Connected vehicle-based road safety information system (CROSS): Framework and evaluation
Abstract
Valuable high-resolution data representing the maneuvering of both individual subject vehicles and adjacent vehicles are available in the era of the connected vehicle systems, which is also referred to as cooperative intelligent transportation systems (C-ITS). C-ITS can share useful traffic information between connected vehicles (CV) and between vehicles and infrastructure in support of vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) wireless communications. An excellent feature of a C-ITS pre-deployment project in Korean freeways that CVs are equipped with an in-vehicle forward collision warning system. This technical support provides a useful opportunity to evaluate crash risks more objectively and scientifically based on the analysis of vehicle interactions, which motivates our study. The purpose of this study is to develop a road safety information system based on the analysis of CV data. The proposed system estimates individual vehicle crash risks based on the crash potential index (CPI) and further utilizes them to develop a methodology for assessing road safety risks on freeways. High CPIs were observed in toll plaza area, recurrent congestion sections, and on and off-ramp areas. An encouraging result showed that the relationship between the estimated CPI and the actual crash frequencies was statistically meaningful. In addition, the impact of the CV market penetration rate (MPR) on the feasibility of the proposed road risk monitoring method was explored b…
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CPI's effectiveness in identifying road hazard points and segments in C-ITS environments has been validated.
“CPI's effectiveness in identifying road hazard points and segments in C-ITS environments has been validated [52,53].”
From Evaluation of Autonomous Driving Safety by Operational Design Domains (ODD) in Mixed Traffic (2024) · cites this paper as [53]
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Evaluation of Autonomous Driving Safety by Operational Design Domains (ODD) in Mixed Traffic
Kim, H., Ko, J., Oh, C., & Kim, S. (2024) · Sustainability · doi:10.3390/su16229672 · Cited by 18 · see citing works
“CPI’s effectiveness in identifying road hazard points and segments in C-ITS environments has been validated [52,53].”
Self-citation
- Authors
- Jo, Y., Jang, J., Park, S., & Oh, C.
- Affiliations
- Hanyang University (KR)
- Corresponding author
- Oh, Cheol
- Venue
- Accident Analysis & Prevention
- Publisher
- Elsevier BV
- Published
- 2021-03
- Volume
- 151
- Pages
- 105972
- ISSN
- 0001-4575 (ISSN-L)
- OpenAlex
- W3122799560
- Cited by
- 22
- References
- 0
- Citations by year
- 2026: 3 · 2025: 3 · 2024: 8 · 2023: 3 · 2022: 3 · 2021: 2
- FWCI
- 2.99
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Accident Analysis & Prevention (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Ministry of Land, Infrastructure and Transport (20TLRP-B148659-03)
- Topics
- Physical Sciences › Engineering › Safety, Risk, Reliability and Quality › Traffic and Road Safety
- Physical Sciences › Engineering › Control and Systems Engineering › Traffic control and management
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Vehicular Ad Hoc Networks (VANETs)
- Keywords
- connected vehicles, cooperative intelligent transport systems, crash risk estimation, vehicle-to-vehicle communication, vehicle-to-infrastructure communication, forward collision warning, freeway safety, toll plazas, market penetration rate, microscopic traffic simulation
- MeSH terms
- Accidents, Traffic, Computer Simulation, Humans, Information Systems, Safety
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