Related papers: Engineering Autonomous Driving Software
This paper discusses a model-based approach to validate software requirements in agile development processes by simulation and in particular automated testing. The use of models as central development artifact needs to be added to the…
Autonomous vehicles rely on machine learning to solve challenging tasks in perception and motion planning. However, automotive software safety standards have not fully evolved to address the challenges of machine learning safety such as…
Autonomous vehicles are the culmination of advances in many areas such as sensor technologies, artificial intelligence (AI), networking, and more. This paper will introduce the reader to the technologies that build autonomous vehicles. It…
Safety assurance is a paramount factor in the large-scale deployment of various autonomous systems (e.g., self-driving vehicles). However, the execution of safety engineering practices and processes have been challenged by an increasing…
Trajectory prediction is one of the key components of the autonomous driving software stack. Accurate prediction for the future movement of surrounding traffic participants is an important prerequisite for ensuring the driving efficiency…
Designing, assuring and releasing safe automated vehicles is a highly interdisciplinary process. As complex systems, automated driving systems will inevitably be subject to emergent properties, i. e., the properties of the overall system…
In the realm of autonomous driving, the development and integration of highly complex and heterogeneous systems are standard practice. Modern vehicles are not monolithic systems; instead, they are composed of diverse hardware components,…
Conducting real road testing for autonomous driving algorithms can be expensive and sometimes impractical, particularly for small startups and research institutes. Thus, simulation becomes an important method for evaluating these…
Autonomous vehicles are one of the most popular and also fast-growing technologies in the world. As we go further, there are still a lot of challenges that are unsolved and may cause problems in the future when it comes to testing in real…
The way to full autonomy of public road vehicles requires the step-by-step replacement of the human driver, with the ultimate goal of replacing the driver completely. Eventually, the driving software has to be able to handle all situations…
In the past few years, we have observed a huge supply-demand gap for autonomous driving engineers. The core problem is that autonomous driving is not one single technology but rather a complex system integrating many technologies, and no…
This paper explores the role and challenges of Artificial Intelligence (AI) algorithms, specifically AI-based software elements, in autonomous driving systems. These AI systems are fundamental in executing real-time critical functions in…
As an envisaged future of transportation, self-driving cars are being discussed from various perspectives, including social, economical, engineering, computer science, design, and ethics. On the one hand, self-driving cars present new…
Game-based interactive driving simulations have emerged as versatile platforms for advancing decision-making algorithms in road transport mobility. While these environments offer safe, scalable, and engaging settings for testing driving…
This paper explores the emerging knowledge-driven autonomous driving technologies. Our investigation highlights the limitations of current autonomous driving systems, in particular their sensitivity to data bias, difficulty in handling…
Autonomous systems are emerging in many application domains. With the recent advancements in artificial intelligence and machine learning, sensor technology, perception algorithms and robotics, scenarios previously requiring strong human…
Engineering the software development process in robotics is one of the basic necessities towards industrial-strength service robotic systems. A major challenge is to make the step from code-driven to model-driven systems. This is essential…
The development of fully automated vehicles imposes new challenges in the development process and during the operation of such vehicles. As traditional design methods are not sufficient to account for the huge variety of scenarios which…
The latest advances in the design of vehicles with the adaptive level of automation pose new challenges in the vehicle-driver interaction. Safety requirements underline the need to explore optimal cockpit architectures with regard to driver…
The development dynamics of digital innovations for industry, business, and society are producing complex system conglomerates that can no longer be designed centrally and hierarchically in classic development processes. Instead, systems…