Benchmarking road safety performance: Identifying a meaningful reference (best-in-class)

Chen, Faan; Wu, Jiaorong; Chen, Xiaohong; Wang, Jianjun; Wang, Di

doi:10.1016/j.aap.2015.10.018

Cited by 48 publications

(21 citation statements)

References 18 publications

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“…The index was derived from the probability of accidents based on Logistic Regression with a set of variables such as ship age, size and nationality, etc. In road safety management, Chen et al (2016) developed safety index by combining the indicators of safety performance, policy and culture. The proposed index was used to benchmark road safety performance in European Union.…”

Section: Philosophiesmentioning

confidence: 99%

Vessel traffic safety in busy waterways: A case study of accidents in western shenzhen port

Mou

Chen

et al. 2019

Accident Analysis & Prevention

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Section: Philosophiesmentioning

confidence: 99%

Vessel traffic safety in busy waterways: A case study of accidents in western shenzhen port

Mou

Chen

et al. 2019

Accident Analysis & Prevention

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“…(1) m K g (1) Figure 1 -Indicators hierarchy for constructing GreyCI similar road safety backgrounds, identify the best-inclass and learn from it [12]. In this study, the grouping is made based on the methodology described in Chen et al [25]. The distribution of gCI is determined, following the frequencies, cumulative frequencies, percentiles and corresponding probit.…”

Section: Construction Of the Grey Composite Indicatormentioning

confidence: 99%

“…For detailed steps of the grouping see Chen et al [25]. To ensure that the grouping is statistically significant (P<0.01), the analysis of variance is performed with 95% level of confidence.…”

Section: Greycimentioning

confidence: 99%

Construction of Road Safety Composite Indicator Using Grey Relational Analysis

Grdinić-Rakonjac

Antić

Pešić

et al. 2021

PROMET

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Aggregation of different variables into one road safety performance index is a popular concept in evaluating road safety and comparing the performance of territories/entities. This paper presents the development of a novel and innovative weighting methodology using grey relational analysis. Based on the proposed model, ten hierarchical road safety indicators were selected in terms of a two-layered model with three categories related to behaviour, safety and system. Grey weights are assigned to the categorized indicators in each layer, and the grey road safety composite indicator for each entity (21 selected territories) is calculated by the weighted sum approach. With relatively high weights, this systematic methodology can serve the policy makers in targeting the risk domains where improvements are needed. The results clearly illustrate effectiveness in addressing a large number of indicators with hierarchical structures.

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“…In the US, there are approximately 33000 traffic fatalities per year (Wu et al 2013). In Europe, 26009 people were killed as a result of TCs in 2013 in the 28 EU countries (Chen et al 2016). In Australia and New Zealand, respectively, 31 and 16% of fatal occupational incidents are TCs (Naevestad et al 2015).…”

Section: Introductionmentioning

confidence: 99%

An Approach for Traffic Collision Avoidance: Measuring the Similar Evidence on the Causal Factors of Collisions

Kang

Zhang

2021

Transport

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The lessons learned from each Traffic Collision (TC) will help safety practitioners to avoid similar occurrences in the future. However, few studies and methods have focused specifically on the similar features among different collisions. Thus, the development of a measurement method for investigating the best evidence on the causal factors of TCs was warranted. In this study, a similarity analysis method based on the Analytic Hierarchy Process (AHP) and Similarity (S) theory, the AHP-S method, was constructed. This method was designed to identify the similar elements and similar units of collision scenes according to the analysis criteria and sub-criteria and further to calculate the degree of similarity between recognized similar pairs among TCs. Six TC cases were randomly selected as examples, and the degrees of similarity between cases 1 to 5 and case 6 were calculated separately. The calculation results showed that out of the five collision cases (cases 1–5), case 1 provided the best evidence for analysing the causal factors of case 6. This study promotes the development of quantitative analysis methods for collision incidents and provides an effective evidence-based method for TC avoidance.

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Benchmarking road safety performance: Identifying a meaningful reference (best-in-class)

Cited by 48 publications

References 18 publications

Vessel traffic safety in busy waterways: A case study of accidents in western shenzhen port

Vessel traffic safety in busy waterways: A case study of accidents in western shenzhen port

Construction of Road Safety Composite Indicator Using Grey Relational Analysis

An Approach for Traffic Collision Avoidance: Measuring the Similar Evidence on the Causal Factors of Collisions

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