Modeling offenses among motorcyclists involved in crashes in Spain

Abstract

In relative terms, Spanish motorcyclists are more likely to be involved in crashes than other drivers and this tendency is constantly increasing. The objective of this study is to identify the factors that are related to being an offender in motorcycle accidents. A binary logit model is used to differentiate between offender and non-offender motorcyclists. A motorcyclist was considered to be offender when s/he had committed at least one traffic offense at the moment previous to the crash. The analysis is based that inexperienced, older females, not using helmets, absent-minded and non-fatigued riders are more likely to be offenders. Moreover, riding during the night, on weekends, for leisure purposes and along roads in perfect condition, mainly on curves, predict offenses among motorcyclists. The findings of this study are expected to be useful in developing traffic policy decisions in order to improve motorcyclist safety.

Comprehensive Analysis of Wrong-Way Driving Crashes on Alabama Interstates

“…Few focused on comparing WWD crashes with non-WWD crashes to test the significance of the identified contributing factors, which can be done with logistic regression models. Myriad previous research investigated the effect of several factors on one particular outcome in the field of traffic safety by using logistic regression models (12)(13)(14)(15)(16)(17). In this paper, a new logistic method-Firth's penalized likelihood logistic regression-is used to characterize WWD crashes while accounting for the effect of all confounding parameters.…”

Motorcyclists’ Mortality Pattern in Colombia from 2000 to 2013: A Longitudinal Study

“…The high incidence of mortality rate among population 15 and 34 years of age could be related to limited skills and abilities to drive [74], lack of knowledge of road safety rules [27], lack of technical expertise to make decisions in risky situations and "overconfidence" [75][76][77][78].…”

“…Moreover, it has also been corroborated by several authors that in low-income countries the high incidence of mortality rate is a result of several circumstances, such as negligible use of personal protective equipment, slight low enforcement, frequent breach of traffic laws, driving at high speeds, culture of diving in zigzag patterns, use of cell phones while driving, and low perception of risk on unsafe driving conditions with little traffic signals [20][21][22][23][24][25][26][27][28][29].…”

“…Among them, the following factors has been observed: most of motorcyclist do not respect red lights; very often they ride on sidewalks and on pedestrian walkways; they make zigzag driving movements in and out of cars and lanes; they do not wear motorcycle helmet, or if they do, they do not wear it correctly or do not wear the type of helmet that provides the best safety conditions [51][52][53][54][55][56][57][58][59]. Additionally, few of them use reflective vests even during the hours that it is mandatory; the backseat riders do not use personal protection gear [6]; very often motorcyclists ride at excessive speed, and they do not stay in before the lane when they stop at red lights [27,32,39,53,[60][61][62][63].…”

Opportunities for Using Building Information Modeling to Improve Worker Safety Performance

“…In doing so, the binary logistic regression modeling framework was utilized due to having only two possible outcomes-1 if BIM increases safety and 0 otherwise. This modeling framework has been utilized and presented in transportation safety literature [30][31][32][33], yet applying this econometric technique with regard to construction safety is scarce. With that in mind, to determine the probability that the outcome takes the value 1 (e.g., BIM increases safety), the following binary logit form applies [34]:…”