相关论文: A Systematic Literature Review on Safety of the In…
The use of machine learning (ML) is on the rise in many sectors of software development, and automotive software development is no different. In particular, Advanced Driver Assistance Systems (ADAS) and Automated Driving Systems (ADS) are…
As autonomous driving systems (ADSes) become increasingly complex and integral to daily life, the importance of understanding the nature and mitigation of software bugs in these systems has grown correspondingly. Addressing the challenges…
Assuring safety of artificial intelligence (AI) applied to safety-critical systems is of paramount importance. Especially since research in the field of automated driving shows that AI is able to outperform classical approaches, to handle…
Real-time safety metrics are important for the automated driving system (ADS) to assess the risk of driving situations and to assist the decision-making. Although a number of real-time safety metrics have been proposed in the literature,…
Semi-autonomous driving, as it is already available today and will eventually become even more accessible, implies the need for driver and automation system to reliably work together in order to ensure safe driving. A particular challenge…
Drivers are becoming increasingly reliant on advanced driver assistance systems (ADAS) as autonomous driving technology becomes more popular and developed with advanced safety features to enhance road safety. However, the increasing…
Autonomous Driving Systems (ADS) are critical dynamic reconfigurable agent systems whose specification and validation raises extremely challenging problems. The paper presents a multilevel semantic framework for the specification of ADS and…
With the growing technological advances in autonomous driving, the transport industry and research community seek to determine the impact that autonomous vehicles (AV) will have on consumers, as well as identify the different factors that…
This paper describes the comprehensive safety framework that underpinned the development, release process, and regulatory approval of BMW's first SAE Level 3 Automated Driving System. The framework combines established qualitative and…
Research into safety in autonomous and semi-autonomous vehicles has, so far, largely been focused on testing and validation through simulation. Due to the fact that failure of these autonomous systems is potentially life-endangering, formal…
Virtual testing of automated driving systems (ADS) has become an essential part of testing procedures for all automation levels. As ADS from automation level 3 and up are very complex, virtual testing for such systems is inevitable. The…
Existing Autonomous Driving Systems (ADS) independently make driving decisions, but they face two significant limitations. First, in complex scenarios, ADS may misinterpret the environment and make inappropriate driving decisions. Second,…
Nowadays, systematic security risk analysis plays a vital role in the automotive domain. The demand for advanced driver assistance systems and connectivity of vehicles to the internet makes cyber-security a crucial requirement for vehicle…
Autonomous driving vehicles aim to free the hands of vehicle operators, helping them to drive easier and faster, meanwhile, improving the safety of driving on the highway or in complex scenarios. Automated driving systems (ADS) are…
The rapid advancement of artificial intelligence and autonomous driving technologies has significantly propelled the development of autonomous vehicles (AVs). However, psychological barriers continue to impede widespread AV adoption,…
The rapid development of artificial intelligence, especially deep learning technology, has advanced autonomous driving systems (ADSs) by providing precise control decisions to counterpart almost any driving event, spanning from anti-fatigue…
The autonomous car technology promises to replace human drivers with safer driving systems. But although autonomous cars can become safer than human drivers this is a long process that is going to be refined over time. Before these vehicles…
Trust in robots has been gathering attention from multiple directions, as it has special relevance in the theoretical descriptions of human-robot interactions. It is essential for reaching high acceptance and usage rates of robotic…
In high-level Autonomous Driving (AD) systems, behavioral planning is in charge of making high-level driving decisions such as cruising and stopping, and thus highly securitycritical. In this work, we perform the first systematic study of…
Automated driving functions (ADFs) have become increasingly popular in recent years. However, their safety must be assured. Thus, the verification and validation of these functions is still an important open issue in research and…