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Investigating the role of Advanced Driver Assistance Systems (ADAS) in reducing sideswipe collisions in rural Ohio.

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Τίτλος: Investigating the role of Advanced Driver Assistance Systems (ADAS) in reducing sideswipe collisions in rural Ohio.
Συγγραφείς: Ngereza A; Department of Civil and Environmental Engineering, Cleveland State University, 2121 Euclid Avenue, Cleveland, OH 44115, United States. Electronic address: a.ngereza@vikes.csuohio.edu., Kutela B; Associate Research Engineer, Texas A&M Transportation Institute, 701 N Post Oak Ln # 430, Houston, TX 77024, United States. Electronic address: b-kutela@tti.tamu.edu., Ibrahim I; Undergraduate Research Assistant, Department of Civil and Environmental Engineering, Cleveland State University, 2121 Euclid Avenue, Cleveland, OH 44115, United States. Electronic address: i.ibrahim16@vikes.csuohio.edu., Kalambay P; Department of Transportation Studies, Texas Southern University, 3100 Cleburne St. Tech #208, Houston, TX 77004, United States. Electronic address: panick.kalambay@tsu.edu., Masanja N; Department of Electrical and Computer Engineering, Cleveland State University, 2121 Euclid Avenue, Cleveland, OH 44115, United States. Electronic address: n.masanja@vikes.csuohio.edu., Kidando E; Department of Civil & Environmental Engineering, Cleveland State University, 2121 Euclid Avenue, Cleveland, OH 44115, United States. Electronic address: e.kidando@csuohio.edu., Kitali A; School of Engineering and Technology, University of Washington Tacoma, Tacoma, WA 98402, United States. Electronic address: akitali@uw.edu.
Πηγή: Journal of safety research [J Safety Res] 2026 Sep; Vol. 98, pp. 599-611. Date of Electronic Publication: 2026 Aug 27.
Τύπος έκδοσης: Journal Article; Research Support, Non-U.S. Gov't
Γλώσσα: English
Στοιχεία περιοδικού: Publisher: Pergamon Press Country of Publication: United States NLM ID: 1264241 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1879-1247 (Electronic) Linking ISSN: 00224375 NLM ISO Abbreviation: J Safety Res Subsets: MEDLINE
Imprint Name(s): Publication: Elmsford, NY : Pergamon Press
Original Publication: [Chicago] National Safety Council.
Ιατρικοί όροι (MeSH): Accidents, Traffic*/prevention & control , Accidents, Traffic*/statistics & numerical data , Rural Population*/statistics & numerical data , Automobile Driving*, Ohio ; Humans ; Environment Design
Περίληψη: Introduction: Rural roadways continue to experience disproportionately high fatality rates per vehicle-mile traveled compared with urban facilities, underscoring persistent safety challenges that demand targeted interventions. Among the most prevalent crash types on rural roads are sideswipe collisions, frequently attributed to driver error, limited roadway delineation, and reduced situational awareness. Advanced Driver Assistance Systems (ADAS), including Blind Spot Warning (BSW), Lane Departure Warning (LDW), and Lane Keeping Assistance (LKA), offer potential countermeasures by enhancing driver perception and lateral control; however, existing effectiveness evidence is predominantly frequency-focused and urban-aggregate, and the severity-conditional performance of these systems in rural sideswipe crashes remains unquantified.
Method: This study evaluates the influence of ADAS on the severity of rural sideswipe crashes using data from 49 rural Ohio counties for 2017-2023. A 50-foot spatial buffer approach matched each ADAS-equipped crash with nearby conventional-vehicle crashes to control for roadway and environmental context, and a Bayesian Network was applied to model the dependencies among driver, vehicle, roadway, and environmental factors. Model credibility was assessed through repeated cross-validation, hold-out discrimination testing, and bootstrap analyses of structural stability and conditional probabilities.
Results: The results reveal a clear hierarchy of evidence: driving under the influence and higher speed environments were the structurally robust determinants of severe outcomes, whereas ADAS-severity associations were small and condition-dependent, protective when systems were operating and under adverse weather, but unfavorable in dark conditions consistent with degraded camera-based sensing on unlit, poorly marked rural roads.
Conclusions and Practical Applications: The findings indicate that ADAS benefits in rural settings are contingent on system operation and sensing conditions, supporting safety strategies that pair ADAS adoption with pavement-marking maintenance, roadway lighting, driver education on system limitations, and sustained enforcement of impaired-driving and speed laws.
(Copyright © 2026 The Author(s). Published by Elsevier Ltd.. All rights reserved.)
Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Contributed Indexing: Keywords: Advanced Driver Assistance System (ADAS); Rural Area; Rural Safety; Sideswipe
Entry Date(s): Date Created: 20260915 Date Completed: 20260915 Latest Revision: 20261006
Update Code: 20261006
DOI: 10.1016/j.jsr.2026.08.012
PMID: 42744509
Βάση Δεδομένων: MEDLINE
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  Data: Investigating the role of Advanced Driver Assistance Systems (ADAS) in reducing sideswipe collisions in rural Ohio.
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  Data: <searchLink fieldCode="AU" term="%22Ngereza+A%22">Ngereza A</searchLink>; Department of Civil and Environmental Engineering, Cleveland State University, 2121 Euclid Avenue, Cleveland, OH 44115, United States. Electronic address: a.ngereza@vikes.csuohio.edu.<br /><searchLink fieldCode="AU" term="%22Kutela+B%22">Kutela B</searchLink>; Associate Research Engineer, Texas A&M Transportation Institute, 701 N Post Oak Ln # 430, Houston, TX 77024, United States. Electronic address: b-kutela@tti.tamu.edu.<br /><searchLink fieldCode="AU" term="%22Ibrahim+I%22">Ibrahim I</searchLink>; Undergraduate Research Assistant, Department of Civil and Environmental Engineering, Cleveland State University, 2121 Euclid Avenue, Cleveland, OH 44115, United States. Electronic address: i.ibrahim16@vikes.csuohio.edu.<br /><searchLink fieldCode="AU" term="%22Kalambay+P%22">Kalambay P</searchLink>; Department of Transportation Studies, Texas Southern University, 3100 Cleburne St. Tech #208, Houston, TX 77004, United States. Electronic address: panick.kalambay@tsu.edu.<br /><searchLink fieldCode="AU" term="%22Masanja+N%22">Masanja N</searchLink>; Department of Electrical and Computer Engineering, Cleveland State University, 2121 Euclid Avenue, Cleveland, OH 44115, United States. Electronic address: n.masanja@vikes.csuohio.edu.<br /><searchLink fieldCode="AU" term="%22Kidando+E%22">Kidando E</searchLink>; Department of Civil & Environmental Engineering, Cleveland State University, 2121 Euclid Avenue, Cleveland, OH 44115, United States. Electronic address: e.kidando@csuohio.edu.<br /><searchLink fieldCode="AU" term="%22Kitali+A%22">Kitali A</searchLink>; School of Engineering and Technology, University of Washington Tacoma, Tacoma, WA 98402, United States. Electronic address: akitali@uw.edu.
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  Data: Introduction: Rural roadways continue to experience disproportionately high fatality rates per vehicle-mile traveled compared with urban facilities, underscoring persistent safety challenges that demand targeted interventions. Among the most prevalent crash types on rural roads are sideswipe collisions, frequently attributed to driver error, limited roadway delineation, and reduced situational awareness. Advanced Driver Assistance Systems (ADAS), including Blind Spot Warning (BSW), Lane Departure Warning (LDW), and Lane Keeping Assistance (LKA), offer potential countermeasures by enhancing driver perception and lateral control; however, existing effectiveness evidence is predominantly frequency-focused and urban-aggregate, and the severity-conditional performance of these systems in rural sideswipe crashes remains unquantified.<br />Method: This study evaluates the influence of ADAS on the severity of rural sideswipe crashes using data from 49 rural Ohio counties for 2017-2023. A 50-foot spatial buffer approach matched each ADAS-equipped crash with nearby conventional-vehicle crashes to control for roadway and environmental context, and a Bayesian Network was applied to model the dependencies among driver, vehicle, roadway, and environmental factors. Model credibility was assessed through repeated cross-validation, hold-out discrimination testing, and bootstrap analyses of structural stability and conditional probabilities.<br />Results: The results reveal a clear hierarchy of evidence: driving under the influence and higher speed environments were the structurally robust determinants of severe outcomes, whereas ADAS-severity associations were small and condition-dependent, protective when systems were operating and under adverse weather, but unfavorable in dark conditions consistent with degraded camera-based sensing on unlit, poorly marked rural roads.<br />Conclusions and Practical Applications: The findings indicate that ADAS benefits in rural settings are contingent on system operation and sensing conditions, supporting safety strategies that pair ADAS adoption with pavement-marking maintenance, roadway lighting, driver education on system limitations, and sustained enforcement of impaired-driving and speed laws.<br /> (Copyright © 2026 The Author(s). Published by Elsevier Ltd.. All rights reserved.)
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  Data: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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