arXiv subjects

Pavlo Bazilinskyy

Publications and source records attributed to Pavlo Bazilinskyy.

6 recordsLinked to original sources

arXiv2026

A global dataset of continuous urban dashcam driving

We introduce CROWD (City Road Observations With Dashcams), a manually curated dataset of ordinary, minute scale, temporally contiguous, unedited, front facing urban dashcam segments screened and segmented from publicly available YouTube videos. CROWD is designed to support cross-domain robustness and interaction analysis by prioritising routine driving and explicitly excluding crashes, crash aftermath, and other edited or incident-focused content. The release contains 51,753 segment records spanning 20,275.56 hours (42,032 videos), covering 7,103 named inhabited places in 238 countries and territories across all six inhabited continents (Africa, Asia, Europe, North America, South America and Oceania), with segment level manual labels for time of day (day or night) and vehicle type. To lower the barrier for benchmarking, we provide per-segment CSV files of machine-generated detections for all 80 MS-COCO classes produced with YOLOv11x, together with segment-local multi-object tracks (BoT-SORT); e.g. person, bicycle, motorcycle, car, bus, truck, traffic light, stop sign, etc. CROWD is distributed as video identifiers with segment boundaries and derived annotations, enabling reproducible research without redistributing the underlying videos.

cs.CV↗

arXiv2026

MRDrive: An Open Source Mixed Reality Driving Simulator for Automotive User Research

Designing and evaluating in-vehicle interfaces requires experimental platforms that combine ecological validity with experimental control. Driving simulators are widely used for this purpose. However, they face a fundamental trade-off: high-fidelity physical simulators are costly and difficult to adapt, while virtual reality simulators provide flexibility at the expense of physical interaction with the vehicle. In this work, we present MRDrive, an open mixed-reality driving simulator designed to support HCI research on in-vehicle interaction, attention, and explainability in manual and automated driving contexts. MRDrive enables drivers and passengers to interact with a real vehicle cabin while being fully immersed in a virtual driving environment. We demonstrate the capabilities of MRDrive through a small pilot study that illustrates how the simulator can be used to collect and analyze eye-tracking and touch interaction data in an automated driving scenario. MRDRive is available at: https://github.com/ciao-group/mrdrive

cs.HC↗

arXiv2025

Psychoacoustic assessment of synthetic sounds for electric vehicles in a virtual reality experiment

The growing adoption of electric vehicles, known for their quieter operation compared to internal combustion engine vehicles, raises concerns about their detectability, particularly for vulnerable road users. To address this, regulations mandate the inclusion of exterior sound signals for electric vehicles, specifying minimum sound pressure levels at low speeds. These synthetic exterior sounds are often used in noisy urban environments, creating the challenge of enhancing detectability without introducing excessive noise annoyance. This study investigates the design of synthetic exterior sound signals that balance high noticeability with low annoyance. An audiovisual experiment with 14 participants was conducted using 15 virtual reality scenarios featuring a passing car. The scenarios included various sound signals, such as pure, intermittent, and complex tones at different frequencies. Two baseline cases, a diesel engine and only tyre noise, were also tested. Participants rated sounds for annoyance, noticeability, and informativeness using 11-point ICBEN scales. The findings highlight how psychoacoustic sound quality metrics predict annoyance ratings better than conventional sound metrics, providing insight into optimising sound design for electric vehicles. By improving pedestrian safety while minimising noise pollution, this research supports the development of effective and user-friendly exterior sound standards for electric vehicles.

cs.HC↗

arXiv2025

Quo-Vadis Multi-Agent Automotive Research? Insights from a Participatory Workshop and Questionnaire

The transition to mixed-traffic environments that involve automated vehicles, manually operated vehicles, and vulnerable road users presents new challenges for human-centered automotive research. Despite this, most studies in the domain focus on single-agent interactions. This paper reports on a participatory workshop (N = 15) and a questionnaire (N = 19) conducted during the AutomotiveUI '24 conference to explore the state of multi-agent automotive research. The participants discussed methodological challenges and opportunities in real-world settings, simulations, and computational modeling. Key findings reveal that while the value of multi-agent approaches is widely recognized, practical and technical barriers hinder their implementation. The study highlights the need for interdisciplinary methods, better tools, and simulation environments that support scalable, realistic, and ethically informed multi-agent research.

cs.HC↗

arXiv2024

Exploring Holistic HMI Design for Automated Vehicles: Insights from a Participatory Workshop to Bridge In-Vehicle and External Communication

Human-Machine Interfaces (HMIs) for automated vehicles (AVs) are typically divided into two categories: internal HMIs for interactions within the vehicle, and external HMIs for communication with other road users. In this work, we examine the prospects of bridging these two seemingly distinct domains. Through a participatory workshop with automotive user interface researchers and practitioners, we facilitated a critical exploration of holistic HMI design by having workshop participants collaboratively develop interaction scenarios involving AVs, in-vehicle users, and external road users. The discussion offers insights into the escalation of interface elements as an HMI design strategy, the direct interactions between different users, and an expanded understanding of holistic HMI design. This work reflects a collaborative effort to understand the practical aspects of this holistic design approach, offering new perspectives and encouraging further investigation into this underexplored aspect of automotive user interfaces.

cs.HC↗

arXiv2024

Holistic HMI Design for Automated Vehicles: Bridging In-Vehicle and External Communication

As the field of automated vehicles (AVs) advances, it has become increasingly critical to develop human-machine interfaces (HMI) for both internal and external communication. Critical dialogue is emerging around the potential necessity for a holistic approach to HMI designs, which promotes the integration of both in-vehicle user and external road user perspectives. This approach aims to create a unified and coherent experience for different stakeholders interacting with AVs. This workshop seeks to bring together designers, engineers, researchers, and other stakeholders to delve into relevant use cases, exploring the potential advantages and challenges of this approach. The insights generated from this workshop aim to inform further design and research in the development of coherent HMIs for AVs, ultimately for more seamless integration of AVs into existing traffic.

cs.HC↗