Details
| Original language | English |
|---|---|
| Title of host publication | 35th IEEE Intelligent Vehicles Symposium |
| Subtitle of host publication | IV 2024 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 124-128 |
| Number of pages | 5 |
| ISBN (electronic) | 9798350348811 |
| ISBN (print) | 979-8-3503-4882-8 |
| Publication status | Published - 2 Jun 2024 |
| Event | 35th IEEE Intelligent Vehicles Symposium, IV 2024 - Jeju Island, Korea, Republic of Duration: 2 Jun 2024 → 5 Jun 2024 |
Publication series
| Name | IEEE Intelligent Vehicles Symposium, Proceedings |
|---|---|
| ISSN (Print) | 1931-0587 |
| ISSN (electronic) | 2642-7214 |
Abstract
Recent reports from the World Health Organization highlight that Vulnerable Road Users (VRUs) have been involved in over half of the road fatalities in recent years, with occlusion risk - a scenario where VRUs are hidden from drivers' view by obstacles like parked vehicles - being a critical contributing factor. To address this, we present a novel algorithm that quantifies occlusion risk based on the dynamics of both vehicles and VRUs. This algorithm has undergone testing and evaluation using a real-world dataset from German intersections. Additionally, we introduce the concept of Maximum Tracking Loss (MTL), which measures the longest consecutive duration a VRU remains untracked by any vehicle in a given scenario. Our study extends to examining the role of the Collective Perception Service (CPS) in VRU safety. CPS enhances safety by enabling vehicles to share sensor information, thereby potentially reducing occlusion risks. Our analysis reveals that a 25% market penetration of CPS-equipped vehicles can substantially diminish occlusion risks and significantly curtail MTL. These findings demonstrate how various scenarios pose different levels of risk to VRUs and how the deployment of Collective Perception can markedly improve their safety. Furthermore, they underline the efficacy of our proposed metrics to capture occlusion risk as a safety factor.
ASJC Scopus subject areas
- Computer Science(all)
- Computer Science Applications
- Engineering(all)
- Automotive Engineering
- Mathematics(all)
- Modelling and Simulation
Cite this
- Standard
- Harvard
- Apa
- Vancouver
- BibTeX
- RIS
35th IEEE Intelligent Vehicles Symposium: IV 2024. Institute of Electrical and Electronics Engineers Inc., 2024. p. 124-128 (IEEE Intelligent Vehicles Symposium, Proceedings).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Mitigating Vulnerable Road Users Occlusion Risk Via Collective Perception
T2 - 35th IEEE Intelligent Vehicles Symposium, IV 2024
AU - Wolff, Vincent Albert
AU - Xhoxhi, Edmir
N1 - Publisher Copyright: © 2024 IEEE.
PY - 2024/6/2
Y1 - 2024/6/2
N2 - Recent reports from the World Health Organization highlight that Vulnerable Road Users (VRUs) have been involved in over half of the road fatalities in recent years, with occlusion risk - a scenario where VRUs are hidden from drivers' view by obstacles like parked vehicles - being a critical contributing factor. To address this, we present a novel algorithm that quantifies occlusion risk based on the dynamics of both vehicles and VRUs. This algorithm has undergone testing and evaluation using a real-world dataset from German intersections. Additionally, we introduce the concept of Maximum Tracking Loss (MTL), which measures the longest consecutive duration a VRU remains untracked by any vehicle in a given scenario. Our study extends to examining the role of the Collective Perception Service (CPS) in VRU safety. CPS enhances safety by enabling vehicles to share sensor information, thereby potentially reducing occlusion risks. Our analysis reveals that a 25% market penetration of CPS-equipped vehicles can substantially diminish occlusion risks and significantly curtail MTL. These findings demonstrate how various scenarios pose different levels of risk to VRUs and how the deployment of Collective Perception can markedly improve their safety. Furthermore, they underline the efficacy of our proposed metrics to capture occlusion risk as a safety factor.
AB - Recent reports from the World Health Organization highlight that Vulnerable Road Users (VRUs) have been involved in over half of the road fatalities in recent years, with occlusion risk - a scenario where VRUs are hidden from drivers' view by obstacles like parked vehicles - being a critical contributing factor. To address this, we present a novel algorithm that quantifies occlusion risk based on the dynamics of both vehicles and VRUs. This algorithm has undergone testing and evaluation using a real-world dataset from German intersections. Additionally, we introduce the concept of Maximum Tracking Loss (MTL), which measures the longest consecutive duration a VRU remains untracked by any vehicle in a given scenario. Our study extends to examining the role of the Collective Perception Service (CPS) in VRU safety. CPS enhances safety by enabling vehicles to share sensor information, thereby potentially reducing occlusion risks. Our analysis reveals that a 25% market penetration of CPS-equipped vehicles can substantially diminish occlusion risks and significantly curtail MTL. These findings demonstrate how various scenarios pose different levels of risk to VRUs and how the deployment of Collective Perception can markedly improve their safety. Furthermore, they underline the efficacy of our proposed metrics to capture occlusion risk as a safety factor.
UR - http://www.scopus.com/inward/record.url?scp=85199811828&partnerID=8YFLogxK
U2 - 10.48550/arXiv.2404.0775
DO - 10.48550/arXiv.2404.0775
M3 - Conference contribution
AN - SCOPUS:85199811828
SN - 979-8-3503-4882-8
T3 - IEEE Intelligent Vehicles Symposium, Proceedings
SP - 124
EP - 128
BT - 35th IEEE Intelligent Vehicles Symposium
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 2 June 2024 through 5 June 2024
ER -