Updating safety-critical applications, e.g. to adapt to a changed interface specification, is expensive due to the required recertification. We describe a concept based on the Simplex architecture for trusted systems to update the implementation of a backwardcompatible interface with unchanged safety properties. We show that safety can be inherited from an existing trusted controller at the cost of reducing the overall system's availability. The applicability is shown via a case study in the railway sector, where we see a shift toward standardized interfaces. EULYNX is the European railway interface standardization initiative. Due to the long lifetimes of railway systems, vendors are building EULYNX-compatible products while the standard is still under active development. In our case study, we build a EULYNX-compatible object controller for train-detecting axle counting modules, relying on the proven safety of an object controller implementing the older NeuPro protocol.

With the increasing reach and applicability of software systems in railway infrastructure, their complexity and the demand for constant change increases. Main factors include the use of unreliable COTS components, technical obsolescence, increasing centralization, international harmonization of technical and operational standards as well as IT-security concerns. Statically assessing the functional safety of a software-based railway system (offline assurance) is thus insufficient to maintain continued operation.Applying simplex architectures on multiple layers of the system architecture can alleviate this problem: Using a simple decision logic component, simplex controls the complexity of an evolving and multi-faceted system while maintaining the level of dependability that is required for safe passenger transport. We argue that the introduction of online assurance marks a paradigm shift in the railway domain, where the system safety today is guaranteed by expert assessments.

In modern trains, a juridical recording unit logs events that occur during operation. This data is used to reconstruct the exact chain of events in case of failures and crashes. To ensure data recovery after an accident, the recorder is hardened against physical damage and secured against tampering; however, it is a single proprietary device and by no means indestructible.This paper presents ZugChain, a distributed, blockchain-based juridical recording unit that opportunistically utilizes on-train hardware. ZugChain offers high reliability via replication and tamper-resistance due to the nature of blockchains. It implements a permissioned blockchain based on a Byzantine fault-tolerant agreement protocol suitable for diverse communication systems. To utilize the logged data for advanced services, e. g., predictive maintenance, ZugChain securely and continuously exports traces to private data centers. We demonstrate ZugChain's feasibility with an implementation running on real train hardware, where we show that ZugChain orders data within 14 ms using at maximum 15 % of the total available shared CPU resources, thus fulfilling requirements of juridical recorders.

The digitalization of railway systems should increase the efficiency of the train operation to achieve future mobility challenges and climate goals. But this digitalization also comes with several new challenges in providing a secure and reliable train operation. The work resulting in this paper tackles two major challenges. First, there is no single university curriculum combining computer science, railway operation, and certification processes. Second, many railway processes are still manual and without the usage of digital tools and result in static implementations and configurations of the railway infrastructure devices. This case study occurred as part of the Digital Rail Summer School 2021, a university course combining the three mentioned aspects as cooperation of several German universities with partners from the railway industry. It passes through all steps from a digital Control-Command and Signalling (CCS) planning in ProSig 7.3, the transfer, and validation of the planning in the PlanPro data format and toolbox, to the generation of code of an interlocking for the digital CCS planning to contribute to the vision of test automation. This paper contributes the experiences of the case study and a proof-of-concept of the whole lifecycle for the Digital Testfield of Deutsche Bahn in Scheibenberg. This proof-of-concept will be continued in ongoing and following projects to fulfill the vision of test automation and automated launching of new devices.

Federated learning allows a group of distributed clients to train a common machine learning model on private data. The exchange of model updates is managed either by a central entity or in a decentralized way, e.g. by a blockchain. However, the strong generalization across all clients makes these approaches unsuited for non-independent and identically distributed (non-IID) data.

Data transfers impose a major bottleneck in heterogenous system architectures. As a mitigation strategy, compute resources can be introduced in places where data occurs naturally. The increased diversity of compute resources in turn affects programming models and practicalities of software development for near-data compute kernels and raises the question of how those resources can be made accessible to users and applications.

This paper presents a multivariable state feedback tracking control with integral sliding mode which can achieve the output tracking of a reference step signal without any overshoot by rejecting the disturbances. The control designed is able to completely reject the matched-bounded disturbances by using the integral sliding mode technique. The multivariable feedback controller is capable of achieving arbitrarily small rise time without any overshoot for square multivariable system under some mild assumptions. The proposed control is verified using a numerical example of quadruple-tank setup.