Related papers: OpenCDA:An Open Cooperative Driving Automation Fra…
Simulative and scenario-based testing are crucial methods in the safety assurance for automated driving systems. To ensure that simulation results are reliable, the real world must be modeled with sufficient fidelity, including not only the…
Future mobility systems and their components are increasingly defined by their software. The complexity of these cooperative intelligent transport systems (C-ITS) and the everchanging requirements posed at the software require continual…
Coordination among connected and autonomous vehicles (CAVs) is advancing due to developments in control and communication technologies. However, much of the current work is based on oversimplified and unrealistic task-specific assumptions,…
We introduce M$^3$CAD, a comprehensive benchmark designed to advance research in generic cooperative autonomous driving. M$^3$CAD comprises 204 sequences with 30,000 frames. Each sequence includes data from multiple vehicles and different…
Teleoperation is a key enabler for future mobility, supporting Automated Vehicles in rare and complex scenarios beyond the capabilities of their automation. Despite ongoing research, no open source software currently combines Remote…
We describe a software framework and a hardware platform used in tandem for the design and analysis of robot autonomy algorithms in simulation and reality. The software, which is open source, containerized, and operating system (OS)…
Vision-language models have demonstrated impressive capabilities as computer-use agents (CUAs) capable of automating diverse computer tasks. As their commercial potential grows, critical details of the most capable CUA systems remain…
Recent research on testing autonomous driving agents has grown significantly, especially in simulation environments. The CARLA simulator is often the preferred choice, and the autonomous agents from the CARLA Leaderboard challenge are…
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,…
We describe the computing tasks involved in autonomous driving, examine existing autonomous driving computing platform implementations. To enable autonomous driving, the computing stack needs to simultaneously provide high performance, low…
This work describes the setup of an advanced technical infrastructure for collaborative software development (CDE) in large, distributed projects based on GitLab. We present its customization and extension, additional features and processes…
Search-based software testing (SBT) is an effective and efficient approach for testing automated driving systems (ADS). However, testing pipelines for ADS testing are particularly challenging as they involve integrating complex driving…
Control systems on unmanned vehicles are safety-critical systems whose requirements on reliability and safety are ever-increasing. Currently, testing a complex autonomous control system is an expensive and time-consuming process, which…
The infrastructure-vehicle cooperative autonomous driving approach depends on the cooperation between intelligent roads and intelligent vehicles. This approach is not only safer but also more economical compared to the traditional…
This paper introduces our Cyber-Physical Mobility Lab (CPM Lab). It is an open-source development environment for networked and autonomous vehicles with focus on networked decision-making, trajectory planning, and control. The CPM Lab hosts…
Developing safety and efficiency applications for Connected and Automated Vehicles (CAVs) require a great deal of testing and evaluation. The need for the operation of these systems in critical and dangerous situations makes the burden of…
With their potential to significantly reduce traffic accidents, enhance road safety, optimize traffic flow, and decrease congestion, autonomous driving systems are a major focus of research and development in recent years. Beyond these…
Scenario-based testing using simulations is a cornerstone of Autonomous Vehicles (AVs) software validation. So far, developers needed to choose between low-fidelity 2D simulators to explore the scenario space efficiently, and high-fidelity…
Commercial Adaptive Cruise Control (ACC) systems are increasingly available as standard options in modern vehicles. At the same time, still little information is openly available on how these systems actually operate and how different is…
The safety of single-vehicle autonomous driving technology is limited due to the limits of perception capability of on-board sensors. In contrast, vehicle-road collaboration technology can overcome those limits and improve the traffic…