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Lane change is a very demanding driving task and number of traffic accidents are induced by mistaken maneuvers. An automated lane change system has the potential to reduce driver workload and to improve driving safety. One challenge is how…
Frontier AI developers are increasingly deploying highly capable models internally to automate AI R&D, but these deployments currently face limited external oversight. It is essential, therefore, that developers provide evidence that…
Interaction-aware Autonomous Driving (IAAD) is a rapidly growing field of research that focuses on the development of autonomous vehicles (AVs) that are capable of interacting safely and efficiently with human road users. This is a…
The risen complexity of automotive systems requires new development strategies and methods to master the upcoming challenges. Traditional methods need thus to be changed by an increased level of automation, and a faster continuous…
Assessing drivers' interaction capabilities is crucial for understanding human driving behavior and enhancing the interactive abilities of autonomous vehicles. In scenarios involving strong interaction, existing metrics focused on…
Trust is a multilayered concept with critical relevance when it comes to introducing new technologies. Understanding how humans will interact with complex vehicle systems and preparing for the functional, societal and psychological aspects…
Autonomous systems are becoming increasingly prevalent in new vehicles. Due to their environmental friendliness and their remarkable capability to significantly enhance road safety, these vehicles have gained widespread recognition and…
The complex functional structure of driverless vehicles induces a multitude of potential malfunctions. Established approaches for a systematic hazard identification generate individual potentially hazardous scenarios for each identified…
Small-scale autonomous vehicle platforms provide a cost-effective environment for developing and testing advanced driving systems. However, specific configurations within this scale are underrepresented, limiting full awareness of their…
According to data from the United Nations, more than 3000 people have died each day in the world due to road traffic collision. Considering recent researches, the human error may be considered as the main responsible for these fatalities.…
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…
In the recent years, there has been a rush towards highly autonomous systems operating in public environments, such as automated driving of road vehicles, passenger shuttle systems and mobile robots. These systems, operating in…
Open-weight advanced AI models -- systems whose parameters are freely available for download and adaptation -- are reshaping the global AI landscape. As these models rapidly close the performance gap with closed alternatives, they enable…
In the last four years, the number of distinct autonomous vehicles platforms deployed in the streets of California increased 6-fold, while the reported accidents increased 12-fold. This can become a trend with no signs of subsiding as it is…
Autonomous driving has attracted significant attention from both academia and industries, which is expected to offer a safer and more efficient driving system. However, current autonomous driving systems are mostly based on a single…
The capabilities of automated vehicles are advancing rapidly, yet achieving full autonomy remains a significant challenge, requiring ongoing human cognition in decision-making processes. Incorporating human cognition into control algorithms…
As autonomous or semi-autonomous vehicles are deployed on the roads, they will have to eventually start communicating with each other in order to achieve increased efficiency and safety. Current approaches in the control of collaborative…
The purpose of this review paper is to present some recent results on the modeling and control of large systems of agents. We focus on particular applications where the agents are capable of independent actions instead of simply reacting to…
Autonomous driving is a complex undertaking. A common approach is to break down the driving task into individual subtasks through modularization. These sub-modules are usually developed and published separately. However, if these…
The recent proliferation of computing technologies (e.g., sensors, computer vision, machine learning, and hardware acceleration), and the broad deployment of communication mechanisms (e.g., DSRC, C-V2X, 5G) have pushed the horizon of…