Differences between pickup truck and automobile driver-owners

Hierarchical Bayesian random intercept model-based cross-level interaction decomposition for truck driver injury severity investigations

Traffic crashes occurring on rural roadways induce more severe injuries and fatalities than those in urban areas, especially when there are trucks involved. Truck drivers are found to suffer higher potential of crash injuries compared with other occupational labors. Besides, unobserved heterogeneity in crash data analysis is a critical issue that needs to be carefully addressed. In this study, a hierarchical Bayesian random intercept model decomposing cross-level interaction effects as unobserved heterogeneity is developed to examine the posterior probabilities of truck driver injuries in rural truck-involved crashes. The interaction effects contributing to truck driver injury outcomes are investigated based on two-year rural truck-involved crashes in New Mexico from 2010 to 2011. The analysis results indicate that the cross-level interaction effects play an important role in predicting truck driver injury severities, and the proposed model produces comparable performance with the traditional random intercept model and the mixed logit model even after penalization by high model complexity. It is revealed that factors including road grade, number of vehicles involved in a crash, maximum vehicle damage in a crash, vehicle actions, driver age, seatbelt use, and driver under alcohol or drug influence, as well as a portion of their cross-level interaction effects with other variables are significantly associated with truck driver incapacitating injuries and fatalities. These findings are helpful to understand the respective or joint impacts of these attributes on truck driver injury patterns in rural truck-involved crashes.

Prediction of vehicle crashes by drivers' characteristics and past traffic violations in Korea using a zero-inflated negative binomial model

AIMS

Traffic safety is a significant public health challenge, and vehicle crashes account for the majority of injuries. This study aims to identify whether drivers' characteristics and past traffic violations may predict vehicle crashes in Korea.

METHODS

A total of 500,000 drivers were randomly selected from the 11.6 million driver records of the Ministry of Land, Transport and Maritime Affairs in Korea. Records of traffic crashes were obtained from the archives of the Korea Insurance Development Institute. After matching the past violation history for the period 2004-2005 with the number of crashes in year 2006, a total of 488,139 observations were used for the analysis. Zero-inflated negative binomial model was used to determine the incident risk ratio (IRR) of vehicle crashes by past violations of individual drivers. The included covariates were driver's age, gender, district of residence, vehicle choice, and driving experience.

RESULTS

Drivers violating (1) a hit-and-run or drunk driving regulation at least once and (2) a signal, central line, or speed regulation more than once had a higher risk of a vehicle crash with respective IRRs of 1.06 and 1.15. Furthermore, female gender, a younger age, fewer years of driving experience, and middle-sized vehicles were all significantly associated with a higher likelihood of vehicle crashes.

CONCLUSIONS

Drivers' demographic characteristics and past traffic violations could predict vehicle crashes in Korea. Greater resources should be assigned to the provision of traffic safety education programs for the high-risk driver groups.

Another Look at “Look-Alikes”

Popular belief and recent findings suggest that dogs look like their owner - but are such pairs necessarily look-alikes or do we recognize their affiliation based on other information? We asked judges to match automobiles with their owners. They were able to identify the pairs above chance. The correlational analyses of actual information about owners' and automobiles' characteristics and their estimations suggest that stereotypes with respect to external clues about the owner and the automobiles were available to judges. People's appearance and certain characteristics of their possessions apparently carry information beyond physiognomic resemblance and these clues help to make inferences about their affiliation. The different mechanisms that judges might use to make connections between people and their cars are discussed.

Role of gender in road accidents

Influence of driver sex on road accidents is assessed in this article. Accident records for 3 years and for three different income regions were analyzed. Annual distance traveled, social and economic participation, and effect of public vehicle accidents were considered. Effects of environmental factors and driver age were also included. Driver faults analysis identified possible reasons for accident differences. Analysis of accident severity was used to assess degree of harm. Statistical analysis at the 5% significance level was used to evaluate all differences. The results show that male accident rates are significantly higher. This trend is consistent through all the analyses. Accident differences are significant only in normal driving conditions. Drivers over age 50 had the lowest accident rates. Accident rate differences were caused by lack of attention and impatience among male drivers. Appropriate means of communication should alert concerned populations to these findings.

Pickup truck use in the National Personal Transportation Survey

To guide interventions to prevent injuries to pickup-truck occupants, we characterized pickup truck ownership, drivers and use in the 1995 National Personal Transportation Survey, which collects travel data from the civilian noninstitutionalized population of the US. SUDAAN software was used to account for the complex nature of the sample. Pickup truck ownership was more common in households with more vehicles, in rural households, in households living in single family homes and mobile homes, and in middle-income households. Among US regions, pickup truck ownership was highest among households in the mountain west. Pickup truck ownership was greater in households with two adults, whether or not children or youths were present, but this was largely due to the number of vehicles in these households. Driving a pickup on the sample day was more frequent among men, among drivers with less education and among full-time workers. A higher proportion of trips to work, work-related trips, longer trips and trips with fewer people were by pickup truck. Seat belt use was lower among pickup truck drivers than drivers of other vehicles. For only 0.5% of households (those with three or more members and a pickup truck as their only vehicle), restrictions on travel in cargo areas might be burdensome. Restrictions on cargo area travel, strengthening existing seat belt laws and social marketing strategies might increase the safety of pickup truck occupants.