V2P Collision Warnings for Distracted Pedestrians: A Comparative Study with Traditional Auditory Alerts

Novel Certad Hernandez; Enrico Del Re; Joshua Varughese; Cristina Olaverri-Monreal

doi:10.1109/IV64158.2025.11097625

V2P Collision Warnings for Distracted Pedestrians: A Comparative Study with Traditional Auditory Alerts

^*Corresponding author for this work

Department Intelligent Transport Systems

Research output: Chapter in Book/Report/Conference proceeding › Conference proceedings › peer-review

Abstract

This study assesses a Vehicle-to-Pedestrian (V2P) collision warning system compared to conventional vehicle-issued auditory alerts in a real-world scenario simulating a vehicle on a fixed track, characterized by limited maneuverability and the need for timely pedestrian response. The results from analyzing speed variations show that V2P warnings are particularly effective for pedestrians distracted by phone use (gaming or listening to music), highlighting the limitations of auditory alerts in noisy environments. The findings suggest that V2P technology offers a promising approach to improving pedestrian safety in urban areas

Original language	English
Title of host publication	20225 IEEE Intelligent Vehicles Symposium (IV)
Place of Publication	Cluj, Romania
Publisher	IEEE
Pages	1340-1345
Number of pages	6
Edition	1
ISBN (Electronic)	9798331538033
DOIs	https://doi.org/10.1109/IV64158.2025.11097625
Publication status	Published - 2025

Publication series

Name	IEEE Intelligent Vehicles Symposium, Proceedings
ISSN (Print)	1931-0587
ISSN (Electronic)	2642-7214

Fields of science

102003 Image processing
102002 Augmented reality
102001 Artificial intelligence
102029 Practical computer science
211911 Sustainable technologies
102021 Pervasive computing
303 Health Sciences
303008 Ergonomics
211917 Technology assessment
102026 Virtual reality
501026 Psychology of perception
501025 Traffic psychology
102024 Usability research
102013 Human-computer interaction
202034 Control engineering
202003 Automation
211902 Assistive technologies
201306 Traffic telematics
201305 Traffic engineering
202031 Network engineering
202030 Communication engineering
102 Computer Sciences
102034 Cyber-physical systems
203 Mechanical Engineering
202040 Transmission technology
102019 Machine learning
211909 Energy technology
202 Electrical Engineering, Electronics, Information Engineering
202038 Telecommunications
211908 Energy research
202041 Computer engineering
501 Psychology
202037 Signal processing
102015 Information systems
202036 Sensor systems
501030 Cognitive science
202035 Robotics
203004 Automotive technology

JKU Focus areas

Sustainable Development: Responsible Technologies and Management
Digital Transformation

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/IV64158.2025.11097625

Cite this

@inproceedings{339488041dce4824a873939093e2edb0,

title = "V2P Collision Warnings for Distracted Pedestrians: A Comparative Study with Traditional Auditory Alerts",

abstract = "This study assesses a Vehicle-to-Pedestrian (V2P) collision warning system compared to conventional vehicle-issued auditory alerts in a real-world scenario simulating a vehicle on a fixed track, characterized by limited maneuverability and the need for timely pedestrian response. The results from analyzing speed variations show that V2P warnings are particularly effective for pedestrians distracted by phone use (gaming or listening to music), highlighting the limitations of auditory alerts in noisy environments. The findings suggest that V2P technology offers a promising approach to improving pedestrian safety in urban areas",

author = "\{Certad Hernandez\}, Novel and \{Del Re\}, Enrico and Joshua Varughese and Cristina Olaverri-Monreal",

year = "2025",

doi = "10.1109/IV64158.2025.11097625",

language = "English",

series = "IEEE Intelligent Vehicles Symposium, Proceedings",

publisher = "IEEE",

pages = "1340--1345",

booktitle = "20225 IEEE Intelligent Vehicles Symposium (IV)",

edition = "1",

}

V2P Collision Warnings for Distracted Pedestrians: A Comparative Study with Traditional Auditory Alerts. / Certad Hernandez, Novel ; Del Re, Enrico ; Varughese, Joshua et al.
20225 IEEE Intelligent Vehicles Symposium (IV). 1. ed. Cluj, Romania: IEEE, 2025. p. 1340-1345 (IEEE Intelligent Vehicles Symposium, Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference proceedings › peer-review

TY - GEN

T1 - V2P Collision Warnings for Distracted Pedestrians: A Comparative Study with Traditional Auditory Alerts

AU - Certad Hernandez, Novel

AU - Del Re, Enrico

AU - Varughese, Joshua

AU - Olaverri-Monreal, Cristina

PY - 2025

Y1 - 2025

N2 - This study assesses a Vehicle-to-Pedestrian (V2P) collision warning system compared to conventional vehicle-issued auditory alerts in a real-world scenario simulating a vehicle on a fixed track, characterized by limited maneuverability and the need for timely pedestrian response. The results from analyzing speed variations show that V2P warnings are particularly effective for pedestrians distracted by phone use (gaming or listening to music), highlighting the limitations of auditory alerts in noisy environments. The findings suggest that V2P technology offers a promising approach to improving pedestrian safety in urban areas

AB - This study assesses a Vehicle-to-Pedestrian (V2P) collision warning system compared to conventional vehicle-issued auditory alerts in a real-world scenario simulating a vehicle on a fixed track, characterized by limited maneuverability and the need for timely pedestrian response. The results from analyzing speed variations show that V2P warnings are particularly effective for pedestrians distracted by phone use (gaming or listening to music), highlighting the limitations of auditory alerts in noisy environments. The findings suggest that V2P technology offers a promising approach to improving pedestrian safety in urban areas

UR - https://www.scopus.com/pages/publications/105014240417

U2 - 10.1109/IV64158.2025.11097625

DO - 10.1109/IV64158.2025.11097625

M3 - Conference proceedings

T3 - IEEE Intelligent Vehicles Symposium, Proceedings

SP - 1340

EP - 1345

BT - 20225 IEEE Intelligent Vehicles Symposium (IV)

PB - IEEE

CY - Cluj, Romania

ER -

V2P Collision Warnings for Distracted Pedestrians: A Comparative Study with Traditional Auditory Alerts

Abstract

Publication series

Fields of science

JKU Focus areas

UN SDGs

Access to Document

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Research output

V2P Collision Warnings for Distracted Pedestrians: A Comparative Study with Traditional Auditory Alerts

Cite this