Related papers: OpenSBT: A Modular Framework for Search-based Test…
Developing autonomous driving systems (ADSs) involves generating and storing extensive log data from test drives, which is essential for verification, research, and simulation. However, these high-frequency logs, recorded over varying…
Our work introduces a module for assessing the trajectory safety of autonomous vehicles in dynamic environments marked by high uncertainty. We focus on occluded areas and occluded traffic participants with limited information about…
Although Cooperative Driving Automation (CDA) has attracted considerable attention in recent years, there remain numerous open challenges in this field. The gap between existing simulation platforms that mainly concentrate on single-vehicle…
Autonomous Driving Systems (ADS) are safety-critical, where failures can be severe. While Metamorphic Testing (MT) is effective for fault detection in ADS, existing methods rely heavily on manual effort and lack automation. We present…
Search-Based Software Testing (SBST) is the application of optimization algorithms to problems in software testing. In previous work, we have implemented and evaluated Interactive Search-Based Software Testing (ISBST) tool prototypes, with…
The rapidly evolving field of autonomous driving systems (ADSs) is full of promise. However, in order to fulfil these promises, ADSs need to be safe in all circumstances. This paper introduces ISS-Scenario, an autonomous driving testing…
Automated driving systems (ADS) are expected to be reliable and robust against a wide range of driving scenarios. Their decisions, first and foremost, must be well understood. Understanding a decision made by ADS is a great challenge,…
Advanced driver assistance systems (ADAS) often rely on deep neural networks to interpret driving images and support vehicle control. Although reliable under nominal conditions, these systems remain vulnerable to input variations and…
Autonomous Driving Systems (ADS) use complex decision-making (DM) models with multimodal sensory inputs, making rigorous validation and verification (V&V) essential for safety and reliability. These models pose challenges in diagnosing…
Ensuring the safety and reliability of Automated Driving Systems (ADS) remains a critical challenge, as traditional verification methods such as large-scale on-road testing are prohibitively costly and time-consuming.To address…
Search-Based Software Engineering (SBSE) is a promising paradigm that exploits the computational search to optimize different processes when engineering complex software systems. Self-adaptive system (SAS) is one category of such complex…
One of the major impediments in deployment of Autonomous Driving Systems (ADS) is their safety and reliability. The primary reason for the complexity of testing ADS is that it operates in an open world characterized by its…
In-vehicle communication technologies are evolving. While today's cars are equipped with fieldbusses to interconnect the various electronic control units, next generation vehicles have timing and bandwidth requirements that exceed the…
Closed-loop simulation environments play a crucial role in the validation and enhancement of autonomous driving systems (ADS). However, certain challenges warrant significant attention, including balancing simulation accuracy with duration,…
Automated driving systems (ADSs) promise a safe, comfortable and efficient driving experience. However, fatalities involving vehicles equipped with ADSs are on the rise. The full potential of ADSs cannot be realized unless the robustness of…
Automated Driving Systems (ADSs) are being manufactured at an accelerated rate, leading to improvements in traffic safety, reduced energy consumption, pollution, and congestion. ADS relies on various data streams from onboard sensors,…
Search-based Software Testing (SBST) can automatically generate test cases to search for requirements violations. Unlike manual test case development, it can generate a substantial number of test cases in a limited time. However, SBST does…
The automotive industry is experiencing a transition from assisted to highly automated driving. New concepts for validation of Automated Driving System (ADS) include amongst other a shift from a "technology based" approach to a "scenario…
Autonomous vehicles (AV) depend on the sensors like RADAR and camera for the perception of the environment, path planning, and control. With the increasing autonomy and interactions with the complex environment, there have been growing…
Automated Driving Systems (ADS) hold great potential to increase safety, mobility, and equity. However, without public acceptance, none of these promises can be fulfilled. To engender public trust, many entities in the ADS community…