Incorporating The Home Address of Road Users Involved in Traffic Crashes in Road Safety Analysis

Traditionally, road safety metrics are measured at the location of the crash and its surrounding area. For example, if a crash occurs at an intersection, depending on the scope of the study, the researchers or practitioners may count crashes at intersection level, corridor level, or at a coarser geographic area such as Traffic Analysis Zone (TAZ), city level, or county level. Attributing crash to the location of the crash helps us learn about the relationship between road, environment, traffic, and weather and road safety. Based on this practice, several countermeasures have been developed to prevent crashes or reduce the severity of traffic crashes. As a result, a large body of road safety literature was allocated to road and geometry design and their effect on traffic crashes. In my dissertation, I set out to take a more epidemiological approach to road safety analysis, looking at factors such as social geography and travel behavior surrounding the home addresses of the road users involved in traffic crashes –i.e., a Home-Based Approach. Knowing more about the role of a human factor origin, and expressly sociodemographic, and travel behavior could help us to understand road safety from a different perspective that enables researchers and road safety practitioners to target individuals with proper countermeasure and intervention with the intention of reducing crash risk or eliminating aberrant behaviors of road users. My dissertation consists of five chapters. I explored different applications of the Home-Based Approach (HBA) methods in economical cost of traffic crashes, seat belt use analysis, and negative externalities of the tourism industry

Not gendered...but different from each other? A structural equation model for explaining risky road behaviors of female and male pedestrians.

As alternative transportation is getting more and more fashionable, and more people worldwide are 'shifting' to walking trips, even for their daily commuting, traffic crashes suffered by pedestrians are still a great concern for road safety and public health researchers and practitioners. In this regard, risky or 'aberrant' road behaviors have emerged, during the last few years, as a key issue to be considered for crash prevention. Nevertheless, the idea of a 'generic pedestrian' is getting re-evaluated, and analyzing key features, such as gender, seems to be crucial for understanding pedestrians' performance and safety outcomes. Objective: The objective of this study was to examine the effect of gender on pedestrians' both deliberate (traffic violations) and undeliberate (errors) risky walking behaviors, considering a set of theoretically based demographic and psychosocial variables as their potential predictors. Method: For this cross-sectional study, data from 1070 Spanish pedestrians (60 % females and 40 % males, aged between 16 and 79) from the 17 regions of Spain, responding to an electronic questionnaire, were analyzed through a multi-group structural equation modeling (MGSEM) approach. Results: Although age, handheld device-interaction, and sensation-seeking seem to have a similar effect on the errors and violations reported by both genders (similarities), factors such as risk perception, educational level and the misbehaviors observed in other road users are significant predictors only in the case of male pedestrians. On the other hand, road distractions have been shown to play a significant role in females' errors and violations, while males' road distractions seem to only affect their involuntary risky behaviors. Conclusion: The findings of this study support the influence of gender in the statistical explanation of both deliberate and undeliberate walking risky road behaviors, also depicting the differential role of certain demographic and psychosocial factors when we compare male and female pedestrians

Predictors of Self-reported Crashes among Iranian Drivers: Exploratory Analysis of an Extended Driver Behavior Questionnaire

More than 16,500 people lose their lives each year due to traffic crashes in Iran, which reflects one of the highest road traffic fatality rates in the world. The aim of the present study is to investigate the factors structure of an extended Driver Behaviour Questionnaire (DBQ) and to examine the gender differences in the extracted factors among Iranian drivers. Further, the study tested the association between DBQ factors, demographic characteristics, and self-reported crashes. Based on Iranian driving culture, an extended (36 items) Internet-based version of the DBQ was distributed among Iranian drivers. The results of Exploratory Factor Analysis based on a sample of 632 Iranians identified a five-factor solution named “Speeding and Pushing Violations”, “Lapses and Errors”, “Violations Causing Inattention”, “Aggressive Violations” and “Traffic Violations” which account for 44.7 percent of the total variance. The results also revealed that females were more prone to Lapses and Errors, whereas males reported more violations than females. Logistic regression analysis identified Violations Causing Inattention, Speeding and Pushing Violations as predictors of self-reported crashes in a three-year period. The results were discussed in line with road traffic safety countermeasures suitable for the Iranian context.</p

Intention to use bicycle helmet as explained by the Health Belief Model, comparative optimism and risk perception in an Iranian sample

