Related papers: Detecting Intentions of Vulnerable Road Users Base…
In the driving scene, the road agents usually conduct frequent interactions and intention understanding of the surroundings. Ego-agent (each road agent itself) predicts what behavior will be engaged by other road users all the time and…
Traditional approaches to prediction of future trajectory of road agents rely on knowing information about their past trajectory. This work rather relies only on having knowledge of the current state and intended direction to make…
While measures, such as traffic calming and advance driver assistance systems, can improve safety for Vulnerable Road Users (VRUs), their effectiveness ultimately relies on the responsible behavior of drivers and pedestrians who must adhere…
According to the World Health Organization, the involvement of Vulnerable Road Users (VRUs) in traffic accidents remains a significant concern, with VRUs accounting for over half of traffic fatalities. The increase of automation and…
In order to be globally deployed, autonomous cars must guarantee the safety of pedestrians. This is the reason why forecasting pedestrians' intentions sufficiently in advance is one of the most critical and challenging tasks for autonomous…
Employing skin-like tactile sensors on robots enhances both the safety and usability of collaborative robots by adding the capability to detect human contact. Unfortunately, simple binary tactile sensors alone cannot determine the context…
Human emotion detection in automated vehicles helps to improve comfort and safety. Research in the automotive domain focuses a lot on sensing drivers' drowsiness and aggression. We present a new form of implicit driver-vehicle cooperation,…
Predicting the motion of a driver's vehicle is crucial for advanced driving systems, enabling detection of potential risks towards shared control between the driver and automation systems. In this paper, we propose a variational neural…
Autonomous vehicles (AVs) are expected to be commercially available in the near future, leading to mixed autonomy traffic consisting of both AVs and human-driven vehicles (HVs). Although numerous studies have shown that AVs can be deployed…
Rapid advancements in driver-assistance technology will lead to the integration of fully autonomous vehicles on our roads that will interact with other road users. To address the problem that driverless vehicles make interaction through eye…
Walking as a form of active travel is essential in promoting sustainable transport. It is thus crucial to accurately predict pedestrian crossing intention and avoid collisions, especially with the advent of autonomous and advanced…
In future traffic scenarios, vehicles and other traffic participants will be interconnected and equipped with various types of sensors, allowing for cooperation based on data or information exchange. This article presents an approach to…
With the substantial growth of logistics businesses the need for larger and more automated warehouses increases, thus giving rise to fully robotized shop-floors with mobile robots in charge of transporting and distributing goods. However,…
Pedestrian intention prediction needs to be accurate for autonomous vehicles to navigate safely in urban environments. We present a lightweight, socially informed architecture for pedestrian intention prediction. It fuses four behavioral…
When pedestrians encounter vehicles, they typically stop and wait for a signal from the driver to either cross or wait. What happens when the car is autonomous and there isn't a human driver to signal them? This paper seeks to address this…
At the moment, urban mobility research and governmental initiatives are mostly focused on motor-related issues, e.g. the problems of congestion and pollution. And yet, we can not disregard the most vulnerable elements in the urban…
Micromobility is a growing mode of transportation, raising new challenges for traffic safety and planning due to increased interactions in areas where vulnerable road users (VRUs) share the infrastructure with micromobility, including…
Ships, or vessels, often sail in and out of cluttered environments over the course of their trajectories. Safe navigation in such cluttered scenarios requires an accurate estimation of the intent of neighboring vessels and their effect on…
Mobile robots are traditionally developed to be reactive and avoid collisions with surrounding humans, often moving in unnatural ways without following social protocols, forcing people to behave very differently from human-human interaction…
Autonomous vehicles navigate in dynamically changing environments under a wide variety of conditions, being continuously influenced by surrounding objects. Modelling interactions among agents is essential for accurately forecasting other…