Vehicle automation software development using software-only simulation

Automatic driving and driver assistance systems are gaining attraction in the automotive industry. Their development is not an easy task and requires enormous amounts of testing and validation. However, conducting all testing with a real car is expensive and ineffcient. A possible solution to streamline testing is simulation, especially software-only simulation. In software-only simulation, everything is simulated using just software. It does not require any specialized hard ware making it cheaper and easier to establish and scale up the number of testing environments. The goal of this thesis was to study how a software-only simulation environment could be built using readily available open-source components. A simulator environment based on an open-source driving simulator, CARLA, was built, and an example application was developed and integrated into it using Robot Operating System 2 (ROS2). The example application, Carlabot, supports manual driving with a gamepad and utilizes a LiDAR sensor to implement a simple collision avoider, which slows down or stops the car if something is detected in front of the car. The process of setting up a CARLA simulator environment using predefned assets, such as vehicle and world model, proved to be straightforward, and integrating a simple example application was fairly uncomplicated. However, using the environment for real product development would require customizing at least the assets. Software-only simulation brings benefts to the software development of automatic vehicles. It allows testing on a scale that is not viable using just real hardware, and it enables using test automation already in integration testing. Software-only simulation supports agile software development, where testing begins early, already during the development

EDGAR: An Autonomous Driving Research Platform -- From Feature Development to Real-World Application

While current research and development of autonomous driving primarily focuses on developing new features and algorithms, the transfer from isolated software components into an entire software stack has been covered sparsely. Besides that, due to the complexity of autonomous software stacks and public road traffic, the optimal validation of entire stacks is an open research problem. Our paper targets these two aspects. We present our autonomous research vehicle EDGAR and its digital twin, a detailed virtual duplication of the vehicle. While the vehicle's setup is closely related to the state of the art, its virtual duplication is a valuable contribution as it is crucial for a consistent validation process from simulation to real-world tests. In addition, different development teams can work with the same model, making integration and testing of the software stacks much easier, significantly accelerating the development process. The real and virtual vehicles are embedded in a comprehensive development environment, which is also introduced. All parameters of the digital twin are provided open-source at https://github.com/TUMFTM/edgar_digital_twin

Technical Note: 4D Deformable Digital Phantom for MRI Sequence Development

PURPOSE: MR-guided radiotherapy has different requirements for the images than diagnostic radiology, thus requiring development of novel imaging sequences. MRI simulation is an excellent tool for optimising these new sequences, however currently available software does not provide all the necessary features. In this paper we present a digital framework for testing MRI sequences that incorporates anatomical structure, respiratory motion and realistic presentation of MR physics. METHODS: The extended Cardiac-Torso (XCAT) software was used to create T1, T2 and proton density maps that formed the anatomical structure of the phantom. Respiratory motion model was based on the XCAT deformation vector fields, modified to create a motion model driven by a respiration signal. MRI simulation was carried out with JEMRIS, an open source Bloch simulator. We developed an extension for JEMRIS, which calculates the motion of each spin independently, allowing for deformable motion. RESULTS: The performance of the framework was demonstrated through simulating the acquisition of a 2D cine and demonstrating expected motion ghosts from T2 weighted spin echo acquisitions with different respiratory patterns. All simulations were consistent with behaviour previously described in literature. Simulations with deformable motion were not more time consuming than with rigid motion. CONCLUSIONS: We present a deformable 4D digital phantom framework for MR sequence development. The framework incorporates anatomical structure, realistic breathing patterns, deformable motion and Bloch simulation to achieve accurate simulation of MRI. This method is particularly relevant for testing novel imaging

Integration of Macro-Fiber Composite Material on a Low Cost Unmanned Aerial System

The development, deployment, and operation of Unmanned Aerial Systems (UAS) have grown exponentially in recent years and have provided researchers with the opportunity to gain hands-on experience with aircraft in a manner that was previously limited to institutions and companies with large budgets. This allows the generation and testing of UAS advanced technologies using low cost systems. The scope of this thesis does not aim to make vast improvements to the control strategy itself, but to expand upon previous UAV work carried out at Embry-Riddle by designing, implementing, and demonstrating a simulation environment for mechanical and Macro-Fiber Composite (MFC) actuated ailerons in a Skywalker 1880 UAV using model reference adaptive control law. This work will contribute to a baseline model for the research and development of future UAV with morphing control surfaces up to a flight test stage. Meanwhile the extensive use of low-cost hardware and open source software allows the opportunity to explore the feasibility of using affordable open-source technology in an academic context. Future students who are interested in morphing designs for UAV may find the baseline system presented here to be a useful starting point from which to begin their own research