The present study was set out to identify variables which predict intention to use helmet among bicyclists. The theoretical framework was based on the Health Belief Model (HBM) integrated with risk perception and comparative optimism, as relevant constructs from the risk theories. The results were based on an internet survey carried out among bicyclists (n = 256). A second-order SEM revealed that while controlling for gender, age and cycling experience, risk perception (β = .113, p < .05) fully mediated the effect of comparative optimism (β = −.201, p < .05) on intention to use a helmet. Perceived exemption from harm (β = −.340, p < .05) and perceived barriers (β = −.507, p < .001) were also found to be significant predictors of intention to use a bicycle helmet. The hypothesized model explained 55.8 percent of the variance within the intention to use a bicycle helmet. Theoretical implications of these findings are discussed

Predictors of Self-Reported Crashes Among Iranian Drivers: Exploratory Analysis of an Extended Driver Behavior Questionnaire

More than 16,500 people lose their lives each year due to traffic crashes in Iran, which reflects one of the highest road traffic fatality rates in the world. The aim of the present study is to investigate the factors structure of an extended Driver Behaviour Questionnaire (DBQ) and to examine the gender differences in the extracted factors among Iranian drivers. Further, the study tested the association between DBQ factors, demographic characteristics, and self-reported crashes. Based on Iranian driving culture, an extended (36 items) Internet-based version of the DBQ was distributed among Iranian drivers. The results of Exploratory Factor Analysis based on a sample of 632 Iranians identified a five-factor solution named “Speeding and Pushing Violations”, “Lapses and Errors”, “Violations Causing Inattention”, “Aggressive Violations” and “Traffic Violations” which account for 44.7 percent of the total variance. The results also revealed that females were more prone to Lapses and Errors, whereas males reported more violations than females. Logistic regression analysis identified Violations Causing Inattention, Speeding and Pushing Violations as predictors of self-reported crashes in a three-year period. The results were discussed in line with road traffic safety countermeasures suitable for the Iranian context

A home-based approach to understanding seatbelt use in single-occupant vehicles in Tennessee: Application of a latent class binary logit model

Although the enforcement of seatbelt use is considered to be an effective strategy in reducing road injuries and fatalities, lack of seatbelt use still accounts for a substantial proportion of fatal crashes in Tennessee, United States. This problem has raised the need to better understand factors influencing seatbelt use. These factors may arise from spatial/temporal characteristics of a driving location, type of vehicle, demographic and socioeconomic attributes of the vehicle occupants, driver behaviours, attitudes, and social norms. However, the above factors may not have the same effects on seatbelt use across different individuals. In addition, the behavioural factors are usually difficult to measure and may not always be readily available. Meanwhile, residential locations of vehicle occupants have been shown to be associated with their behavioural patterns and thus may serve as a proxy for behavioural factors. However, the suitability of geographic and residential locations of vehicle occupants to understand the seatbelt use behaviour is not known to date. This study aims to fill the above gaps by incorporating the residential location characteristics of vehicle occupants in addition to their demographics and crash characteristics into their seatbelt use while accounting for the varying effects of these factors on individual seatbelt use choices. To achieve this goal, empirical data are collected for vehicular crashes in Tennessee, United States, and the home addresses of vehicle occupants at the time of the crash are geocoded and linked with the census tract information. The resulting data is then used as explanatory variables in a latent class binary logit model to investigate the determinants of vehicle occupants’ seatbelt use at the time of the crash. The latent class specification is employed to capture the unobserved heterogeneity in data. Results show that Tennessean drivers belong to two general categories—conformist and eccentric—with gender, vehicle type, and income per capita determining the likelihood of these categories. Overall, male drivers, younger drivers, and drivers who have consumed drugs are less likely to wear a seatbelt, whereas drivers who come from areas with higher population density, travel time, and income per capita are more likely to wear a seatbelt. In addition, driving during the day and in rainy weather are associated with an increased likelihood of seatbelt use. The findings of this study will help developing effective policies to increase seatbelt use rate and improve safety.</p

