Intersection Related Crash Injuries: A Study on Factors Contributing to Injury Severity among Younger and Older Drivers in Summer and Winter

Older drivers and younger drivers are affected differently both in summer and winter. Different factors affect each level of severity differently;some factors affect a particular level of injury severity differently from when the same factor is analyzed for another injury severity. The goal of this study is to identify the factors that contribute to injury severity among older drivers (65+) and young drivers (16 - 25) considering two seasons namely, summer and winter at intersections. Binary ordered probit models were used to develop four models to identify the contributing factors, two models for each season, namely winter and summer. A statistical t-test has been done to identify the statistically significant variables @ 90% confidence interval. Based on the developed models, in summer, three contributing factors, driving too fast condition, rear-end crashes, and followed too close are associated with younger drivers injury severity, while two contributing factors, rear-end crashes and followed too close are associated with older drivers injury severity. In winter, five factors, made an improper turn, E Failed to Yield Right-of-Way from Traffic Signal, rear end (front to rear), gender like male and lighting condition like dark and dusk light condition, are associated with younger drivers injury severity, while three factors such as made improper turn, rear-end crashes, and followed too close are associated with older drivers injury severity. Contributing factors in summer are the same for both younger and older drivers, but different in winter for both younger and older drivers. This indicates that older drivers and younger drivers are affected differently both in summer and winter.

The effect of ride experience on changing opinions toward autonomous vehicle safety

Autonomous vehicles(AVs)are a promising emerging technology that is likely to be widely deployed in the near future.People's perception on AV safety is critical to the pace and success of deploying the AV technology.Existing studies found that people's perceptions on emerging technologies might change as additional information was provided.To investigate this phenomenon in the AV technology context,this paper conducted real-world AV experiments and collected factors that may associate with people's initial opinions without any AV riding experience and opinion change after a successful AV ride.A number of ordered probit and binary probit models considering data heterogeneity were employed to estimate the impact of these factors on people's initial opinions and opinion change.The study found that people's initial opinions toward AV safety are significantly associated with people's age,personal income,monthly fuel cost,education experience,and previous AV experience.Further,the factors dominating people's opinion change after a successful AV ride include people's age,personal income,monthly fuel cost,daily commute time,driving alone indicator,willingness to pay for AV technology,and previous AV experience.These results provide important references for future implementations of the AV technology.Additionally,based on the inconsistent effects for variables across different models,suggestions for future transportation survey designs are provided.