Investigating the use of ray tracing for signal-level radar simulation in space monitoring applications: a comparison of radio propagation models

This thesis presents the design and development of an accelerated signal-level radar simulator with an emphasis on space debris monitoring in the Low Earth Orbit. Space surveillance represents a major topic of concern to astronomers as the threat of space debris and orbital overpopulation looms – particularly due to the lack of effective mitigation techniques and the limitations of modern space-monitoring sensors. This work thus aimed to investigate and design possible tools that could be used for training, testing and research purposes, and thereby aid further study in the field. At present, there exist no three-dimensional, ray-traced, signal-level radar simulators available for public use. As such, this thesis proposes an open-source, ray-traced radar simulator that models the interactions between spaceborne targets and terrestrial radar systems. This utilises a ray-tracing algorithm to simulate the effects of debris size, shape, orientation, and material properties when computing radar signals in a typical simulation. The generated received signals, produced at the output of the simulator, were also verified against systems theory, and validated with an existing, well-established simulator. The developed software was designed to aid astronomers and researchers in space situational awareness applications through the simulation of radar designs for orbital surveillance experiments. Due to its open-source nature, it is also expected to be used in training and research environments involving the testing of space-monitoring systems under various simulation conditions. The software offers native support for measured Two-Line Element datasets and the Simplified General Perturbations #4 orbit propagation model, enabling the accurate modelling of targets and the dynamic orbital forces acting upon them. As a result, the software has aptly been named the Space Object Astrodynamics and Radar Simulator – or SOARS. SOARS was built upon the foundations of a general-purpose radar simulator known as the Flexible Extensible Radar Simulator – or FERS – which provided integrated radar models for propagation loss, antenna shapes, Doppler and phase shifts, Radar Cross Section modelling, pulse waveforms, high-accuracy clock mechanisms, and interpolation algorithms. While FERS lacked various features required for space-monitoring applications, many of its implementations were used in SOARS to minimise simulation limits and maximise signal rendering accuracy by supporting an arbitrary number of transmitters, receivers, and targets. The goal was thus to have the simulator limited only by the end-user's system, and to specialise the operation of the software towards space surveillance by integrating additional features – such as built-in models for environmental and system noise, multiscatter effects, and target modelling using meshes comprised of triangular primitives. After completing the software's development, the ray-traced simulator was compared against a more streamlined version of SOARS that made use of point-model approximations for quick-look simulations, and the trade-offs between both simulators (including software runtime, memory utilisation and simulation accuracy) were investigated and evaluated. This assessed the value of implementing ray tracing in a radar simulator operating primarily within space contexts and evaluated the results of both simulators using detection processing as a demonstrated application of the system. And while the use of ray tracing resulted in significant costs in speed and memory, the investigation found that the ray-traced simulator generated more reliable results relative to the point-model version – providing various advantages in test scenarios involving shadowing and multiscatter. The design of the SOARS software, as well as its point-model “baseline” alternative and the investigation into each simulator's advantages and disadvantages, are thus presented in this thesis. The developed programs were released as open-source tools under the GNU General Public Licence and are freely available for public use, modification, and distribution

Using SCCharts models in Simulink to model an electronic control unit

When constructing an electrical racing car, special attention needs to be directed to the development of its engine control unit. Functionality of the motor-torque calculation and the integration of advanced driver assistance systems are crucial for the speed handling and hence, the safety of the car. The Kieler Formula Student Team Raceyard, which since 2011 has been constructing electrical racing cars annually, so far designed and tested its controller model in the popular commercial modeling software MATLAB/Simulink. This work shows how a functionally equivalent system can be designed by utilizing the visual synchronous language SCCharts in the academic open-source project KIELER. A complete controller model is modeled in KIELER and validated to behave the same as the original controller both in Simulink directly as well as in the 3D simulation environment IPG Carmaker. Tests on the performance of both controllers show that while a slowdown can be observed when comparing the generated C Code, simulation time in IPG Carmaker only increases by a negligible factor. KIELER’s developing and testing capabilities for synchronous models can therefore be considered a valuable tool in the process of designing, tuning and documenting such a controller model

