Exploring the application of latent class cluster analysis for investigating pedestrian crash injury severities in Switzerland

Sasidharan, Lekshmi; Wu, Kun Feng; Menéndez, Mónica

doi:10.1016/j.aap.2015.09.020

Cited by 105 publications

(52 citation statements)

References 25 publications

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“…Recent research (Abegaz et al, 2014) highlighted that minibus or van involved accidents were found to be more severe injuries. The estimation results of other past studies Sasidharan et al, 2015;Wu et al, 2014) put forward accidents involving heavy vehicles were more likely to increase the level of injury severity.…”

Section: Earlier Studiesmentioning

confidence: 76%

“…For instance, road grade (Chen et al, 2015) was highly associated with an increase on fatal injuries, while asphalt roads (Ma et al, 2015) were found as another contributing risk factor of injury severity. Moreover, traffic accidents occurred on national roads (Sasidharan et al, 2015) were found to increase the probability of more severe injuries. On the other hand, a most recent study (Behnood and Mannering, 2015) found that road construction is associated with the increase of less severe injuries.…”

Section: Earlier Studiesmentioning

confidence: 99%

“…Many earlier research (Chu, 2015;Chung et al, 2014;Hao and Daniel, 2014;Kim et al, 2008;Kröyer, 2015;Ma et al, 2015;Mitchell et al, 2015;Sasidharan et al, 2015) exhibited driver's violation of speed limits were extensively associated with increasing more severe injuries. The results of another earlier research revealed that speed control might have a significant impact on decreasing more severe injuries.…”

Section: Earlier Studiesmentioning

confidence: 99%

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A Comparison of Ordered and Unordered Response Models for Analyzing Road Traffic Injury Severities in the North-Eastern Turkey

Çelik

Oktay

2017

Period. Polytech. Transp. Eng.

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Section: Earlier Studiesmentioning

confidence: 76%

Section: Earlier Studiesmentioning

confidence: 99%

Section: Earlier Studiesmentioning

confidence: 99%

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A Comparison of Ordered and Unordered Response Models for Analyzing Road Traffic Injury Severities in the North-Eastern Turkey

Çelik

Oktay

2017

Period. Polytech. Transp. Eng.

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“…Table 4 shows the estimation results of the different models. Following Kim et al (2007) [34] and Sasidharan et al (2015) [36], a significance level of 10% was used in this analysis. In Table 4, only statistically significant variables at a significance level of 10% have been represented.…”

Section: Injury Severity Analysis Using Mnlmentioning

confidence: 99%

Investigating the Risk Factors Associated with the Severity of the Pedestrians Injured on Spanish Crosstown Roads

et al. 2019

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According to the Spanish General Traffic Accident Directorate, in 2017 a total of 351 pedestrians were killed, and 14,322 pedestrians were injured in motor vehicle crashes in Spain. However, very few studies have been conducted in order to analyse the main factors that contribute to pedestrian injury severity. This study analyses the accidents that involve a single vehicle and a single pedestrian on Spanish crosstown roads from 2006 to 2016 (1535 crashes). The factors that explain these accidents include infractions committed by the pedestrian and the driver, crash profiles, and infrastructure characteristics. As a preliminary tool for the segmentation of 1535 pedestrian crashes, a k-means cluster analysis was applied. In addition, multinomial logit (MNL) models were used for analysing crash data, where possible outcomes were fatalities and severe and minor injured pedestrians. According to the results of these models, the risk factors associated with pedestrian injury severity are as follows: visibility restricted by weather conditions or glare, infractions committed by the pedestrian (such as not using crossings, crossing unlawfully, or walking on the road), infractions committed by the driver (such as distracted driving and not respecting a light or a crossing), and finally, speed infractions committed by drivers (such as inadequate speed). This study proposes the specific safety countermeasures that in turn will improve overall road safety in this particular type of road.

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“…A great deal of attention has been dedicated to age and gender of the pedestrians because of the higher involvement of males (Al-Madani and Al-Janahi, 2006; Kim et al, 2008;Mabunda et al, 2008;Prato et al, 2012;Mohamed et al, 2013;Iragavarapu et al, 2015;Tulu et al, 2015) and the higher vulnerability of children and/or elderly (Al-Ghamdi, 2002;Preusser et al, 2002;Eluru et al, 2008;Prato et al, 2012;Hanson et al, 2013;Abdel-Aty et al, 2013;Tulu et al, 2015). Attention has been given also to the type of vehicle involved in the crash (Ballesteros et al, 2004;Kim et al, 2008), the modality of the crash (Al-Ghamdi, 2002;Preusser et al, 2002;Mohamed et al, 2013;Sasidharan et al, 2015), the location in urban environments and the land use destination (Al-Ghamdi, 2002;Montella et al, 2011;Sasidharan et al, 2015;Amoh-Gyimah et al, 2016;Tran et al, 2016;Wang et al, 2016), and the intoxication level of pedestrians (e.g., Fontaine and Gourlet, 1997;Öström and Eriksson, 2001;Mabunda et al, 2008;Hanson et al, 2013;Iragavarapu et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Integrating police reports with geographic information system resources for uncovering patterns of pedestrian crashes in Denmark

Prato

Kaplan

Patrier

et al. 2019

Journal of Transport Geography

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Promoting walking goes a long way in contributing to the sustainability and health of future cities and regions, and improving pedestrian safety is essential for building more sustainable and healthier communities. As the problem is multifaceted in nature, this study looks at patterns of pedestrian crashes from a perspective that goes beyond the traditional investigation of pedestrian characteristics and behaviour by analysing the contribution of built environment, land use, and traffic conditions. Moreover, this study goes beyond the traditional analysis of traditional police reports by integrating them with rich geographic information system resources. This study analysed a sample of 7469 crashes between a pedestrian and another road user that occurred in Denmark between 2006 and 2015. The crash locations were geocoded and matched to a detailed traffic network, a transport planning model, and several resources detailing building and land use composition. Latent class analysis uncovered patterns of pedestrian crashes for both the fully identified records and the substantial amount of hit-and-run records. Findings from this study reveal a major red thread in the lack of hazard awareness for both pedestrians and road users and suggest solutions from both the behavioural and the infrastructure perspectives. Major needs are (i) educating pedestrians about the risks related to drinking and then walking along major roads in the darkness, (ii) making crossings for pedestrians and approaches for road users easier to understand and to access in order to reduce unnecessary conflicts, and (iii) designing traffic calming solutions around major shopping and leisure locations in dense city centres.

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Exploring the application of latent class cluster analysis for investigating pedestrian crash injury severities in Switzerland

Cited by 105 publications

References 25 publications

A Comparison of Ordered and Unordered Response Models for Analyzing Road Traffic Injury Severities in the North-Eastern Turkey

A Comparison of Ordered and Unordered Response Models for Analyzing Road Traffic Injury Severities in the North-Eastern Turkey

Investigating the Risk Factors Associated with the Severity of the Pedestrians Injured on Spanish Crosstown Roads

Integrating police reports with geographic information system resources for uncovering patterns of pedestrian crashes in Denmark

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