Severity of motorcycle crashes in Calgary

Abstract

Motorcycle riders would be more vulnerable in the event of a crash because of their lack of protection which would often result in them suffering more severe injuries than car drivers. This paper estimated three crash severity models to identify factors that contributed to increasing the severity of motorcycle involved crashes in the Canadian City of Calgary. We found that results from the ordered logit model, heterogeneous choice model and partially constrained generalized ordered logit model produced estimates that were very similar which attested to their robustness. Injury severity tended to increase in neighborhoods with loops and lollipops types of streets or involved right-angle and left-turn-across-path crashes, a truck, unsafe speed or alcohol use but tended to decrease if the crash occurred in parking lots or during winter, involved a van or male rider, or a rider following-too-closely to the vehicle in front.

Introduction

Road crashes are a leading cause of deaths and serious injuries around the world, with about 1.2 million people killed each year. Compared to other vehicle drivers, motorcycle riders are often considered as more vulnerable because of their lack of protection in the event of a crash. Hence, motorcycle riders are often associated with high fatality and injury risks. According to Statistics Canada, around 2.35% of the total registered vehicles in 2008 the Province of Alberta comprised of powered two wheelers (motorcycles and mopeds). However, motorcycle riders comprised 10.2% and 3.8% of the total road users killed and injured in 2008 (Alberta Transportation, 2008).

In order to improve the safety of these vulnerable road users, a number of studies have thus investigated the factors affecting motorcycle crash severity (Clarke et al., 2007, Haque et al., 2010, Kasantikul et al., 2005, Gabella et al., 1995, Conrad et al., 1996, Branas and Knudson, 2001, Savolainen and Mannering, 2007, Lapparent, 2006, Zambon and Hasselberg, 2006, Yannis et al., 2005, Li et al., 2009, Majdzadeh et al., 2008, Quddus et al., 2002). These factors include: road design characteristics such as number of lanes, wide median, uncontrolled left turn, and exclusive right-turn lane; riders characteristics and actions such as rider's age, gender, alcohol intoxication, speeding, use of helmet, loss of the control of motorcycle, right of way violation, and traffic control signal violation; road characteristics such as local road, intersection, and highways; environmental characteristics such as lighting condition, and time of crashes; and vehicle characteristics such as engine capacity and headlight.

Not surprisingly, these studies have produced mixed results on the importance of different contributing factors. One obvious reason for these inconsistencies is the differences in driver behaviour, vehicle composition and the traffic and road environments in different jurisdictions studied. Another reason is the differences in the statistical methodologies used. Since different modeling techniques impose different assumptions, identifying contributing factors using observational data is likely to result in different outcomes if different methods are used. Hence, it is important that more studies be conducted using different estimation techniques and data from different jurisdictions to provide a more complete picture on the safety effects of these factors.

The purpose of this paper is to identify the factors contributing to the severity of motorcycle crashes in the Canadian City of Calgary in the Province of Alberta using data from 2003 to 2005. To check the robustness of our results with respect to different methodologies used, this study will estimate three different severity models using the standard ordered logit model, the heterogeneous choice model and the partially constrained generalized logit model. In addition, we will examine effect of the urban street pattern on crash severity.

Recently, the authors have undertaken a series of studies to identify the influence of street pattern on injury severity of different crashes involving two-vehicle (Rifaat and Tay, 2009), single vehicle (Rifaat et al., 2011b) and pedestrian and bicycle (Rifaat et al., 2011a). As a part of their continuing efforts, this study examines how the different street patterns may affect the severity of motorcycle involved collisions. Besides street pattern, other factors related to road features, drivers’ characteristics, crash characteristics, environment condition and vehicle attributes are also explored as control variables.