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External human-machine interface (eHMI) is considered as a new explicit communication method for pedestrian-AV interactions, particularly in encounter scenarios. Pedestrians without prior negotiation experience with eHMI may misinterpret…
Modern driver assistance systems rely on a wide range of sensors (RADAR, LIDAR, ultrasound and cameras) for scene understanding and prediction. These sensors are typically used for detecting traffic participants and scene elements required…
In this work, we tackle two vital tasks in automated driving systems, i.e., driver intent prediction and risk object identification from egocentric images. Mainly, we investigate the question: what would be good road scene-level…
A major challenge in the safety assessment of automated vehicles is to ensure that risk for all traffic participants is as low as possible. A concept that is becoming increasingly popular for testing in automated driving is scenario-based…
Perception and prediction modules are critical components of autonomous driving systems, enabling vehicles to navigate safely through complex environments. The perception module is responsible for perceiving the environment, including…
It is essential to help drivers have appropriate understandings of level 2 automated driving systems for keeping driving safety. A human machine interface (HMI) was proposed to present real time results of image recognition by the automated…
Pedestrians are exposed to risk of death or serious injuries on roads, especially unsignalized crosswalks, for a variety of reasons. To date, an extensive variety of studies have reported on vision based traffic safety system. However, many…
For autonomous vehicles to safely share the road with human drivers, autonomous vehicles must abide by specific "road rules" that human drivers have agreed to follow. "Road rules" include rules that drivers are required to follow by law --…
In two intersecting many-particle streams, one can often find the emergence of oscillatory patterns. Here, we investigate the interaction of pedestrians with vehicles, when they try to cross a road. A numerical study of this coupled…
Awareness of the road scene is an essential component for both autonomous vehicles and Advances Driver Assistance Systems and is gaining importance both for the academia and car companies. This paper presents a way to learn a semantic-aware…
Automotive User Interface (AutoUI) is relatively a new discipline in the context of both Transportation Engineering and Human Machine Interaction (HMI). It covers various HMI aspects both inside and outside vehicle ranging from operating…
In this paper, we investigate the problem of anticipating future dynamics, particularly the future location of other vehicles and pedestrians, in the view of a moving vehicle. We approach two fundamental challenges: (1) the partial…
Pedestrian detection is a critical task in autonomous driving, aimed at enhancing safety and reducing risks on the road. Over recent years, significant advancements have been made in improving detection performance. However, these…
With the recent development of autonomous vehicle technology, there have been active efforts on the deployment of this technology at different scales that include urban and highway driving. While many of the prototypes showcased have been…
The challenge of navigation in environments with dynamic objects continues to be a central issue in the study of autonomous agents. While predictive methods hold promise, their reliance on precise state information makes them less practical…
The simulation of vehicular traffic as well as pedestrian dynamics meanwhile both have a decades long history. The success of this conference series, PED and others show that the interest in these topics is still strongly increasing. This…
Pedestrian safety is a critical public health priority, with pedestrian fatalities accounting for 18% of all U.S. traffic deaths in 2022. The rising prevalence of distracted walking, exacerbated by mobile device use, poses significant risks…
Fine localization is a crucial task for autonomous vehicles. Although many algorithms have been explored in the literature for this specific task, the goal of getting accurate results from commodity sensors remains a challenge. As…
The lateral position of vehicles within their lane is a decisive factor for the range of vision of vehicle sensors. This, in turn, is crucial for a vehicle's ability to perceive its environment and gain a high situational awareness by…
Compared to a manual driving vehicle (MV), an automated driving vehicle lacks a way to communicate with the pedestrian through the driver when it interacts with the pedestrian because the driver usually does not participate in driving…