augmentation techniques which improve the performance of the model. Quality and performance analysis of the model is performed based on a collected dataset in the UPB campus. The evaluation is carried out using a simulation pipeline which applies transformations to the frames in test videos such that they reflect decisions made by the model in earlier steps. This brings the system evaluation closer to out of distribution testing. Results indicate that the proposed models offers a good performance for the collected dataset.