Institut für Automatisierungstechnik

Modellbasierte Systemanalyse

Studien- und Diplomarbeit

Safety Analysis for Group of Autonomous and Connected Vehicles

The automotive industry has demonstrated a strong trend towards autonomous and connected vehicles in recent years.​ One of the biggest challenges for today is ensuring that the autonomous and connected vehicle systems are reliable and safe under possible hazardous conditions. Model-based system design allows the user to implement safety measures to comply with standards, however if the system involves heterogeneous components and subsystems which have to work all together in the presence of stochastic faults, then the safety of the overall system is also critical.

The task is to create a traffic simulation environment using MATLAB and Simulink, implement control algorithms and assess safety levels in the presence of stochastically injected faults. Further extension of the project may include, implementing decision making algorithms depending on the safety metrics.

The student will work with the following technologies and methods: MATLAB, Simulink, Distributed Control, Markov Process. The student is expected to have experience with MATLAB and its graphical user interface and one should be creative and enthusiastic about problem solving.

Contacts: Mustafa Saraoglu
Dr.-Ing. A. Morozov

Studien- und Diplomarbeit

MOBATSim is a simulation framework based on MATLAB Simulink that allows the user to assess vehicle level and traffic level safety by a 3D traffic simulation. It is used to simulate urban city traffic, design intersection management algorithms for the infrastructure or path planning algorithms for vehicles and test the efficiency of autonomous driving functions by PC-based simulations. Simulink 3D Animation with V-Realm are used to visualize the driving scenarios. (

MOBATSim is still being developed to make it a complete tool for comprehensive testing. Its main task is to test autonomous vehicles and their functionsin the presence of various faults. New fault libraries are being defined. An automatic report generator is being developed in accordance with the ISO 26262 standard. Possible Studien- and Diplomarbeit topics can be given to the students who are interested in autonomous vehicle modeling, simulation and safety assessment. The students who want to be a part of the project should know coding and modeling in MATLAB and Simulink, and be highly proficient in both spoken and written English.

Detailed information about MOBATSim can be obtained from:

M.Sc. Mustafa Saraoglu

Efficient Testing of Automotive Model-based Software

Up to 80% of the automotive software can be generated from models. MATLAB Simulink is a common tool for creation of complex combinations of block diagrams and state machines, automated generation of executable code, and its deployment on a target ECU. The automotive safety standard ISO26262 requires extensive testing of the developed models with a large number of test cases. These activities can account up to two-thirds of the cost of software production. Automated software tools like Simulink V&V, Reactis Tester, TraceTronic ECU-TEST or TPT allow the generation of a complete test suite with maximum coverage and minimum redundancy. However, the testing stays extremely time-consuming even these tools. The topics, listed below, are devoted to the improvement of the model-based automotive testing with several intelligent methods. The tasks are closely connected to the industry. Students will get an opportunity to work with real automotive models and tools provided by our partners from TraceTronic and BMW.

Topic 1: Automatic Fault Localization

In practice, the testing tools basically show which test cases were successfully passed and which were failed. We are developing a new method that allows the identification of the faulty part of the model, based on the structural and behavioural properties of the model and the information about the succeeded and failed test cases. The intended method will be based on recently introduced stochastic dual-graph error propagation model and incorporate intelligent methods such as model reduction, forward propagation of data diversity, and backward error propagation analysis.

The task is to implement a prototype of the fault localisation method (or a part of it) and demonstrate it with a realistic Simulink model accompanied with a number of test cases provided by our industrial partners.

The student will work with the following methods and technologies: MATLAB, Simulink, Simulink API, Python, Basic probability theory, Markov chains, PRISM model checker and testing tools such as TraceTronic ECU-TEST and Reactis Tester.

Dr.-Ing. A. Morozov

Topic 2: Test-case Prioritization for Regression Testing

Regression testing, as it is shown in the figure above, should be undertaken every time the models are updated to ensure that the modifications do not introduce new bugs into a previously validated model. A common, time-consuming way is to rerun an entire test suite after even minor changes. We develop a new method for automatic prioritization of test cases for efficient regression testing. The method is based on a recently introduced dual-graph error propagation model - a stochastic mathematical framework that describes data error propagation processes. The method automatically estimates which parts of the system can be affected by the errors that have occurred in the updated blocks and identifies the test cases that will both stimulate errors in the updated components and detect the occurred errors.

The task is to optimize and extend the current implementation of the prioritization method towards full-scale automotive models. Our colleagues from the TraceTronic Dresden will provide realistic Simulink models used by BMW and ensure that the method is implemented according to industrial needs.

The student will work with the following technologies and methods: MATLAB, Simulink, Simulink API, Python, Basic probability theory, automated testing tools.

Dr.-Ing. A. Morozov

Stand: 24.10.2019 14:26
Autor: Webmaster IFA