The performance of low-cost RTK(real-time kinematic)GPS receivers hasbeen compared to a state-of-the-art system as well to each other. Both static and dynamic performanceshavebeen compared. The dynamic performance has been evaluated using a vehicle with driving robot on the AstaZero proving ground.The assembly of the low-cost RTK GPS receivers is presented, and the test set-ups described. Besides having a lower data output frequency, two of the low-cost receivers have static and dynamic performance not far fromthat of the state-of-the-art system.

When designing safety critical and software intensive embedded systems, extensive development processes have to be followed in order to ensure that the software corresponds with the software safety requirement specification. This paper describes a study performed to investigate how to use a component based approach in order to reduce the requirements of the development processes for safety critical embedded systems. Focus is on certification of individual software components by the use of integrity contracts and how this enables software component composition and re-usability, particularly between different domains. The use of our approach in system design may reduce the effort required for an assessor in certifying an entire safety critical system.

In this paper we present a methodology and a platform using Fault Injection (FI) and Property-Based Testing (PBT). PBT is a technique in which test cases are automatically generated from a specification of a system property. The generated test cases vary input stimuli as well as the sequence in which commands are executed. FI is used to accelerate the occurrences of faults in a system to exercise and evaluate fault handling mechanisms and e.g. calculate error detection coverage. By combining the two we have achieved a way of randomly injecting different faults at arbitrary moments in the execution sequence while checking whether certain properties still hold. We use the commercially available tool QuickCheck for generating the test cases and developed FaultCheck for FI. FaultCheck enables the user to utilize fault models, commonly used during FI, from PBT tools like QuickCheck. We demonstrate our method and tools on a simplified example of two Airbag systems that should meet safety requirements. We can easily find a safety violation in one of the examples, whereas by using the AUTOSAR E2E-library implementation, exhaustive testing cannot reveal any such safety violation. This demonstrates that our approach on testing can reveal certain safety violations in a cost-effective way.

We present a quadcopter platform built with commodity hardware that is able to do localization in GNSS-denied areas and avoid collisions by using a novel easy-to-setup and inexpensive ultrasound-localization system. We address the challenge to accurately estimate the copter's position and not hit any obstacles, including other, moving, quadcopters. The quadcopters avoid collisions by placing contours that represent risk around static and dynamic objects and acting if the risk contours overlap with ones own comfort zone. Position and velocity information is communicated between the copters to make them aware of each other. The shape and size of the risk contours are continuously updated based on the relative speed and distance to the obstacles and the current estimated localization accuracy. Thus, the collision-avoidance system is autonomous and only interferes with human or machine control of the quadcopter if the situation is hazardous. In the development of this platform we used our own simulation system using fault-injection (sensor faults, communication faults) together with automatically-generated tests to identify problematic scenarios for which the localization and risk contour parameters had to be adjusted. In the end, we were able to run thousands of simulations without any collisions, giving us confidence that also many real quadcopters can manoeuvre collision free in space-constrained GNSS-denied areas.

Accurate positioning is a requirement for many applications, including safety-critical autonomous vehicles. To reduce cost and at the same time improving accuracy for positioning of autonomous vehicles, new methods, tools, and research platforms are needed. We have created a low-cost testbed consisting of electronics and software that can be fitted on model vehicles allowing them to follow trajectories autonomously with a position accuracy of around 3 cm outdoors. The position of the vehicles is derived from sensor fusion between Real-Time Kinematic Satellite Navigation (RTK-SN), odometry, and inertial measurement and performs well within a 10 km radius from a base station. Trajectories to be followed can be edited with a custom GUI, where also several model vehicles can be controlled and visualized in real time. All software and Printed Circuit Boards (PCBs) for our testbed are available as open source to make customization and development possible. Our testbed can be used for research within autonomous driving, for carrying test equipment, and other applications where low cost and accurate positioning and navigation are required.

Cyclists are not well protected in accidents with other road users, and there are few active safety systems available for bicycles. In this study we have evaluated the use of inexpensive Real-Time Kinematic Satellite Navigation (RTK-SN) receivers with multiple satellite constellations together with dead reckoning for accurate positioning of bicycles to enable active safety functions such as collision warnings. This is a continuation of previous work were we concluded that RTK-SN alone is not sufficient in moderately dense urban areas as buildings and other obstructions degrade the performance of RTK-SN significantly. In this work we have added odometry to the positioning system as well as extending RTK-SN with multiple satellite constellations to deal with situations where the view of the sky is poor and thus fewer satellites are in view. To verify the performance of the positioning system we have used Ultra-Wideband radios as an independent positioning system to compare against while testing during poor conditions for RTK-SN. We were able to verify that adding dead reckoning and multiple satellite constellations improves the performance significantly under poor conditions and makes the positioning system more useful for active safety systems.

Safety ADD is a tool for working with safety contracts for software components. Safety contracts tie safety related properties, in the form of guarantees and assumptions, to a component. A guarantee is a property the component promises to hold, on the premise that the environment provides its associated assumptions. When multiple software components are integrated in asystem, Safety ADD is used to verify that the guarantees and assumptions match when there are safety-related dependencies between the components. The initial goal of Safety ADD is to investigate how safety contracts can be managed and used efficiently within the software design process. It is implemented as an Eclipse plug in. The tool has two main functions. It gives designers of software components a way to specify safety contracts, which are stored in an XML format and shall be distributed together with the component. It also gives developers who integrate multiple software components in their systems a tool to verify that the safety contracts are fulfilled. A graphical editor is used to connect guarantees and assumptions for dependent components, and an algorithm traverses all such connections to make sure they match.