Lightweight Simulator for Automated Guided Vehicles

Automatic solutions are rapidly being adopted by the world’s leading industries to cut costs and improve effciency for processes, which have previously required human operators. However, as the automation of heavy machinery involves expensive hardware, the development and testing of automated solutions can be slow and costly. One solution to avoid this problem is to create a simulation of the physical environment and do preliminary software functionality testing in simulation only. This thesis examines the implementation of a lightweight simulation environment for the evaluation of software used to control automated guided straddle carriers. The simulator is based on Gazebo, an open-source robotics simulation software with support for multiple physics engines, which allows for advanced and fexible physics simulation. The aim of the thesis was to implement a minimum-viable-product type of simulation environment, where a simplifed model of the straddle carrier can be controlled through the real machine control system, using pre-existing operating tools for both manual and automatic guidance. This was achieved by creating software with a layered architecture, where interprocess communication protocols are utilized to create communication channels between the machine control system, virtual device layer, and the physics simulator. In the future, the simulator will be extended to support more advanced features of the automated guided vehicle, such as picking and placing containers

SuLMaSS - Sustainable Lifecycle Management for Scientific Software

The SuLMaSS project [1] will advance, develop, build, evaluate, and test infrastructure for sustainable lifecycle management of scientific software. The infrastructure is tested and evaluated by an existing cardiac electrophysiology simulation software project, which is currently in the prototype state and will be advanced towards optimal usability and a large and active user community. Thus, SuLMaSS is focused on designing and implementing application-oriented e-research technologies and the impact is three-fold: - Provision of a high quality, user-friendly cardiac electrophysiology simulation software package that accommodates attestable needs of the scientific community. - Delivery of infrastructure components for testing, safe-keeping, referencing, and versioning of all phases of the lifecycle of scientific software. - Serve as a best practice example for sustainable scientific software management. Scientific software development in Germany and beyond shall benefit through both the aforementioned best practice role model and the advanced infrastructure that will, in part, be available for external projects as well. With adding value for the wider scientific cardiac electrophysiology community, the software will be available under an open source license and be provided for a large share of people and research groups that can potentially leverage computational cardiac modeling methods. Institutional infrastructure will be extended to explore, evaluate and establish the basis for research software development regarding testing, usage, maintenance and support. The cardiac electrophysiology simulator will drive and showcase the infrastructure formation, thus serving as a lighthouse project. The developed infrastructure can be used by other scientific software projects in future and aims to support the full research lifecycle from exploration through conclusive analysis and publication, to archival, and sharing of data and source code, thus increasing the quality of research results. Moreover it will foster a community-based collaborative development and improve sustainability of research software. References: [1]­‌‌‌‌‌‌‌‌‌ http://www.dfg.de/dfg_magazin/aus_der_wissenschaft/impulse_fuer_das_digitale_lis_jb17/02_aus_der_foerderung/index.htm

Mixed-Effects Location-Scale Models for Conditionally Normally Distributed Repeated-Measures Data

Hypotheses about psychological processes are most frequently dedicated to individual mean differences, but individual differences in variability are likely to be important as well. The mixed-effects location-scale model estimates individual differences in both mean level and variability in a single model, and represents an important advance in testing variability-related hypotheses. However, the mixed-effects location-scale model remains relatively novel to empirical scientists as statistical software is often handicapped by more complex models and a paucity of methodological studies exist examining the statistical properties of this model. This dissertation investigates the mixed-effects location-scale model through the development of open-source software for its estimation and through simulation and empirical studies. First, the theoretical framework for the mixed-effects location-scale model is presented followed by a description of the Metropolis-Hastings algorithm developed to estimate this model. Then, two simulation studies are presented evaluating the power to detect and predict individual differences in variability as well as identify the consequences of model misspecification. Finally, results of an empirical analysis examining individual differences in mean level and variability of unstructured movements from a sample of older adults with and without probable mild Alzheimer’s disease is presented. Results of the power investigation simulation study indicated that the power to detect the scale-model random intercept variance and the effect of an individual-level predictor of residual variability increased with greater numbers of individuals and occasions, and that failing to detect the scale-model random intercept variance essentially precluded the detection of systematically varying fixed effects for an individual-level predictor of residual heterogeneity. Results of the misspecification simulation study indicated that misspecifying the location model and/or scale model for the residual variance had consequences only for fixed and random effects on the same side of the model. Finally, results of the empirical data analysis indicated individuals with probable mild Alzheimer’s disease averaged less movement compared to healthy individuals, but did not differ in the variability of their unstructured movements. In sum, this dissertation provides information useful to empirical scientists as they progress from study design through analysis, interpretation, and reporting for publication. Advisors: Lesa Hoffman & Jonathan Templi