Residential accessibility's relationships with crash rates per capita

This paper examines the relationship between residential accessibility, i.e., accessibility from a person's home address, and their likelihood of being in a crash over a three-year period. We explore two potential relationships with accessibility. The first is that persons who live in areas with high destination accessibility may drive less and therefore are less likely to be in vehicular crashes. The second is that persons who live in high vehicle miles traveled (VMT) accessibility areas may be exposed to higher levels of traffic in their regular activity space and therefore may be more likely to be in crashes of all modal types. Examining traffic analysis zones in Knoxville, Tennessee, this research finds some evidence for each of these hypothesized effects. These oppositely directed effects have dominant influence within different travel-time thresholds. The first relationship between destination accessibility and fewer crashes is found to be strongest for 10-minute auto accessibility, whereas the second relationship between VMT accessibility and more crashes is found to occur at 10-minute, 20-minute, and 30-minute thresholds

Errors and Violations in Relation to Bicyclists' Crash Risks: Development of the Bicycle Rider Behavior Questionnaire (BRBQ)

Promoting bicycling has several health benefits at the individual- and population-level. However, safety concerns for bicyclists is one of the main hindrances for bicycling. Little work has explored aberrant riding behavior, and to the best of our knowledge, no instrument that measures aberrant behavior among bicyclists has been reported in the literature. This study reports the psychometric properties of a newly designed measurement instrument, the Bicycle Rider Behavior Questionnaire (BRBQ) that follows methodological approaches of motorized vehicle user behavior questionnaires. The BRBQ is a 34-item questionnaire that relies on Principal Component Analysis with Varimax Rotation to identify dimensions of aberrant behavior and ultimately predict self-reported multi-vehicles crashes. We illustrated this approach on a sample of 306 bicyclists in Iran and developed a five-dimension solution that explained 51% of the total variance. The dimensions were termed: “Stunts and Distractions”, “Traffic Violations”, “Notice Failures”, “Control Errors”, and “Signaling Violations” with Cronbach’s alpha ranging from 0.70 to 0.84. On average, males reported more Stunts and Distractions than females, while females reported more Control Errors than males. Bivariate correlations between dimensions and riding experience indicated that as years of riding experience increased, aberrant behaviors of riders declined. Further, as riders grow older, the occurrence of their reported Control Errors and Signaling Violations increased. Logistic regression results showed that Traffic Violations, Stunts and Distractions, and Signaling Violations were the predictors of at-fault self-reported multi-vehicle crashes. Traffic Violations, Control Errors, and Notice Failures were the predictors of all self-reported multi-vehicle crashes. The BRBQ was found to have feasible psychometric properties and had good criterion validity that supports the original theoretical taxonomy of human errors. The findings present a sample of Iranian bicyclists and need further validation in other settings

A home-based approach to understanding seatbelt use in single-occupant vehicles in Tennessee: Application of a latent class binary logit model

Although the enforcement of seatbelt use is considered to be an effective strategy in reducing road injuries and fatalities, lack of seatbelt use still accounts for a substantial proportion of fatal crashes in Tennessee, United States. This problem has raised the need to better understand factors influencing seatbelt use. These factors may arise from spatial/temporal characteristics of a driving location, type of vehicle, demographic and socioeconomic attributes of the vehicle occupants, driver behaviours, attitudes, and social norms. However, the above factors may not have the same effects on seatbelt use across different individuals. In addition, the behavioural factors are usually difficult to measure and may not always be readily available. Meanwhile, residential locations of vehicle occupants have been shown to be associated with their behavioural patterns and thus may serve as a proxy for behavioural factors. However, the suitability of geographic and residential locations of vehicle occupants to understand the seatbelt use behaviour is not known to date. This study aims to fill the above gaps by incorporating the residential location characteristics of vehicle occupants in addition to their demographics and crash characteristics into their seatbelt use while accounting for the varying effects of these factors on individual seatbelt use choices. To achieve this goal, empirical data are collected for vehicular crashes in Tennessee, United States, and the home addresses of vehicle occupants at the time of the crash are geocoded and linked with the census tract information. The resulting data is then used as explanatory variables in a latent class binary logit model to investigate the determinants of vehicle occupants’ seatbelt use at the time of the crash. The latent class specification is employed to capture the unobserved heterogeneity in data. Results show that Tennessean drivers belong to two general categories—conformist and eccentric—with gender, vehicle type, and income per capita determining the likelihood of these categories. Overall, male drivers, younger drivers, and drivers who have consumed drugs are less likely to wear a seatbelt, whereas drivers who come from areas with higher population density, travel time, and income per capita are more likely to wear a seatbelt. In addition, driving during the day and in rainy weather are associated with an increased likelihood of seatbelt use. The findings of this study will help developing effective policies to increase seatbelt use rate and improve safety.Safety and Security Scienc