Journal
INTERNATIONAL JOURNAL OF CRASHWORTHINESS
Volume 27, Issue 6, Pages 1697-1707Publisher
TAYLOR & FRANCIS LTD
DOI: 10.1080/13588265.2021.2008174
Keywords
Two-wheelers; intersections; crash severity; logistic regression
Funding
- Ministry of Education (MoE), Government of India
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Two-wheelers have become a standard transportation mode for short-distance travellers, especially in developing countries, but they also come with safety concerns, particularly at intersections. Research findings show that certain variables (such as age, gender, environmental conditions) increase the likelihood of fatal injuries, while other variables (such as crash date, intersection type) decrease the probability of fatal injuries.
For short-distance travellers, two-wheelers have become a standard transportation mode and an ideal alternative (compact size, economical, easy parking), to four-wheelers particularly in developing countries. However, two-wheelers are associated with different safety concerns. In India, two-wheelers are more vulnerable to fatal and serious injuries per kilometres of travel in contrast to drivers of other vehicles. Most of these accidents occur on junctions and are likely to be fatal and more severe in contrast to nonjunction accidents. This research article aims to examines different risk variables associated with motorized two-wheeler crashes at intersections (signalized and un-signalized) in Haridwar and Dehradun districts of Uttarakhand state, India. A multinominal logistic approach was used to analyse a dataset of 680 two-wheeler crashes occurred within four years (2016-2019). The accident severities were categorized into three groups, i.e. fatal injury, serious injury and normal injury. The risk variables were categorized into five significant classes, i.e. riders' attributes, environmental attributes, junction crash attributes and land-use attributes. However, the majority of this study's findings endorses the concepts derived from earlier researches that used alternative (for instance; random forest, ordered logit, etc.) analytical methodologies in crash severity analysis. The model results showed that some variables (e.g. age, gender, adverse environmental conditions, time of crash and location of the junction) increases the possibility of mortal injuries. In contrast, some variables (day of crash, type of intersection and type of controls at intersections) decrease the probability of mortal injuries compared with minor or severe injuries. Based on the model's findings, policy recommendations are made, such as enforcing rules, advanced traffic management systems and road safety campaigns. For instance, education of young drivers can be an effective way to reduce crash severity as they are physiologically less sensitive towards the risk associated with crashes, thus, their involvement results in more severe crashes. Additionally, the results suggested that treatment measures such as transforming an un-controlled junction into signalized or all-way stop controls can be a productive approach for improving the safety of uncontrolled junctions.
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