Journal of Safety Research最新文献

Introduction: This research implements the steps of developing or identifying leading indicators (LIs) delineated in a previously published conceptual model to test its practicality on case study data. Concomitant objectives are (a) to systematically review extant literature of ‘LIs development and identification’ to develop an analytical framework for identifying LIs; and to identify LIs from case study incident reports and normative documents using the framework. Method: To empirically validate the conceptual model, a two staged data analysis process was adopted: (1) a theoretical work stage, where pertinent literature was studied through systematic literature review using Scopus and Web of Science databases and a detailed framework analysis; and (2) practical work stage, where an inductively developed analytical framework and insights gained from the theoretical work stage were applied to real-life case study data and their apposite normative documents. Random sampling was used to select 12 different case studies of accidents from a private database of 97 case studies. In total, 2,423 LIs were identified from extant literature and through framework analysis using the bespoke analytical framework generated, a total of 484 LIs were identified from a combination of selected case study materials and their relevant normative documents. All these 484 newly developed LIs were contrasted with a compilation of the previously published 2,423 LIs in the literature. Results: Consequently, a total of 232 LIs out of 484 were recognized as entirely new and novel. These LIs were then thematically grouped into 19 clusters for brevity. A novel analytical framework for identifying new LIs was inductively developed. The framework enables identification of LIs from a qualitative dataset and classify them into eight types of LIs. Practical Applications: This novel research constitutes the first attempt to identify and validate LIs via the use of an analytical framework and real-life case study data.

Introduction: This study investigates the mitigating effect of passive safe poles on the severity of run-off-road crashes in Belgium. Method: Run-off-road (ROR) crash data were collected from 2015 to 2020 on sections of roads in Flanders, and multinomial and mixed logit models were estimated using the driver injury and the most severely injured occupant as outcome variables. Results: Our results align with previous findings reported in the literature on ROR crash severity in several distinct settings. Most importantly, findings from this study provide evidence that High Energy absorbing passive safe poles (CEN 12767 HE compliant) contribute towards minor injuries in ROR crashes. The study also indicates the importance of protecting errant vehicles from traditional poles, which are linked to severe injuries. Conclusions: Our findings offer relevant insights for road safety agencies to enhance roadside design policies and implement forgiving roadsides. Practical Applications: Our results support the current Flemish policy concerning the installation of lighting columns and the “forgiving roadside” concept to mitigate ROR crash severity on Belgian roads. Further developments in road inventory systems should provide additional and enhanced data on roadside characteristics and crashes. These data will create the basis for further research, leading to more accurate recommendations on increasing roadside safety most effectively.

Introduction: Advanced vehicle technologies (AVTs) can reduce the risk of crashing and serious injuries however their uptake remains low amongst older drivers. A discrete choice experiment (DCE) was used to investigate what vehicle features, including AVTs, are preferred in vehicle purchasing decision in older drivers. Methods: Older drivers (≥65 years) completed a DCE containing 12 choice sets, with 2 vehicles to choose from, described by 4 attributes: Access, Fuel Efficiency, Cost, and AVTs. Conditional logistic models adjusting for age and sex, and then expanded to include a priori interactive terms for socio economic status, self-rated mobility limitations and anxiety/depression, and sex were run in R v4.2.2 with odds ratio (ORs) and 95% confidence intervals (Cls) reported. Marginal willingness to pay for more AVTs was estimated. Results: 133 participants (mean age: 73.6 years; 66% males) completed the survey. Participants significantly preferred vehicles with better “Fuel efficiency” (OR 1.57, 95%Cl 1.44–1.71) and AVT inclusions (OR 1.29, 95%Cl 1.20–1.40), and were less likely to choose more expensive vehicles (per $5000 increase; OR 0.91, 95%Cl 0.86–0.99). “Access” did not influence choice between the two vehicle options. Those on a pension were price sensitive: twice as likely to choose a vehicle with better “fuel efficiency” and approximately 40 % less likely to choose a more expensive vehicle. Participants were willing to pay at most $1,604.17 (95%Cl $337.60-$3,174.50) extra for a car with AVTs that otherwise would cost $30,000. Conclusion: Despite showing interest in AVTs, older adults place more importance on price and fuel efficiency, and therefore would only pay a modest amount to get a car with more technological features. Practical applications: These results can help road safety professionals, industry and policy makers better communicate the value of AVTs to older drivers and help promote the uptake of AVTs and safety amongst older drivers.